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Cognitive Control Disruption in Traumatic Brain Injury

Permanent Link: http://ufdc.ufl.edu/UFE0021099/00001

Material Information

Title: Cognitive Control Disruption in Traumatic Brain Injury
Physical Description: 1 online resource (122 p.)
Language: english
Creator: Larson, Michael
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: acc, anterior, brain, cingulate, cognitive, conflict, contingency, control, cortex, ern, erp, error, event, executive, feedback, frn, injury, mfn, monitor, n450, performance, potential, related, reward, stroop, tbi, trauma, traumatic
Clinical and Health Psychology -- Dissertations, Academic -- UF
Genre: Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Cognitive control comprises two essential interactive component processes: a regulative component supporting the activation and implementation of control and an evaluative component that monitors the need for regulative control and signals when adjustments in control are necessary. Survivors of severe traumatic brain injury (TBI) experience cognitive control impairments that frequently contribute to long-term disability, but the specific nature of these impairments is poorly characterized. Moreover, research on TBI-related cognitive control dysfunction has focused primarily on regulative control deficits. The current series of studies utilized behavioral (i.e., response time RT and error rates) and electrophysiological (i.e., event-related potentials ERPs) measures of cognitive control to test the hypotheses that: (1) survivors of severe TBI exhibit impairments compared to demographically-matched healthy control participants in the evaluative control functions of performance-monitoring, conflict detection, feedback utilization, and signaling for increased implementation of regulative control; and (2) both behavioral and electrophysiological manifestations of evaluative control impairment are associated with impairments in deficit awareness. Relative to healthy control participants, survivors of severe TBI showed attenuated neural reflections of both performance-monitoring and feedback context utilization; however, groups did not differ on putative measures of the evaluative control process of signaling for enhanced regulative control following conflict. Neither behavioral nor electrophysiological manifestations of evaluative control were associated with awareness of deficits in TBI survivors. Taken together, these findings suggest that survivors of severe TBI are impaired in the evaluative control functions of performance monitoring and feedback context utilization, but can still utilize conflict information to reactively adjust performance to changing task demands. Future research based on these findings may allow us to capitalize on the heterogeneity associated with TBI to identify clinically meaningful subtypes and appropriately tailor rehabilitation efforts to specific cognitive control deficits.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Michael Larson.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Perlstein, William.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021099:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021099/00001

Material Information

Title: Cognitive Control Disruption in Traumatic Brain Injury
Physical Description: 1 online resource (122 p.)
Language: english
Creator: Larson, Michael
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: acc, anterior, brain, cingulate, cognitive, conflict, contingency, control, cortex, ern, erp, error, event, executive, feedback, frn, injury, mfn, monitor, n450, performance, potential, related, reward, stroop, tbi, trauma, traumatic
Clinical and Health Psychology -- Dissertations, Academic -- UF
Genre: Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Cognitive control comprises two essential interactive component processes: a regulative component supporting the activation and implementation of control and an evaluative component that monitors the need for regulative control and signals when adjustments in control are necessary. Survivors of severe traumatic brain injury (TBI) experience cognitive control impairments that frequently contribute to long-term disability, but the specific nature of these impairments is poorly characterized. Moreover, research on TBI-related cognitive control dysfunction has focused primarily on regulative control deficits. The current series of studies utilized behavioral (i.e., response time RT and error rates) and electrophysiological (i.e., event-related potentials ERPs) measures of cognitive control to test the hypotheses that: (1) survivors of severe TBI exhibit impairments compared to demographically-matched healthy control participants in the evaluative control functions of performance-monitoring, conflict detection, feedback utilization, and signaling for increased implementation of regulative control; and (2) both behavioral and electrophysiological manifestations of evaluative control impairment are associated with impairments in deficit awareness. Relative to healthy control participants, survivors of severe TBI showed attenuated neural reflections of both performance-monitoring and feedback context utilization; however, groups did not differ on putative measures of the evaluative control process of signaling for enhanced regulative control following conflict. Neither behavioral nor electrophysiological manifestations of evaluative control were associated with awareness of deficits in TBI survivors. Taken together, these findings suggest that survivors of severe TBI are impaired in the evaluative control functions of performance monitoring and feedback context utilization, but can still utilize conflict information to reactively adjust performance to changing task demands. Future research based on these findings may allow us to capitalize on the heterogeneity associated with TBI to identify clinically meaningful subtypes and appropriately tailor rehabilitation efforts to specific cognitive control deficits.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Michael Larson.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Perlstein, William.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021099:00001


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280cbb8689d33e0599b3634dcf1ba25f3926be9c







COGNITIVE CONTROL DISRUPTION IN TRAUMATIC BRAIN INJURY


By

MICHAEL JAMES LARSON


















A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2008

































2008 Michael James Larson









ACKNOWLEDGMENTS

I wish to acknowledge my chair and mentor, William M. Perlstein, Ph.D., for his

assistance and support on this project and his guidance throughout graduate school. I also wish to

express gratitude to my other dissertation committee members, Russell M. Bauer, Ph.D., Dawn

Bowers, Ph.D., Michael Robinson, Ph.D., and Linda Shaw, Ph.D., for their assistance with this

endeavor. I would like to thank David Stigge-Kaufman, Cortney Mauer, Megan McIntyre, Drew

Nagle, Allen Sirizi, and Raechel Steckley for their assistance in participant recruitment and data

collection. This research was supported by pre-doctoral National Institute of Health Fellowship

#F31-NS-053335.









TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ...............................................................................................................3

L IS T O F T A B L E S ................................................................................. 6

LIST O F FIG U RE S ................................................................. 7

ABSTRAC T ..........................................................................................

CHAPTER

1 GENERAL INTRODU CTION ........................................ ..............................................11

Cognitive Control and Traumatic Brain Injury (TBI) .......................................................11
A w areness of D deficits in TB I .................. .................................... ................................... 15

2 AWARENESS OF DEFICITS, PERFORMANCE MONITORING, AND
EVALUATIVE CONTROL FOLLOWING SEVERE TRAUMATIC BRAIN INJURY .....19

Introduction ..................................... ................................................. 19
Awareness of Deficits, Performance Monitoring, and TBI......................................22
C u rren t S tu dy .. ................................................................................................2 3
M methods .......................... ............ ....... ....... ......................... .............. 23
Assessment of TBI Symptoms and Deficit Awareness .....................................26
Experim mental Task.............................................................. ................ 29
Electrophysiological Data Recording, Reduction, and Measurement.............................30
D ata A n aly sis .................................................................................. 3 1
R e su lts ................................................................................... ......... .... 3 2
B eh av ioral D ata ....................................... ... .. ........................... ............. ... 32
Event-related Potential (ERP) Data: Response-related Activity ..................................33
C orrelational A naly ses ..............................................................35
D iscu ssio n ....................................35.............................

3 COGNITIVE CONTROL ADJUSTMENT PROCESSES FOLLOWING SEVERE
TRAUMATIC BRAIN INJURY .................. .................. ........ ...................... ... 47

Introdu action ............................ .... .............................................................47
Conflict Adaptation vs. Repetition Priming .............................................. ......53
C u rre n t S tu d y ............................................................................................................. 5 4
M methods ..................................... ............................. ........ 55
Electrophysiological Data Recording ..................... ................... .................55
Event-related Potential Reduction and Measurement ............................................. 56
D ata Analysis............................................................. .. 57
Results .................................................. ................................. 58
B behavioral Perform ance .............. .................. ............................................ 58


4









E R P D a ta .................................................................................................................... 6 0
Im pact of R petition Prim ing ......... ................. .........................................................63
Correlational Analyses ......................... ..... .......... ........ ..... ..... 64
D isc u ssio n .............. ..... ............ ................. .......................................... 6 5

4 FEEDBACK UTILIZATION AND REWARD CONTEXT SENSITIVITY
IMPAIRMENT FOLLOWING SEVERE TRAUMATIC BRAIN INJURY .........................78

Introdu action ......... .............. ......................................... ............................79
Methods ........................................ 82
P articip an ts ................................................................8 2
E xperim ental T ask ....................... ...... ................................................... .... ........ ... 84
Electrophysiological Data Recording and Reduction................................................86
D ata A n a ly sis .............................................................................................................. 8 7
R e su lts .............. .......... .. .............. .. ........................................................... 8 8
Behavioral Data ............................................. ................... 88
E R P D a ta .................................................................................................................... 8 8
D isc u ssio n .............. ..... ............ ................. .......................................... 9 1

5 GENERAL DISCUSSION ......... ................... ............................... 101

L IST O F R EFE R EN C E S ........... .... .................................................. ...........................106

BIOGRAPHICAL SKETCH ........................................................................... ....... ........ ...... .......122









LIST OF TABLES


Table page

2-1 Demographic and mean summary data for severe traumatic brain injury (TBI) and
control participants....... .............................................................................. ....... .. .. .. 4 1

2-2 Injury characteristics and neuroradiological information for TBI participants .................42

2-3 Error rates and reaction times on the Stroop Task ......................................................43

2-4 Error-related negativity and post-error positivity component amplitude data as a
function of task condition. ........................................................................ ...................44

3-1 Reaction times for congruent and incongruent trials as a function of previous trial
congru ency .................................................................................7 1

3-2 Percent-errors for congruent and incongruent trials as a function of previous trial
congru ency .................................................................................7 1

3-3 Difference scores for reaction times and error rates of the incongruent minus
congruent difference. ........................ ......... .. .. ........ .. ............. 71

3-4 Amplitude data for the N450 and conflict slow potential components. ..........................72

4-1 Demographic data for the subset of control and TBI participants..............................96

4-2 Injury characteristics and neuroradiological information for the subset of TBI
participants .................................................................................97

4-3 Reaction times for control and TBI participants on the guessing task ...........................98

4-4 Non-reward minus reward difference wave means ................................. ...............98

4-5 Peak-to-peak component amplitude and latency as a function of feedback condition......98









LIST OF FIGURES


Figure pe

2-1 Electrical geodesics sensor layout and international 10-20 equivalents for the 64-
channel geodesic sensor net. ...................................................................... ...................45

2-2 Grand average event-related potential (ERP) waveforms depicting response-locked
correct- and error-related activity averaged across fronto-medial electrode locations
for the error-related negativity (ERN) and top view of the spline-interpolated voltage
distribution maps showing mean voltages for error-trial activity ................................46

2-3 Grand average ERP waveforms depicting response-locked correct- and error-related
activity averaged across centro-parietal electrode locations for the post-error
positivity (Pe) and top view of the spline-interpolated voltage distribution maps
showing mean voltages for error-trial activity........ ....... ..... ............... .............. 46

3-1 Mean reaction times as a function of group, congruency, and current/previous trial
ty p e ......... ..... .............. ...................................... ... .............................. 73

3-2 Mean error rates as a function of group, congruency, and current/previous trial type......73

3-3 Grand average ERP waveforms of stimulus-locked congruent and incongruent trials
averaged across fronto-medial electrode locations for the N450 and top view of the
spline-interpolated current source density maps.................................... ............... 74

3-4 Grand average ERP waveforms of stimulus-locked congruent and incongruent trials
averaged across posterior electrode locations for the conflict slow potential (conflict
SP) and top view of the spline-interpolated current source density maps ....................74

3-5 Grand average ERP waveforms of stimulus-locked waveforms for congruent and
incongruent waveforms as a function of previous trial congruency .............................75

3-6 Mean N450 amplitude as a function of group, congruency, and current/previous trial
ty p e .........................................................................7 6

3-7 Mean conflict SP amplitude as a function of group, congruency, and current/previous
trial type .........................................76

3-8 Scatter plot reflecting the relationship between self-awareness of deficits interview
total score for traumatic brain injury (TBI) participants and the parietal conflict SP
incongruent m inus congruent difference ........................................ ....................... 77

3-9 Scatter plot reflecting the relationship between frontal systems behavior scale
(FrSBe) other- minus self-rated total score for TBI participants and the parietal
conflict SP incongruent minus congruent difference...................................................... 77









4-1 Grand average ERP waveforms depicting feedback-locked reward and non-reward
activity as well as the non-reward minus reward difference wave at recording site
FC z for control and TB I participants............................................................................. 99

4-2 Grand average feedback-locked ERP waveforms showing reward and non-reward
activity as well as non-reward minus reward difference waves at recording site FCz
for the high frequency trials and low frequency trials. ............................................... 99

4-3 Spline-interpolated voltage maps of the non-reward minus reward difference wave
for control and TBI participants...................... ....... .............................. 100









Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

COGNITIVE CONTROL DISRUPTION IN TRAUMATIC BRAIN INJURY

By

Michael James Larson

August 2008

Chair: William M. Perlstein
Major: Psychology

Cognitive control comprises two essential interactive component processes: a regulative

component supporting the activation and implementation of control and an evaluative component

that monitors the need for regulative control and signals when adjustments in control are

necessary. Survivors of severe traumatic brain injury (TBI) experience cognitive control

impairments that frequently contribute to long-term disability, but the specific nature of these

impairments is poorly characterized. Moreover, research on TBI-related cognitive control

dysfunction has focused primarily on regulative control deficits. The current series of studies

utilized behavioral (i.e., response time [RT] and error rates) and electrophysiological (i.e., event-

related potentials [ERPs]) measures of cognitive control to test the hypotheses that: (1) survivors

of severe TBI exhibit impairments compared to demographically-matched healthy control

participants in the evaluative control functions of performance-monitoring, conflict detection,

feedback utilization, and signaling for increased implementation of regulative control; and (2)

both behavioral and electrophysiological manifestations of evaluative control impairment are

associated with impairments in deficit awareness. Relative to healthy control participants,

survivors of severe TBI showed attenuated neural reflections of both performance-monitoring

and feedback context utilization; however, groups did not differ on putative measures of the









evaluative control process of signaling for enhanced regulative control following conflict.

Neither behavioral nor electrophysiological manifestations of evaluative control were associated

with awareness of deficits in TBI survivors. Taken together, these findings suggest that survivors

of severe TBI are impaired in the evaluative control functions of performance monitoring and

feedback context utilization, but can still utilize conflict information to reactively adjust

performance to changing task demands. Future research based on these findings may allow us to

capitalize on the heterogeneity associated with TBI to identify clinically meaningful subtypes

and appropriately tailor rehabilitation efforts to specific cognitive control deficits.











CHAPTER 1
GENERAL INTRODUCTION

Traumatic brain injury (TBI) is one of the most common neurological disorders in the

United States. The estimated incidence rate is nearly 100 per 100,000 individuals, with

approximately 52,000 deaths annually (National Institute of Health, 1998). TBI occurs

approximately two times more often in males than females (Centers for Disease Control, 1999),

with direct medical costs and indirect costs (e.g., lost productivity) estimated to be approximately

$60 billion per year in the United States alone (Finkelstein et al., 2006). Mild injuries account for

approximately 80% of all cases of TBI, and may result in recovery of function without

intervention (Levin et al., 1987). In contrast, moderate-to-severe TBI tends to be associated with

worse outcomes and requires extensive and costly rehabilitation in order to maximize functional

recovery (Levin et al., 1990). The debilitating behavioral and cognitive consequences of TBI

often dramatically alter survivors' life-course due, in part, to disruption of the family, income

loss, and illness-related lifetime expenses (National Institute of Health, 1998). Given the high

prevalence, extensive disability, and expense associated with TBI, a comprehensive

understanding of the cognitive impairments, their potential common neural bases, and their

relationship to outcome is critical to developing effective rehabilitation strategies and monitoring

rehabilitation effects on brain function.

Cognitive Control and Traumatic Brain Injury

Although the pattern of impairment following TBI varies across individuals and severity of

injury, the preponderance of current evidence suggests that TBI is associated with severity-

dependent deficits in cognitive control-that is, "in the ability to orchestrate thought and action in

accord with internal goals" (Miller & Cohen, 2001, p. 167). Such deficits appear to exist either in









addition or in contrast to more generalized cognitive impairment (Larson et al., 2006a; Levin et

al., 1990; Levine et al., 2002; Perlstein et al., 2004, 2006; Seignourel et al., 2005). Little

systematic research has explicitly examined cognitive control impairment in TBI. Additionally,

until only recently, examination of cognitive functioning in TBI has employed tasks that

primarily examine dorsolateral prefrontal cortex (dlPFC)-mediated cognitive control functions.

The use of such tasks has been a critical step in identifying some of the specific cognitive

processes impaired in patients with TBI and the brain regions most vulnerable to disruption in

such patients; however, other aspects of cognitive control dysfunction in TBI have received little

attention despite their potential importance in adaptation to, and recovery from, injury.

A basic understanding of the construct of cognitive control is requisite to full appreciation

of cognitive control dysfunction in TBI. Two broad sets of dissociable processes are considered

central to cognitive control: regulative and evaluative control processes (Botvinick et al., 2001;

Kerns et al., 2004; Miller, 2000; Miller & Cohen, 2001). Regulative control processes are those

involved in the top-down control of cognition and include such functions as representing and

maintaining goals (i.e., context maintenance) and implementing control (i.e., allocating limited

attentional resources). These functions rely on the integrity of the dlPFC (Cohen et al., 2000) and

are most critical when faced with competing response options (e.g., the representations of both

correct and incorrect response options). A second set of processes essential for cognitive control

are evaluative in nature and involve the on-line assessment of performance (e.g., detection of

processing conflicts, error-monitoring). These evaluative functions are critical for flexible

adjustments of top-down control and adaptation to a constantly changing environment. The

monitoring of performance for errors and detection of conflict can subsequently act as a signal to

allocate the increased attentional control necessary to overcome errors/conflict and successfully









perform goal-directed behaviors (Botvinick et al., 2001; van Veen & Carter, 2002a). A

convergence of human and animal research implicates the medial frontal cortex, specifically the

anterior cingulate cortex (ACC), as essential to these evaluative control processes (Botvinick et

al., 2001; Rushworth et al., 2004; van Veen & Carter, 2002a,b). In sum, cognitive control is a

dynamic process implemented in a distributed network in the brain that involves closely

interacting, but dissociable components. Anterior cingulate-mediated evaluative control

processes indicate when control needs to be more strongly engaged and signal to the dlPFC for

increased attention allocation and top down support of task appropriate behaviors (Kerns et al.,

2004; MacDonald et al., 2000).

Much of the theoretical and empirical work related to cognitive control functioning has

focused on impaired regulative processes and their association with impairments in the dlPFC

and related circuitry. This is appropriate, as the frontal lobes and temporal poles are

preferentially susceptible to damage following TBI (Bigler, 1999), giving rise to the

preponderance of cognitive control dysfunction seen due to focal frontal/prefrontal cortical

contusions (Adams et al., 1980) or diffuse white matter injury that disrupts dopaminegic input to

the prefrontal cortex (e.g., Adams, 1984; Adams et al., 1982). Several recent functional

neuroimaging studies demonstrate altered dlPFC activity in patients with mild (McAllister et al.,

1999, 2001) and moderate-to-severe TBI (Cazalis et al., 2006; Christodoulou et al., 2001;

Newsome et al., 2007; Perlstein et al., 2004; Scheibel et al., 2003) while they performed working

memory tasks heavily dependent upon regulative control functions. Experimental cognitive

neuroscience tasks designed to precisely isolate specific dlPFC-related regulative control

processes are also reliably identifying TBI-related dysfunction (Larson et al., 2006a; Levine et

al., 2002; Perlstein et al., 2004, 2006; Seignourel et al., 2005). Specifically, performance deficits









in TBI patients relative to controls have been identified on the AX-CPT task (Larson et al.,

2006a), the n-back task (Perlstein et al., 2004), the cued-Stroop paradigm (Seignourel et al.,

2005; Perlstein et al., 2006), and dual-task paradigms (Leclercq et al., 2000; McDowell et al.,

1997), suggesting the presence of cognitive control deficits involving processes such as working

memory, context maintenance, response inhibition, performance adjustment, and the ability to

coordinate simultaneous performance of multiple task demands. In addition, studies employing

traditional neuropsychological assessment methods have reliably identified TBI-related

performance difficulties on traditional measures of dlPFC function, including the Stroop Color-

Word Task (Bate et al., 2001; Ponsford & Kinsella, 1992; Potter et al., 2002), Trail Making Test

Part B (Rios et al., 2004), Wisconsin Card Sorting Test (Leon-Carrion et al., 1998; Rios et al.,

2004), and the Paced Auditory Serial Addition Test (Gronwall & Wrightson, 1981; Levander &

Sonesson, 1998; Ponsford & Kinsella, 1992). Little attention has been paid to impaired

evaluative component processes in TBI. We believe that many cognitive deficits in TBI are

related to dysfunction in the evaluative process of monitoring and signaling of errors/conflict,

and that its remediation is important to the development of future rehabilitation strategies.

Cognitive control deficits in TBI are most debilitating outside the laboratory setting

where complex demands are ubiquitous and fluid performance adjustments critical. For example,

many TBI survivors do well on automatic, well-rehearsed tasks yet experience tremendous

difficulty when required to use flexible, novel approaches to solve new and complex problems

(Levine et al., 2000). Insufficiencies in these processes may serve as a foundation for some of the

most debilitating functional deficits following TBI, such as difficulty making decisions,

performing complex tasks, dual-tasking, and planning (Anderson et al., 2002; Bergquist &

Jacket, 1993; Levine et al., 2002; Stuss & Gow, 1992). Based on these observations, one would









expect cognitive control deficits as measured in the laboratory to correlate with functional

impairment in TBI, particularly in domains of functioning requiring awareness of performance

and adaptive thinking (see Perlstein et al., 2004, 2006 for examples). Thus, deficits in the

monitoring and evaluation of conflict should be manifest outside of the laboratory as difficulties

recognizing discrepancies in actions and subsequent failures to adapt actions appropriately to the

situation (i.e., impaired deficit and performance awareness).

Awareness of Deficits in TBI

Several studies of moderate-to-severe TBI survivors document lack of awareness of

cognitive deficits (Damasio & Anderson, 1993; Sherer et al., 1998; Toglia & Kirk, 2000), lack of

insight into impaired interpersonal skills (Bergquist & Jacket, 1993), and impaired self-

monitoring of behavior (Stuss, 1991). Research suggests that up to 45% of individuals with

moderate-to-severe TBI demonstrate reduced or complete lack of awareness of their deficits (see

Flashman & McAllister, 2002). Survivors of TBI who are unaware of their deficits may display a

lack of motivation to change (Sherer et al., 1998), limited self-regulatory behaviors (Fleming &

Strong, 1995), and decreased compliance in the rehabilitation setting (Allen & Ruff, 1990).

Deficits in the detection of difficulties may lead to poor performance and decreased recovery of

function in the rehabilitation setting. Awareness of deficit is a major factor in predicting overall

rehabilitation outcomes, with decreased awareness of deficits associated with worse

rehabilitation outcomes (Sherer et al., 1998) and decreased likelihood of regaining employment

(Hart et al., 2005). Some researchers hypothesize poor functional outcomes associated with

reduced awareness of deficits are associated with a lack of ability to detect and acknowledge

problems in performance and make the necessary adjustments to perform activities accurately

(Dirette, 2002).









Awareness of deficits is a dynamic, rather than static, component of cognitive function

following TBI (Noe et al., 2005; Toglia & Kirk, 2000). Thus, different variables may contribute

to a patient's awareness of deficits throughout the recovery process. Length of posttraumatic

amnesia (PTA) is the only injury severity index that has been reliably associated with severity of

deficits in awareness (Prigatano et al., 1998; Trudel et al., 1998), although a recent study

indicates that severity of injury is associated with impairments in deficit recognition (Sherer et

al., 2005). This same study (Sherer et al., 2005) examined lesion location and severity in

association with awareness of deficits. Findings indicate the number of brain lesions was

predictive of degree of impaired awareness of deficits; however, right hemisphere contusion or

frontal lobe contusion volumes were not predictive of degree of impaired deficit awareness.

Emotional status (i.e., presence of mood or anxiety disorder) is also associated with deficit

awareness, as several studies indicate emotional status is inversely correlated with measures of

deficit awareness (Ownsworth & Oei, 1998). For example, Ownsworth and Oei (1998), in a

review of the TBI literature, reported improved awareness of deficits is one of the strongest

predictors of depression post-TBI and that Axis I psychopathology is increased in association

with improvements in awareness. Furthermore, recent studies indicate increased awareness of

deficits is associated with improved neuropsychological test performance-particularly on

measures of executive functioning and both verbal and spatial memory, higher levels of

functional independence, and decreased psychopathological symptoms (Noe et al., 2005;

Ownsworth et al., 2000, 2002).

Awareness can be divided into two theoretical categories, metacognitive knowledge and

"on-line abilities" (Toglia & Kirk, 2000). Metacognitive knowledge refers to knowledge about

one's own abilities, and implies knowledge from the present and past, as well as anticipating and









planning for the future. On-line awareness is ongoing monitoring of actual task performance and

implies identification of inappropriate task completion and subsequent adjustments in

performance to complete the task successfully. In other words, metacognitive knowledge is what

an individual brings to the task in terms of cognitive abilities and awareness of one's functioning,

while monitoring reflects awareness of performance on a task and the ability to change strategies

and adjust performance according to previous experience (i.e., performance monitoring; Toglia

& Kirk, 2000). Both aspects of awareness are crucial to effective interactions with the

environment. Deficits in metacognitive knowledge can lead to inappropriate expectations and

goals, increasing the potential for let down and subsequent decreases in emotional functioning.

On-line monitoring of performance, on the other hand, is crucial to appropriate actions in the

work environment, where repeated errors can lead to poor performance and potential

termination, as well as impairments on everyday tasks that require active problem solving and

confrontation of novel situations.

Utilizing neurobiological indices of evaluative control (scalp-recorded event-related

potentials [ERPs]) and measures of symptom expression and deficit awareness, the studies

presented below provide insight into the relationships between evaluative control dysfunction,

brain activity reflecting this dysfunction, and measures of deficit awareness. The specific aims of

these studies were to, first, test the hypothesis that survivors of severe TBI exhibit impairments

in behavioral and neurobiological manifestations of ACC-mediated evaluative control processes.

We specifically predicted survivors of severe TBI would show impairments in their ability to

detect errors and response conflict (i.e., when representations of more than one response are

simultaneously activated) and subsequently show decrements in their ability to adjust

performance to adapt to task demands. Since behavioral data alone do not address the potential









neural underpinnings of impaired performance, we employed high-density ERPs to test the

prediction that TBI survivors exhibit attenuated neural signals for measures of performance

monitoring, conflict monitoring, and subsequent control adjustment. Second, we compared

behavioral and neurobiological indices of evaluative control to measures of deficit awareness in

participants with TBI. We predicted cognitive control deficits as measured in the laboratory

would correlate with deficits in the monitoring and evaluation of performance and abilities (i.e.,

deficit awareness). Finally, we examined TBI-related changes in the evaluative control ability to

monitor and respond to feedback. We predicted survivors of severe TBI would exhibit deficits in

the evaluative control process of reward context monitoring and, subsequently, show decrements

in their ability to evaluate feedback and reward.











CHAPTER 2
AWARENESS OF DEFICITS, PERFORMANCE MONITORING, AND EVALUATIVE
CONTROL FOLLOWING SEVERE TRAUMATIC BRAIN INJURY

Individuals with severe traumatic brain injury (TBI) often demonstrate impairments in

performance monitoring-an evaluative control process that can be measured using the error-

related negativity (ERN) and post-error positivity (Pe). The ERN and Pe are event-related

potential (ERP) components generated following errors, with current theories suggesting the

ERN reflects automatic performance monitoring and the Pe reflects error processing and

awareness. To elucidate the electrophysiological mechanisms of performance monitoring deficits

following severe TBI, behavioral and ERP measurements were obtained while participants with

severe TBI and neurologically-healthy comparison participants performed a modified color-

naming version of the Stroop task. Behaviorally, both groups demonstrated robust RT and error

rate interference; no significant between-groups differences were noted. ERP results indicate

ERN amplitude was attenuated in participants with TBI, while the pattern of Pe amplitude did

not clearly differentiate groups. No meaningful relationships between ERN or Pe component

amplitude and measures of deficit awareness were present. Results suggest the ERN as a

potential electrophysiological marker of evaluative control/performance monitoring impairment

following TBI.

Introduction

Survivors of traumatic brain injury (TBI) frequently exhibit severity-dependent

impairments in a number of cognitive domains, including those that compromise the accuracy of

action and performance monitoring. Impairments of this type belong to a broader constellation of

deficits in the evaluative component of cognitive control (Botvinick et al., 2001; Braver et al.,

1999). Evaluative component processes include monitoring for the presence of response conflict









(simultaneously activated competing responses), monitoring performance for errors, and

signaling the need to implement or adjust top-down control processes. These evaluative

functions are critical for flexible adjustments of top-down control needed for adaptation to

performance demands (e.g., correcting an error). The ACC plays a key role in the evaluative

component of cognitive control (Gehring & Fencsik, 2001; Kerns et al., 2004; MacDonald et al.,

2000; Miltner et al., 2003; van Veen & Carter, 2002a, 2002b).

Dysfunction of ACC-mediated evaluative control processes has direct implications for

survivors of brain injuries. For example, animal research demonstrates ACC lesions alter the

normal pattern of corrective behavior following errors, such that consecutive errors without

appropriate correction are more common (Dias & Aggleton, 2000; Rushworth et al., 2003;

Walton et al., 2003). Similar evidence comes from a human patient with a rare focal lesion of the

rostral-to-middorsal ACC who was less likely than healthy controls to correct mistakes (Swick &

Turken, 2002). In participants with TBI, where axonal shearing may be prominent in medial

frontal regions, little research has examined the neural instantiation of evaluative control

functions. One PET study suggested abnormalities of ACC glucose metabolism at rest in

participants with TBI that correlated with subsequent neuropsychological performance (Fontaine

et al., 1996), an fMRI study using the Stroop task found a relative decrease in ACC activity in

participants with TBI compared with controls (Soeda et al., 2005), an fMRI study reported

impaired ACC activity in TBI survivors with problem solving deficits (Cazalis et al., 2006), and

recent studies from our lab observed ACC dysfunction in survivors of severe TBI during

performance of a task requiring working memory (Perlstein et al., 2004), and a diminished

electrophysiological reflection of evaluative control, presumably mediated by the ACC (i.e.,

N450 component of the scalp-recorded event-related potential [ERP]), in a single-trial version of









the Stroop task; Perlstein et al., 2006). A growing consensus from these studies is that ACC-

mediated changes following TBI are the result of diffuse axonal damage that disturbs fronto-

cortical and subcortical networks leading to subsequent evaluative control impairment.

The physiological and cognitive bases of evaluative control have been the subjects of many

recent investigations. One putative reflection of the evaluative process of performance

monitoring is an electrophysiological signature in the scalp recorded ERP known as the error-

related negativity (ERN). The ERN is a fronto-medial maximal response-locked potential

peaking within 100ms after the commission of an error (Falkenstein et al., 1991). The precise

cognitive mechanisms generating the ERN are under active debate (Holroyd & Coles, 2002;

Yeung & Cohen, 2006), but have been attributed to detection of response conflict (Carter et al.,

1998), detection of errors (i.e., mismatch between an intended and produced response;

Falkenstein et al., 1991; Gehring et al., 1993), or an emotional response to errors (Larson et al.,

2006b; Vidal et al., 2000). Source localization ERP as well as fMRI studies consistently

implicate a region in the dorsal ACC as the primary neural generator of the ERN (van Veen &

Carter, 2002a).

Although the ERN has received considerable attention in electrophysiological

investigations of performance monitoring, researchers also examined a positive deflection

occurring between 100 and 400ms following the ERN known as the post-error positivity (Pe).

The functional significance of the Pe remains controversial (Overbeek et al., 2005); however, the

Pe can be differentiated from the P300 (Falkenstein et al., 2000) and may be associated with

conscious error recognition, as it is diminished when subjects are unaware of performance errors

(Nieuwenhuis et al., 2001). Moreover, post-error RT slowing occurs only on trials that exhibit an









observable Pe (Mathalon et al., 2002), and Pe amplitude varies in relation to the degree of post-

error slowing and autonomic nervous system activity (Hajcak et al., 2003a).

Awareness of Deficits, Performance Monitoring, and TBI

Several studies of TBI survivors document lack of awareness of cognitive and physical

deficits (Damasio & Anderson, 1993; Sherer et al., 1998; Sherer et al., 2005; Toglia & Kirk,

2000). One important aspect of awareness abilities is that of monitoring performance and

implementing strategic adjustments when current performance is inadequate. Stemmer et al.,

(2004) examined overt behavioral signs of error responses (e.g., exclamations, swearing,

grimaces) during a flanker task and found that three of five stroke patients who experienced

anterior communicating artery (ACA) aneurysms and subsequent lesions to the medial PFC,

including the ACC, demonstrated poor ability to monitor performance. This study utilized ERPs

to examine error-related neural activity; findings indicate decreased error-related neural activity

in the individuals with lesions to the medial PFC. Of note, some patients were aware of errors

but did not produce a discernable Ne/ERN.

Another study examined error awareness in everyday situations, such as wrapping a gift or

packing a schoolbag. TBI patients showed less awareness and corrected significantly fewer

errors than control participants (Hart et al., 1998). O'Keeffe and colleagues (2004) utilized

measures of electrodermal activity to examine autonomic responses to errors in TBI participants.

TBI participants detected significantly fewer errors on the task than matched-control

counterparts. In addition, electrodermal activity following errors was decreased in the TBI

participants relative to controls, with error detection rates and electrodermal activity being

significantly correlated. Findings indicate TBI participants exhibit impairments in the evaluative

process of conflict detection and processing, leading to impaired performance of error-related

conflicting information and poor adjustments in performance (O'Keeffe et al., 2004). No studies









to date have examined the electrophysiological instantiations of performance monitoring deficits

in survivors of severe TBI or the relationship of evaluative control dysfunction with deficit

awareness in these individuals. Given the important role that ACC-mediated conflict-

detection/performance monitoring processes appear to play in signaling for the recruitment of

regulative control mechanisms and the prevalence of deficits in awareness, it is important to

characterize the functioning of such a process in survivors of TBI.

Current Study

The primary aims of the current study were to extend previous findings of impaired

performance monitoring in survivors of severe TBI and determine if electrophysiological indices

of evaluative control-the ERN and Pe components of the scalp-recorded ERP-are attenuated

following severe TBI and if these ERP components are related to awareness of deficit. We

predicted that TBI participants would show smaller-amplitude electrophysiological activity

(ERN) to error, relative to correct trials, compared to neurologically healthy controls, and that

ERN amplitude would correlate with deficit awareness, such that larger ERN is associated with

increased awareness of deficit. Additionally, we tested the hypothesis that the Pe is related to

awareness of deficit, as previous studies of the Pe have shown a specific relationship between Pe

amplitude and awareness of performance errors (Nieuwenhuis et al., 2001).

Methods

Participants with severe TBI were recruited from two Northern Florida trauma and

rehabilitation hospitals; control participants were recruited via flyer and advertisement from the

local community. Study enrollment initially included 21 participants with severe TBI and 21

healthy control participants. ERP data for one participant with TBI were lost due to equipment

malfunction and one TBI participant performed the task incorrectly (i.e., responded to the word

rather than the color for every trial); therefore, final analyses included 19 participants with severe









TBI and 21 healthy control participants. All participants provided written informed consent

according to procedures established by the University of Florida Health Science Center

Institutional Review Board and were compensated for their participation.

TBI severity was determined from medical record review of lowest post-resuscitation

Glasgow Coma Scale (GCS) score (Teasdale & Jennett, 1974), with severe TBI defined as a

GCS score < 9. Neurological indices, including neuroradiological findings taken from acute

computerized tomography (CT) scans, duration of loss of consciousness (LOC), and duration of

post-traumatic amnesia (PTA), were also acquired from medical record review or, when LOC

and PTA information were not available in medical records, from structured participant and

significant other interview (King et al., 1997; McMillan et al., 1996). LOC and PTA data

confirmed all TBI participants met criteria for severe TBI as traditionally defined by LOC > 6

hours and/or PTA > 7 days (Bigler, 1990; Bond, 1986; Lezak et al., 2004).

All participants were screened for major psychiatric disorder using the Mental Health

Screening Form-Ill (MHSF-III; Carroll & McGinley, 2000, 2001). The MHSF-III provides

excellent inter-rater reliability (> .95), good internal consistency (Cronbach's a > .83), and good

construct validity (87% rate of agreement between independently assigned mental health

diagnoses and endorsed items on the MHSF-III; Carroll & McGinley, 2001). In addition, the

MHSF-III is useful as a screening instrument because it is quite brief, consisting of 18 questions,

and can be administered in approximately 15 minutes.

Potential participants were excluded from the study if they endorsed a history of psychotic

or bipolar disorder, learning disability, alcohol or substance abuse, other acquired brain disorders

(e.g., epilepsy, stroke), inpatient psychiatric treatment predating brain injury, clinically-

significant depression or anxiety currently or within two years prior to injury, current anti-









epileptic medication use, or color-blindness as measured by the Ishihara pseudo-isochromatic

color plates (Clark, 1924). Participants with language comprehension deficits or uncorrected

visual impairments were also excluded.

Demographic characteristics and neuropsychological test summary data for control and

TBI study participants are provided in Table 2-1. Injury characteristics (etiology, GCS, LOC,

PTA, time since injury) and neuroradiological findings for the participants with TBI are

presented in Table 2-2. Survivors of severe TBI were at least four months post-injury, with the

exception of one TBI survivor (two months post-injury) who was functioning well and desired to

complete the study early before returning to employment responsibilities. No participants were

engaged in legal action at the time of the study. Participant groups were comparable in age and

education (see Table 2-1); groups did not significantly differ in gender distribution X2(1)=2.16,

>. 14 (TBI: 15 male/4 female; Control: 12 male/9 female). Since previous studies demonstrate

differences in ERN amplitude as a function of depressive or anxious symptoms (Hajcak et al.,

2003b; Ruchsow et al., 2004; Ruchsow et al., 2006), TBI and control participants were

administered the Beck Depression Inventory-2nd Edition (BDI-II; Beck, 1996), a modified

version of the Apathy Evaluation Scale (Marin, 1991; Marin et al., 1991; Starkstein et al., 1992),

and the State-Trait Anxiety Inventory (STAI; Speilberger et al., 1983). Compared to controls,

participants with TBI endorsed significantly more depressive symptoms; however, no individual

scores met common clinical cut-offs for moderate depression (BDI-II > 21) and mean scores for

both groups were within normal limits not meeting criteria for minimal depression (BDI-II >

13; see Beck, 1996). Groups did not differ on their report of apathy symptoms, but participants

with TBI endorsed higher levels of state and trait anxiety symptoms.









Assessment of TBI Symptoms and Deficit Awareness

In an effort to characterize the cognitive functioning of participants with TBI, a brief

battery of neuropsychological tests was administered to all participants. Measures administered

included the Digit Span forward and backward subtests from the Weschler Adult Intelligence

Test-Third Edition (WAIS-III; Wechsler, 1997), Trail Making Test Parts A and B (Reitan,

1958), the Controlled Oral Word Association Test [COWAT] and Category Fluency (Benton &

Hamsher, 1976), the Hopkins Verbal Learning Test--Revised (HVLT-R; Brandt & Benedict,

2001) and the Wechsler Memory Scale-Revised (WMS-R) Logical Memory I and II subtests

(Wechsler, 1987). Order of neuropsychological task presentation was counterbalanced across

participants, with the exception of the WMS-R that was presented first and last to allow adequate

time for the long-recall delay (see below). Brief summaries of each measure utilized are

presented below.

Digit span forward and backward. In the digit span forward test of the WAIS-III,

increasingly longer strings of numbers are recalled (1-9 letters). In the backward version,

subjects repeat the numbers in reverse order. Span length is defined as the numbers of digits

recalled correctly before two strings of the same length were failed

Reliability estimates of the Digit Span range from 0.84 to 0.93 and its correlation with the

working memory index of the WAIS-III was estimated at 0.83 in a normative sample (Wechsler,

1997).

Trail Making Test parts A and B. Trail Making Test parts A and B are well-documented

measures of visual scanning, processing speed, and task switching (Lezak et al., 2004). The Trail

Making Test consists of two parts. In Part A, participants connect consecutively numbered

circles, while in Part B, participants connect consecutively numbered and lettered circles that

alternate between the two sequences. Psychometric studies indicate reliability coefficients above









.80 (Spreen & Strauss, 1991), and several studies indicate that the two Trail Making tests are

sensitive to the global effects of brain injury (Botwinick et al., 1988; Buchanan et al., 1994);

Trail Making Test Part B is reported to be specifically sensitive to prefrontal dysfunction because

of the requirement to shift sets (Butters et al., 1994).

Controlled Oral Word Association Test (COWAT) and Category Fluency (Animals).

In the COWAT, participants are asked to produce as many words as possible that begin with the

letters F,A, and S in one minute. Participants are instructed to avoid using proper names and

words that are only changed based on different suffixes (e.g., eat, eating). Similarly, for semantic

or category fluency participants are asked to name as many animals as possible in a one minute

time period. Thus, fluency measures require efficient organization of verbal retrieval and recall

as well as self-monitoring aspects of cognition, self-initiation, and inhibition of inappropriate

responses (Henry & Crawford, 2004). A recent meta-analysis indicates fluency measures are

more sensitive to the presence of severe TBI than the Wisconsin Card Sorting task (Henry &

Crawford, 2004).

WMS-R Logical Memory I and II. Logical memory is a test of paragraph or passage

recall that consists of two stories, each containing 25 items of information. For Logical Memory

I participants are asked to immediately recall the passages after each reading to assess verbal

memory, while Logical Memory II asks for a recall of the passages approximately 30-minutes

later. Reliability estimates are .74 for Logical Memory I and .75 for Logical Memory II

(Wechsler, 1987).

Hopkins Verbal Learning Test-Revised. The HVLT-R is a measure of list-learning

memory that consists of one 12-item word list that can be semantically grouped into categories.

The list is presented such that words from the same category do not occur in sequence and









participants are not informed of the semantic structure. Three initial learning trials are presented,

with a total learning score calculated by adding trials 1 through 3. After a 20-minute delay, long-

delay free recall and a forced choice recognition trial are administered. The HVLT-R has modest

reliability estimates across short- and long-delay recalls (> .49; Woods et al., 2005).

As presented in Table 2-1, and consistent with typical impairments seen after severe TBI,

participants with severe TBI performed significantly worse than controls on tests broadly

assessing attention (Digit Span Forward from the WAIS-III), processing speed (Trail Making

Test Part A), verbal fluency (COWAT and category fluency), executive functioning (Trail

Making Test Part B; Digit Span Backward from the WAIS-III), and delayed verbal memory

(HVLT-R long delay and WMS-R Logical Memory II). In contrast, participants with TBI did not

differ from controls on the initial encoding/immediate recall of verbal memory information

(HVLT-R immediate recall/WMS-R Logical Memory I).

Two independent measures were used to assess self- and significant other-reported clinical

symptomatology and quantify level of deficit awareness: 1) the Frontal Systems Behavior Scale

(FrSBe; Grace & Malloy, 2001); and, 2) the Self-awareness of Deficits Interview (SADI;

Fleming et al., 1996). The FrSBe is a 46-item behavior rating scale originally designed to

measure behavioral change associated with frontal lobe injury. Each item is rated on a one to five

point Likert-type scale, with one indicating "almost never" and five "almost always." Thus,

higher scores indicate more TBI-related symptoms. The FrSBe gathers information regarding

pre- and post-injury behaviors from the participant (self-report) and a significant other and

includes an overall composite score and three subscales that assess apathy, disinhibition, and

executive function and shows adequate reliability (internal consistency 0.96; split half 0.93) and

validity (Grace & Malloy, 2001). Significant others who completed ratings in the current study









were the primary caregivers of the participants with TBI and included eight spouse/fiancee,

seven parents, two siblings, one grandparent, and one aunt. Awareness of deficits was initially

calculated by computing a concordance between self- and other-reported FrSBe responses and

taking the absolute value of the difference score from self- and other-ratings. To account for

participants who were possibly hypervigilant to their deficits (i.e., greater self- than other-report

of deficits), subsequent analyses utilized only those participants with positive concordance scores

(i.e., greater other- than self-reported deficits). The concordance score method is commonly

utilized in the self-awareness literature and is considered a sensitive measurement of self-

awareness following TBI (see Hart et al., 2003 for review).

The SADI is a nine-question structured interview given to participants with TBI that

facilitates questioning in three areas: 1) self-awareness of deficit, 2) self-awareness of functional

implications of deficit, and 3) ability to set realistic goals. Scores for these areas are combined to

produce a composite self-awareness score. The SADI exhibits high inter-rater reliability (>.82;

Fleming et al., 1996), test-retest reliability (0.94; Simmond & Fleming, 2003), can accurately

discriminate TBI participants based on severity of injury (Bogod et al., 2003), and is highly

correlated with measures of executive function, including Go-No-Go and Stroop Color-Word

task errors (Bogod et al., 2003).

Experimental Task

Participants performed a modified color-naming version of the single-trial Stroop task. In

this task, participants are presented with one of three words (RED, GREEN, BLUE) printed in

one of the same three colors. Congruent trials comprised words presented in their same color of

ink (e.g., the word BLUE printed in blue ink); incongruent trials comprised color-words printed

in a different color of ink (e.g., the word BLUE printed in red ink). Participants were instructed

to respond as quickly and accurately as possible to the color of the word (while ignoring the









word itself) with a button press to one of three color-coded response keys using the index,

middle, and ring fingers of their right hand. Color-to-key mapping was practiced prior to task

performance using 40 presentations of each color-key combination. Stroop trials were three

seconds in duration and consisted of a Stroop color-word presented for 1.5s followed by a 1.5s-

duration fixation cross to allow electrophysiological activity to return to baseline. Six blocks of

100 trials, for a total of 600 trials and approximately 30 minutes in EEG testing were presented.

To increase the potency of the conflict stimulus, 70% of trials were congruent (approximately

420 trials) and 30% were incongruent (approximately 180 trials).

Electrophysiological Data Recording, Reduction, and Measurement

Electroencephalogram (EEG) data were recorded from 64 scalp sites using a geodesic

sensor net and Electrical Geodesics, Inc., (EGI; Eugene, Oregon) amplifier system (20K gain,

nominal bandpass=. 10-100Hz). Electrode placements enabled recording vertical and horizontal

eye movements reflecting electro-oculographic (EOG) activity. Data from the EEG were initially

referenced to Cz and digitized continuously at 250Hz with a 16-bit analog-to-digital converter. A

right posterior electrode approximately two inches behind the right mastoid served as common

ground. Electrode impedance was maintained below 50kQ. Electroencephalographic data were

segmented off-line and single trial epochs were rejected if voltages exceeded 100lV, transitional

(sample-to-sample) thresholds were greater than 100lV, or eye-channel amplitudes were above

70 V. Data were digitally re-referenced to an average reference (Bertrand et al., 1985) in order

to yield a reference-free representation of electrophysiological activity and to reconstruct the

EEG at the Cz reference, then digitally low-pass filtered at 15Hz.

Individual-subject response-locked averages were derived separately for correct and

incorrect trials, collapsed across congruency to afford adequate signal-to-noise ratio, spanning









200ms prior to and 500ms following response and baseline corrected using the 200ms pre-

response window. ERP trials containing errors of omission were excluded from averages.

Electrode locations utilized were based on previous findings that the ERN and Pe are relatively

focal over fronto-medial locations and centro-parietal areas, respectively (Falkenstein et al.,

2000; Gehring et al., 1993), as well as the scalp-distribution maps of the present data. To ensure

accurate characterization of ERN amplitude and prevent spurious findings as a result of potential

group-wise latency differences, ERN amplitudes as well as the corresponding correct-trial

amplitudes were extracted as the average of 15ms pre- to 15ms post-peak negative amplitude

between Oms and 100ms and averaged across four fronto-central electrode sites-4 (FCz), 65

(Cz), 5, and 55 (both sites anterior and slightly lateral to Cz-see Figure 2-1). Latency

measurements for the ERN component were indexed as the time of the peak negative-going

amplitude averaged across the four fronto-central electrode locations. Given previous findings

that the Pe is found at centroparietal electrode locations and is less punctate and more tonic than

the ERN (see Overbeek et al., 2005), Pe amplitude was measured as the averaged activity from

200ms 400ms of five centro-parietal electrode sites (65 [Cz], 18, 43, 30, and 34 [Pz];

Figure 2-1).

Data Analysis

Median correct-trial RT (Ratcliff, 1993), arcsine transformed error rates (Neter et al.,

1985), and ERP component amplitude and latency data were analyzed using separate repeated-

measures analyses of variance (ANOVAs). In order to correct for possible violations of

sphericity in the data, the Huynh-Feldt epsilon adjustment was applied for ANOVAs with more

than two levels of a within-subject factor and partial-eta2 (n2) reported as a measure of effect

size. ANOVAs for RTs and error rates included the factors group (TBI, control) and congruency









(congruent, incongruent), while ANOVAs for error-related ERP activity included the factors

group and accuracy (correct, incorrect trial amplitudes). Tests of between-group simple effects

were used to decompose interactions, while planned comparisons were used to examine the

accuracy factor within each group. Cohen's-d effect sizes (Cohen, 1988) were calculated for

condition-related effects. Pearson-product-moment correlations (one-tailed) examined

relationships between task performance and the difference between correct- and error-trial ERP

amplitudes (e.g., error-trial Pe amplitude correct trial Pe amplitude) with measures of deficit

awareness (SADI and FrSBe concordance score) in TBI participants. In an effort to control for

TBI participant who may have been hypervigilant to deficits, we also recomputed the

correlations including only those participants with only positive, rather than absolute value,

FrSBe concordance scores (i.e., higher significant other than TBI survivor scores).

Results

Behavioral Data

Stroop task behavioral performance. Overall RTs and error rates for the Stroop task

(Table 2-3) were not significantly correlated in control participants, r(20)=-0.17, p>.47, but were

significantly positively correlated in participants with TBI, r(18)=.47, p<.04. Results suggest

speed/accuracy trade-off did not influence control or TBI participants, as a positive correlation

indicates longer RTs were associated with increased error rates, opposite the direction suggestive

of a speed/accuracy trade-off.

Error rates. Control and TBI participant groups did not differ on total number of raw

errors, t(38)=1.54, p>.13, d=.49; participants with TBI averaged 48.79+74.75 errors, while

controls averaged 23.10+16.53 errors. Similarly, groups did not reliably differ on the number of









omission errors, t(38)=1.13, p>.27, d=.36. Participants with TBI committed an average of

13.5225.21 omission errors, while control participants averaged 6.4013.38 omission errors.

A Group x Congruency ANOVA on arcsine-transformed error rates yielded only a

significant main effect of congruency, F(1,38)=83.68, 2<.001, !1=.69, reflecting significant error

rate interference, with both groups committing more errors to the incongruent than congruent

condition, as revealed by planned contrasts (TBI: t(18)=6.37, P<.001, d=.58; controls:

t(20)=6.57, p<.001, d=1.34). Neither the main effect of group, F(1,38)=2.21, p>.15, 2 =.06, nor

the Group x Congruency interaction, F(1,38)=1.47, 2>.23, 12 =.04, were significant.

Response times. A Group x Congruency ANOVA on RTs revealed the expected

generalized slowing in participants with TBI, as reflected in a significant main effect of Group,

F(1,38)= 1.75, 2<.001, 2 =.24. Paralleling the error rate data, a main effect of congruency

reflected the anticipated RT interference, F(1,38)=73.19, 2<.001, 1 =.66, with both groups

showing longer RTs to the incongruent than congruent condition (TBI: t(18)=4.97, P<.001, d=

.97; controls: t(20)=9.43, 2<.001, d=1.04). The Group x Congruency interaction was not

significant, F(1,38)=0.84, 2>.37, 2 =.02, indicating the two groups showed equivalent levels of

RT interference.

ERP Data: Response-related Activity

We first examined the number of trials retained for each condition to test for between-

groups differences in signal-to-noise ratio (SNR). Controls and survivors of severe TBI did not

differ on number of trials retained for averaging in correct, t(38)=0.55, p>.59, d=.17, or error

conditions, t(38)=-1.24, p>.22, d=.39. Response-locked correct-trial waveforms contained an

average ( SD) of 401.1132.9 trials for participants with TBI and 422.5+116.1 trials for

controls, while response-locked error waveforms contained an average of 23.1+33.96 trials for









participants with TBI and 13.7+7.9 trials for controls. Response-locked grand average ERP

waveforms and spline-interpolated voltage maps for correct and error response-locked trials

reflecting the fronto-medial ERN are shown in Figure 2-2, while those for the centro-parietal Pe

are shown in Figure 2-3. Mean (+ SD) component amplitude data are presented in Table 2-4.

ERN. As anticipated, response-locked ERPs showed an early negative deflection that was

larger in amplitude to error than correct trials in both groups, as confirmed by a Group x

Accuracy ANOVA, which yielded a significant main effect of accuracy, F(1,38)=41.09, p<.001,

2 =.52, and significant correct- vs. error-trial planned contrasts in both the TBI, t(18)=2.62,

p<.02, d=.70, and control participants, t(20)=6.12, 1<.001, d=1.65. More importantly, a

significant Group x Accuracy interaction, F(1,38)=12.99, p<.001, =.26, reflected greater

amplitude differences between correct- and error-related negativities in control than participants

with TBI. Follow-up contrasts revealed the error-trial ERN was reliably larger in the control

participants than the survivors of severe TBI, t(38)=2.65, p<.01, d=.83. The ERP related to

correct responses (correct-response negativity; CRN) did not differ between groups, t(38)=1.69,

p>.10, d=.54, suggesting a degree of specificity in the error-related differences. Furthermore, the

Group x Accuracy interaction was found in the absence of an overall main effect of group on

ERP component amplitude, F(1,38)=2.58, p>. 12, 2 =.06.

Pe. The Group x Accuracy ANOVA on the centro-parietal Pe revealed a significant main

effect of accuracy, F(1,38)=45.12, p<.001, 12 =.54, reflecting a more positive-going Pe on error

than correct-trials in both the TBI, t(18)=4.84, p<.001, d=1.26, and control participants,

t(20)=4.91, p<.001, d=1.22; the Group x Accuracy interaction was not significant, F(1,38)=1.67,

p>.20, 2 =.04. Subsequent tests of simple effects indicated the Pe significantly differed between

groups on error, t(38)=1.97, p=.05, d=.61, but not correct trials, t(38)=.60, p>.55, d=. 18. These









results are difficult to interpret in the absence of a significant interaction effect and due to the

relatively small sample size. Similar to the ERN, the main effect of group on Pe component

amplitude was not significant, F(1,38)=2.52, p>.13, 2=.06.

Peak latencies. A Group x Accuracy ANOVA yielded no significant main effects or

interactions involving error-related component latencies (ps>.09).

Correlational Analyses

In addition to examining error-related ERP activity in TBI survivors, an important goal of

the current study was to determine if electrophysiological reflections of performance monitoring

correlate with measures of deficit awareness. Pe amplitude (difference between Pe on wrong and

correct trials) inversely correlated with deficit awareness as measured by the FrSBe concordance

score, r(17)=-.48, 2<.02; Pe amplitude did not significantly correlate with SADI score, r(18)=-

.04, p>.40. ERN amplitude (difference between error and correct-trial waveforms) did not

correlate with either FrSBe concordance score or SADI score, rs<.02, es>.47. No significant

correlations were noted for either the Pe or the ERN when only TBI survivors with positive

concordance scores (i.e., higher other- than self-report scores) were included, rs<.39, es>. 12, or

when only the amplitude of error-trial ERN and Pe waveforms were included, rs<.34, es>.09.

Discussion

Results of the current study were largely consistent with our primary prediction that

participants with TBI would show a reduced-amplitude ERN on error relative to correct trials--

reflective of an impaired neural mechanism of error detection or performance monitoring.

Notably, participants with TBI did, on average, demonstrate a clearly discernable ERN,

suggesting that, while error-related performance monitoring was impaired, it was not completely

absent. Additionally, the finding that the control and TBI groups did not significantly differ in

correct-trial ERP amplitudes or the overall magnitude of response-related ERP amplitudes









provides some evidence for specificity of the ERN reflection of performance monitoring deficits

and indicating the difference does not reflect a more generalized decrement of response-locked

ERP amplitudes in the TBI survivors.

We also observed a discernable positive-going deflection following the ERN in both TBI

and control participant groups. This more phasic component, routinely referred to as the Pe, is

thought to be closely related to automatic monitoring of response conflict and error processing

(van Veen & Carter, 2002a). Although both TBI and control participants showed a significant

difference in Pe amplitude between correct and error trials, there was not a significant Group x

Accuracy interaction. Thus, despite the significant difference between control and participants

with TBI on subsequent contrasts for error, but not correct trials, no firm conclusions can

currently be drawn about Pe amplitude in severe TBI, particularly in light of the small sample

size employed.

Correlations between two different measures of deficit awareness and the difference

between correct and error trial component amplitude for the ERN and Pe yielded a pattern that

initially appeared congruent with previous literature suggesting Pe amplitude is related to

awareness of errors (Nieuwenhuis et al., 2001). This was a single, one-tailed correlation that

included the absolute value of scores for both TBI survivors who were less aware of their deficits

(i.e., positive concordance score) and those that were hypervigilant to their deficits (i.e., negative

concordance score). It is possible that this single correlation is a chance finding given the number

of correlations and the small sample size. This, coupled with the lack of a relationship between

Pe amplitude and the SADI, casts significant doubt on the meaningfulness of the correlation and

no speculations about the relationship between Pe amplitude and deficit awareness are drawn









from the current results. Similarly, no relationship was found between measures of deficit

awareness and ERN amplitude.

Several explanations of the lack of relationship between ERN and Pe component

amplitudes and deficit awareness are possible. First, the exact mechanisms of the Pe and ERN

remain quite controversial (Holroyd & Coles, 2002; Overbeek et al., 2005; Yeung & Cohen,

2006). Previous studies suggesting Pe amplitude varies as a function of error-awareness

primarily utilized an anti-saccade task and "real-time" ratings of whether an error occurred

(Niewenhuis et al., 2001). The current study examined the more general construct of awareness

of deficits following brain injury, but did not explicitly examine "real-time" awareness of errors

during task performance. The Pe could be related to "real-time" awareness of errors and neither

the ERN nor Pe is sensitive to awareness of performance over an extended period of time (i.e.,

awareness of level of functioning).

A more likely explanation is the measurement of deficit awareness utilized in the current

study. Utilizing absolute values between the self- and other-ratings on the FrSBe did not take

into account TBI survivors who were hypervigilent to their deficits and, thus, scored higher than

the other-ratings. Taking this into account led to the exclusion of 7 TBI participants-leaving the

study underpowered to detect a relationship if it was present. Similarly, the use of the SADI was

not ideal in the present circumstances as it relies on a vast knowledge of the participants'

functioning (e.g., the knowledge of a rehabilitation specialist who works closely with the patient

on a regular basis) that the examiner did not have due to the single-visit, cross-sectional design

of the study. Future studies should employ a larger sample with a more valid measurement of

deficit awareness (e.g., the Awareness Questionnaire; Sherer et al., 1998) to reduce measurement

error and improve the chances of finding the relationship if present. Finally, it is also possible









that there is not a relationship between electrophysiological manifestations of evaluative

control/error-processing and deficit awareness; however, it is premature to draw any specific

conclusions from the current data.

Results of this study suggest important implications for clinical application and future

research. First, the pursuit of effective rehabilitation and compensatory strategies is dependent on

accurate cognitive assessment and detailed understanding of the mechanisms underlying TBI-

related impairment. The current study, reflecting the first examination of electrophysiological

"marker" of performance monitoring in TBI, suggests a possible experimental method and

electrophysiological marker for examining the behavioral and neurobiological changes in

performance monitoring abilities in response to rehabilitation. Second, results suggest a

continued need for emphasis on rehabilitation of performance monitoring deficits following TBI.

Few empirically supported treatments currently exist that target such deficits, though

investigators are currently working to validate potential treatments in this domain (see

Ownsworth et al., 2006). Finally, future studies should further address the potential link between

performance monitoring decrements and impairments in deficit awareness. For example,

O'Keeffe et al. (2004) found attenuated electrodermal response to errors following TBI as well

as a relationship between performance monitoring abilities (error awareness) and amplitude of

the error-related electrodermal response. Utilization of an electrophyiological marker, such as the

ERN, in studies of performance monitoring and deficit awareness may provide much needed

clarification on the neural mechanisms underlying impairments in deficit awareness.

Findings of the current study must be considered within the context of several potential

limitations and alternative explanations, in addition to the ERP-related factors mentioned above.

The task paradigm employed precluded our ability to unambiguously examine participants'









facility to make reactive strategic adjustments following the commission of errors, such as post-

error trial RT slowing, due to the probability distribution of congruent and incongruent trials

(i.e., the preponderance of participant commission errors occurred in the incongruent condition

and were followed by congruent trials due to the 70% congruent/30% incongruent proportion of

trials employed; thus, post-error slowing was not evaluated as participants traditionally respond

faster to congruent than incongruent trials). Post-error strategic adjustments, or the so-called

"Rabbitt effect" (Rabbitt, 1966, 1968), have often been taken to reflect participants' top-down

adjustments in performance strategy, perhaps reflecting the dynamic interplay between ACC-

mediated evaluative and dlPFC-mediated regulative processes (Botvinick et al., 2004; Kerns et

al., 2004). Nonetheless, our earlier behavioral study using a different task, demonstrated that

participants with TBI were impaired in post-error RT slowing relative to healthy participants

(Larson et al., 2006a). That is, relative to neurologically-normal comparison subjects, they

showed smaller magnitude post-error slowing, suggestive of reduced post-error strategic

adjustments in cognitive control.

Another potential limitation is that the current data indicate generalized slowing in

participants with TBI that was not present for control participants. The potential variability in

ERP component latency, often referred to as latency jitter, associated with variable response

times may serve to spuriously reduce component amplitudes. Previous research also indicates

individuals who respond more quickly at the expense of accuracy show smaller ERN amplitude

than those who attend more to accuracy than speed (Ruchsow et al., 2005); however, the

direction of the correlation between speed and accuracy in participants with TBI suggests those

who made more errors were taking longer to respond to stimuli. Finally, as a consequence of

their impairment, participants with TBI committed significantly more errors on the Stroop task









than the neurologically healthy control participants. Since the error-related ERP data were

dependent upon error rates, the TBI group contains nearly twice as many trials included in the

ERP averages than controls, increasing the signal-to-noise ratio in TBI participants and

potentially making the error-related ERPs in the TBI group more reliable than those for control

participants.

It should also be noted that, despite the higher state and trait anxiety levels in the

participants with TBI relative to controls, ERN amplitude was still reduced in the participants

with TBI. Previous studies demonstrate that anxiety enhances ERN (Hajcak et al., 2003b) and

higher anxiety in the TBI group would appear to work in opposition to our hypothesis of reduced

error processing in participants with TBI. That is, despite the higher anxiety scores in

participants with TBI, a Group x Accuracy interaction was, nonetheless, observed for the ERN.

Depression, on the other hand, is associated with decreased ERN amplitude (Ruchsow et al.,

2004). The finding of group differences in depression score may suggest that the level of

depression in participants with TBI influenced findings of reduced ERP amplitude; however,

depression scores for both groups were in the subclinical range and the lack of change in the

pattern of significance for the ERN and Pe components when depression and anxiety scores were

added as covariates indicates findings cannot be wholly accounted for by these variables.

The present findings implicate an impaired performance monitoring mechanism in

survivors of severe TBI. Thus, the present study fits well into a growing body of research

indicating impaired performance monitoring following severe TBI and emphasizes the need for

continued specific examination of this dysfunction and the development and validation of

remediation or compensatory treatments.










Table 2-1. Demographic and mean summary data for severe TBI and control participants


Age (yrs)
Average educational level (yrs)
BDI-II score

Apathy evaluation scale

STAI-state
STAI-trait

FrSBe self-rating total

Apathy

Disinhibition

Executive dysfunction

FrSBe other-rating total

Apathy

Disinhibition

Executive dysfunction

FrSBe self/other concordance
SADI

HVLT total recall (trials 1-3)

HVLT long-delay recall

WMS-R logical memory I total

WMS-R logical memory II total

Digit span forward (max# of digits)

Digit span backward (max# of digits)

Trail making test part A (seconds)
Trail making test part B (seconds)

COWAT (FAS) total

Category fluency (animals) total


Severe TBI Control Analysis


(n = 19)
Mean SD

30.4 12.1

13.3 1.7

12.3 5.8

11.3 5.4

34.4 8.8

37.5 10.9

98.5 25.3
28.9 9.2

31.6 8.6

38.0 10.5
108.3 28.2

31.6 8.7

32.8 10.1
43.9 11.7

21.5 25.3

3.9 2.0

21.2 5.2

6.7 3.2
22.5 8.1

15.7 8.2

6.1 1.5

4.4 1.2

31.4 17.6
83.6 37.1

29.6 10.4

17.1 4.2


4.4

1.9
6.9

7.7

1.3

1.2

6.8
13.2

9.7

4.2


24.1

8.9
24.6

20.9

7.1

5.3

21.8
51.5

42.3

20.3


(n = 21)
Mean SD

25.4 9.5

14.1 1.3

3.7 2.9

8.6 4.0

26.7 5.9

30.4 6.9

70.4 23.1
23.9 6.8

25.7 6.0

35.5 20.1


-1.8

-2.5

-0.9

-2.1

-2.4

-2.6

2.3

3.7

-4.0

-2.4


.08

.02

.37

.04

.02

.01

.03

.001

.001

.02


Definition of abbreviations: BDI-II


Beck Depression Inventory-


-2nd Edition; STAI=State Trait


Anxiety Inventory; FrSBe=Frontal Systems Behavior Scale; SADI=Self-Awareness of Deficits
Interview; HVLT=Hopkins Verbal Learning Test; WMS-R=Wechsler Memory Scale-Revised
Edition; COWAT=Controlled Oral Word Association Test


t p

1.5 .15

-1.7 .09

6.0 .001

1.8 .08

3.3 .002

2.5 .02

3.4 .002

1.8 .07

2.3 .03

0.5 .65


Cohens-d

.46

.53

1.91

.57

1.04

.79

1.16

.62

.80

.15











.60

.85

.28

.65

.72

.75

.73

1.18

1.27

.76











Table 2-2. Injury characteristics and neuroradiological information for TBI participants (N= 19)
Age (yrs) Sex Etiology GCS LOC PTA Months Neuroradiology
(days) (days) Post


25 M Pedestrian
vs. vehicle
18 M MVA


49 M MVA




25 M MVA


18 M Motorcycle
accident



42 M MVA

52 M Fall from
heights

22 F Rollover
MVA


40 F MVA


23 M MVA


50 F Bicycle
accident


20 F MVA




21 M MVA


50 M Fall


6 21 24 5 Bilateral basal ganglia
hemorrhages
7 4 31 12 Bilateral frontal contusions;
effacement of cortical sulci
and basal cisterns
4 14 30 6 Bilateral frontal subdural
hygromas; left anterior
temporal contusion; right
periventricular white matter
infarct
5 N/A 28 18 Bilateral subdural hygromas
in frontal, parietal, and
temporal convexities
3 7 29 7 Intraparenchymal contusions
at tips of left and right frontal
horns-consistent with DAI;
small right temporal lobe and
right frontal lobe contusions
3 10 120 6 Intraventricular hemorrhage,
basilar skull fracture
4 5 19 4 Left frontal, left parietal, and
right frontal hemorrhagic
contusions
3 7 21 19 Left supraorbital hematoma;
right frontal hematoma;
bifrontal contusions

6 1 15 12 Left temporal-occipital
subarachnoid hemorrhage;
multiple skull fractures
4 18 20 6 Multiple frontal
contusions/Frontal
subarachnoid hemorrhage
8 49 53 6 Right epidural hematoma;
right orbitofrontal fractures


3 14 16 19 Right frontal contusions;
shear injury to left
frontoparietal lobe;
subarachnoid hemorrhage
with interpeduncular cistern
3 42 90 20 Right frontal subdural
hematoma; multiple skull
fractures
6 7 7 29 Right subdural hematoma;
right parietal extra-axial fluid








Table 2-2 Continued.
Age (yrs) Sex Etiology GCS LOC PTA Months Neuroradiology
(days) (days) Post
21 M Motorcycle 3 12 33 18 Right temporal contusions;
accident right frontal subarachnoid
hemorrhage;
Microhemorrhages along
gray-white junction of left
hemisphere and right parietal
lobe
24 M Boating 3 9 13 2 Right temporal lobe epidural
accident and subdural hematomas;
right anterior middle cranial
fossa hematoma
35 M Collision 8 7 N/A 15 Right temporal subdural
with wall hematoma; blood on right
thalamus and left internal
capsule; small uncal
herniation
36 M MVA 3 30 36 4 Small bilateral
intraventricular hemorrhages;
no additional findings
21 M MVA 3 41 50 6 Unavailable

0n A -- -- 1 66 3 I 11 --


(12.1) (1.8) (14.4) (28.4) (7.5)
Note: Last row is Mean ( Standard Deviation) values. LOC and PTA are shown in days unless
otherwise specified. Neuroradiological findings taken from medical record review of
neuroradiological reports from CT scans taken acutely after injury. MVA = Motor Vehicle
Accident; GCS = Glascow Coma Scale; LOC = Loss of consciousness; PTA = Post-traumatic
amnesia; DAI = Diffuse axonal injury

Table 2-3. Mean ( Standard Deviation) error rates (percent) and reaction time (milliseconds) on
the Stroop Task
Control TBI
(n_= 21) (n = 19)
Error Rates
Congruent .02 (.01) .04 (.08)
Incongruent .05 (.03) .11 (.15)
Correct-Trial Reaction Time (ms)
Congruent 583.5 (70.3) 723.8 (178.2)
Incongruent 726.0 (132.1) 900.5 (216.6)










Table 2-4. Mean ( Standard Deviation) ERN and Pe component amplitude (ptV) as a function of
task condition.
Control TBI
(n =21) (n = 19)
Amplitude (tV)
ERN
Correct -0.6(1.7) -1.4(1.2)
Incorrect -5.9 (4.2) -2.9 (2.8)
Pe
Correct -2.3 (4.6) -3.0 (2.6)
Incorrect 3.3 (4.6) 0.8 (3.4)




























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Figure 2-2. Grand average ERP waveforms depicting response-locked correct- and error-related
activity averaged across fronto-medial electrode locations for the ERN and top view
of the spline-interpolated voltage distribution maps showing mean voltages for error-
trial activity at 22ms. denotes the ERN.



Control


21JV


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I A
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I TBI


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Figure 2-3. Grand average ERP waveforms depicting response-locked correct- and error-related
activity averaged across centro-parietal electrode locations for the Pe and top view of
the spline-interpolated voltage distribution maps showing mean voltages for error-
trial activity at 322ms for controland 286ms for participants with TBI. denotes the
Pe component.





q


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i-5 1111111 5
-SPy 0 !S PV


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CHAPTER 3
COGNITIVE CONTROL ADJUSTMENT PROCESSES FOLLOWING SEVERE
TRAUMATIC BRAIN INJURY

Cognitive control theory suggests conflict effects are differentially reduced following high-

relative to low-conflict trials. Such reactive adjustments in control, frequently termed "conflict

adaptation effects," indicate a dynamic interplay between regulative and evaluative components

of cognitive control necessary for efficient goal-directed behavior. The current study examined

conflict adaptation effects while survivors of severe traumatic brain injury (TBI) and healthy

control participants performed a single-trial, color-naming version of the Stroop task. The

incongruent minus congruent trial Stroop effect for trials preceded by incongruent (high conflict)

and congruent (low conflict) trials was compared for behavioral (i.e., RT and error rate) and

electrophysiological (i.e., the N450 and conflict SP components of the event-related potential

[ERP]) reflections of cognitive control. Behavioral data indicate a reduction in the Stroop effect

for RTs when preceded by incongruent trials that cannot be accounted for by stimulus repetition

priming. The magnitude of these effects did not differentiate control and TBI participants. ERP

data indicate a conflict slow potential that differentiated incongruent from congruent trials and

was larger in magnitude for control than TBI participants. Conflict adaptation effects were not

present in the omnibus ERP data; however, planned comparisons revealed a decreased amplitude

tonic conflict SP when preceded by incongruent trials in control participants. Measurements of

conflict adaptation did not correlate with measures of deficit awareness in participants with TBI.

Introduction

Goal-directed behavior requires an adaptive cognitive control system for recognizing

appropriate or inappropriate task completion and dynamically adjusting performance when

control is misdirected or inadequate. The evaluative control mechanisms required to monitor

performance for errors or conflict and to signal for subsequent adjustments are, therefore, critical









to adaptive behavior (see Botvinick et al., 2001). The first studies of evaluative control processes

were completed using single cell recordings in macaque monkeys, with findings indicating a

negative field potential in the ACC following errors (Gemba et al., 1986; Niki & Watanabe,

1979). The human analogue, the error-related negativity (ERN) discussed above, is generated in

the ACC and was initially thought to solely reflect the detection of errors (Gehring et al., 1993;

Gehring & Knight, 2000; van Veen & Carter, 2002a, 2002b). The interpretation that ACC

activation solely represents the detection of errors has been challenged on grounds that the

negativity reflects response conflict (Botvinick et al., 2001; Yeung et al., 2004). Response

conflict occurs when two competing response options are simultaneously active. For example, on

an error trial conflict occurs because both the error and correct response are simultaneously

active. The degree of conflict may be modulated by the degree to which the error representation

has been activated (e.g., prepotency), stimulus-response mapping (e.g., simpler stimulus-

response mapping for the error representation), or because an individual is unsure of how to

respond.

One central aspect of cognitive control theory is that response conflict alone, even in the

absence of an error, is sufficient to lead to conflict-related ACC activation (Botvinick et al.,

2001). This has been demonstrated on tasks such as the Eriksen Flanker task (Eriksen & Eriksen,

1974) and the Stroop task (Stroop, 1935) where incongruent trials activate a prepotent, highly

practiced response simultaneously with a less practiced option. For example, in the Stroop color-

naming condition, participants are asked to name the color of a word written in a different color

of ink (e.g., the word RED written in blue ink). The more practiced response to read the word

must be inhibited in favor of following the instruction to name the color of ink; however, conflict









occurs because both the color-naming and word-reading representations are simultaneously

activated (Cohen et al., 1992).

A stimulus-locked ERP manifestation of this response conflict is a late fronto-central ERP

signature referred to as the N450 (Perlstein et al., 2006; van Veen & Carter, 2002a, 2002b; West

& Alain, 1999, 2000, West, 2003). The N450 is a negative-going deflection in the ERP

waveform occurring approximately 450 milliseconds following the presentation of stimulus with

inherent response conflict. The N450 is largest under conditions of high response conflict, such

as the incongruent condition of the Stroop color-naming task (Grapperon et al., 1988; Liotti et

al., 2000; Rebai et al., 1997; West & Alain, 1999), and has greater amplitude when the degree of

conflict and stimulus prepotency is increased by utilizing relatively more congruent than

incongruent trials (e.g., 70% congruent vs. 30% incongruent; West & Alain, 2000). Functional

magnetic resonance imaging studies (e.g., MacDonald et al., 2000) and ERP source localization

efforts implicate the ACC as the neural generator of the N450 component (Liotti et al., 2000; van

Veen & Carter, 2002a, 2002b; West, 2003). A recent study from our lab (Perlstein et al., 2006)

demonstrated reduced N450 differentiation between congruent and incongruent color-naming

trials in survivors of severe TBI and a previous study showed altered amplitude ERP activity in

the latency range of the N450 in mild TBI participants while performing a single-trial version of

the Stroop task (Potter et al., 2002). Similarly, findings from recent fMRI studies suggest altered

ACC activity in moderate-to-severe TBI survivors on the Stroop or similar conflict-laden tasks

(Scheibel et al., 2007; Soeda et al., 2005).

Adjustments in Control

Detection of response conflict is necessary to cognitive control processes only as it

relates to subsequent adjustments in cognitive control to better complete the task at hand. One

prediction of cognitive control theory is that the occurrence of response conflict and the









subsequent signals for change in regulative control processes should result in behavioral

adjustments (Botvinick et al., 2001). That is, conflict-related evaluative activity in ACC should

signal for increased utilization of dlPFC-mediated regulative control processes leading to

improved behavioral (i.e., RT and error rate) performance.

Several authors have employed the Stroop color-naming task to support this prediction.

Conflict is present for incongruent Stroop trials (e.g., BLUE written in red) relative to congruent

trials (RED written in red) because of the simultaneous activation of competing representations.

Behavioral adjustments in control following this type of conflict include faster RTs on

incongruent trials preceded by incongruent trials (incongruent-incongruent) than on incongruent

trials preceded by congruent trials (congruent-incongruent), and slower RTs for congruent trials

preceded by incongruent trials (incongruent-congruent) and congruent trials preceded by

congruent trials (congruent-congruent). The explanation offered for this pattern of behavioral

adjustments is that high conflict detected on an incongruent trial leads to recruitment of greater

cognitive resources than on congruent trials; the cognitive resources are then utilized on the

subsequent trial to enhance performance (Botvinick et al., 2001; Gratton et al., 1992; Kerns,

2006; Kerns et al., 2004; Ullsperger et al., 2005). In consequence, RTs on incongruent-

incongruent trials are faster than congruent-incongruent trials because the preceding incongruent

trial results in increased signaling for cognitive control, while when the preceding trial is

congruent fewer cognitive resources are allocated for use on the following trial. These

adjustments in RTs are frequently referred to as "conflict adaptation effects" and have been

demonstrated in several behavioral studies using tasks with both congruent and incongruent

conditions (e.g., the Stroop, Simon, and Eriksen Flanker Tasks; Botvinick et al., 1999; di

Pellegrino et al., 2007; Egner & Hirsch, 2005; Gratton et al., 1992; Kerns et al., 2004; Notebaert









et al., 2006; Ullsperger et al., 2005; West & Moore, 2005; Verbruggen et al., 2006). The neural

mechanisms underlying conflict adaptation in neurologically-normal participants have only

recently been explored and few studies to date have examined the neural mechanisms of manifest

impairments in these processes (Egner & Hirsch, 2005; Kerns, 2004, 2006; di Pellegrino et al.,

2007; Stemmer et al., 2004).

Kerns et al., (2004) used a conflict adaptation paradigm (i.e., a single-trial Stroop task) and

fMRI to test the prediction that conflict-related evaluative activity in the ACC should predict

subsequent increases in dlPFC-mediated regulative control processes. A brief summary of their

findings indicates that, first, there was significantly less ACC activity on incongruent-

incongruent trials than congruent-incongruent trials, presumably because increased control was

recruited for incongruent-incongruent trials and subsequently reduced the amount of conflict

associated with the second incongruent trial presentation. Second, they divided trials based on

behavioral performance into high adjustment (e.g., much faster performance on incongruent

trials preceded by an incongruent trial) and low adjustment (e.g., little difference between

subsequent incongruent trials). Increased ACC activity on the previous trial was associated with

high adjustment trials (i.e., increased detection of conflict and subsequent signaling for increased

control) compared to low adjustment trials where the signal to implement increased control was

less robust. Third, they examined dlPFC activity in conjunction with high and low adjustment

trials and found trials exhibiting the greatest adjustments in behavior following conflict were

associated with the greatest dlPFC activity, indicating a recruitment of resources subsequent to

the detection of conflict. Finally, Kerns and colleagues tested whether ACC activity on conflict

trials predicted dlPFC activity on the subsequent trial. They found a reliable correlation between

ACC and dlPFC activity on subsequent trials suggesting a direct relationship between evaluative









ACC activity and regulative dlPFC activity. In other words, ACC-mediated conflict monitoring

processes signal for increased dlPFC-related regulative control processes.

ERP indices of recruitment of cognitive control resources have also been examined.

Researchers have observed a sustained conflict slow potential (conflict SP) that is present

following the more phasic ERP conflict-detection component, the N450 (Liotti et al., 2000; West

& Alain, 2000). The conflict SP reflects a sustained parietal positivity/lateral frontal negativity

occurring approximately 500ms after stimulus onset that is more positive following correct

incongruent trials than congruent trials or errors (Liotti et al., 2000; West & Alain, 2000; West,

2003). The neural generator of the slow wave remains uncertain; however, source localization

studies suggest neural contributions from areas of the middle and inferior frontal gyri, as well as

the extrastriate cortex (West, 2003).

Current theories suggest the conflict SP represents the neural manifestation of resolving

response conflict and, perhaps, signaling for activation of regulative component processes of

cognitive control (Perlstein et al., 2006; West, 2003; West & Alain, 2000). Studies from our

laboratory also indicate a frontal conflict SP that is more negative to incongruent than congruent

trials (Larson et al., 2004; Perlstein et al., 2006) in control participants. Survivors of severe TBI

failed to exhibit a congruency-related effect on the frontal conflict SP suggesting that TBI

patients did not implement regulative control to adaptively resolve the conflict inherent in the

incongruent color-naming condition (Perlstein et al., 2006). No studies to date have examined the

effects of sequential trials (e.g., incongruent following congruent trials) on the conflict SP.

However, if the conflict SP does represent resolution of conflict, it is likely the conflict SP would

be largest on congruent-incongruent trials and somewhat smaller on incongruent-incongruent

trials due to the hypothesized adjustments in cognitive control following incongruent trials.









Conflict Adaptation vs. Repetition Priming

Mayr et al., (2003) suggest that the repetition of the exact stimulus or stimulus attributes

(e.g., the color of the word in the Stroop color-naming condition) accounts for the conflict

adaptation effect following incongruent-incongruent trials relative to congruent-incongruent

trials. That is, the conflict adaptation effect may be accounted for by bottom-up repetition

priming mechanisms rather than top-down adjustments in cognitive control component

processes. To test this hypothesis, Mayr et al., (2003) conducted two separate studies and found

conflict adaptation effects were present only when there was an exact stimulus repetition and

were not present when the experimental task ensured stimulus elements were not repeated.

Subsequent studies provide support for both the repetition priming hypothesis (Hommel et al.,

2004; Niewenhuis et al., 2006) and the conflict adaptation effect when repetition priming was

controlled or removed (Kerns et al., 2004; Ullsperger et al., 2005) as well as a recent study

suggesting both bottom-up and top-down mechanisms contribute to the conflict adaptation effect

(Notebaert et al., 2006). In one example, Niewenhuis et al., (2006) conducted five separate

experiments with and without stimulus repetitions. Findings extend those of Mayr et al., by

indicating a response repetition led to faster RTs, while RTs did not differentiate conditions in

the absence of response repetitions. In contrast, Kerns et al., (2004) removed both word and

color repetitions from a single-trial Stroop task and found robust conflict adaptation effects.

Other investigators have, similarly, found intact conflict adaptation effects when stimulus

repetition trials were removed from the data or not available in the task (Ullsperger et al., 2005;

Verbruggen et al., 2006).

An additional potential confound of examining the neural reflections of conflict

adaptation effects is the inclusion of error and post-error trials (Egner & Hirsch, 2005). Error

trials are frequently associated with faster RTs (see Ridderinkhof, 2002), while post-error trials









are associated with reliable RT slowing (Rabbitt, 1966). Thus, we exclude error and post-error

trials from analyses in an effort to isolate manifestations of conflict adaptation processes from

those associated with error processing.

Current Study

Conflict adaptation effects on the Stroop task provide an ideal paradigm for examining

reactive adjustments in cognitive control and, more specifically, the relationship between

evaluative and regulative control component processes following TBI. Thus, the primary aim of

the current study was to examine the impact of severe TBI on behavioral (RT and error rate) and

electrophysiological (N450 and conflict SP components of the ERP) manifestations of conflict

adaptation effects. We predicted control participants would demonstrate robust conflict

adaptation effects manifest by a decreased Stroop effect incongruentt minus congruent) when

preceded by incongruent relative to congruent trials and smaller N450 and conflict SP

components incongruentt minus congruent differences) when preceded by incongruent trials. For

TBI participants, we predicted if cognitive control component processes (i.e., conflict monitoring

and signaling for adjustments in control) are impaired then the conflict adaptation effect should

be reduced in magnitude relative to control participants for RTs and electrophysiological indices

should not differentiate sequential trial conditions for participants with TBI. Notably, this is the

first ERP investigation of conflict adaptation effects.

Given the potential confound of repetition priming on conflict adaptation effects,

secondary analyses examined both behavioral and electrophysiological manifestations of

sequential trials in the absence of color repetitions. Color repetitions were chosen for exclusion

because the current version of the Stroop task is color-naming only. Finally, as noted in the

General Introduction and Experiment 1, one important aspect of detecting, processing, and

overcoming response conflict may be being aware of conflict and, subsequently, aware of your









own deficits. Thus, we also tested the hypothesis that measures of conflict detection and

processing (i.e., RT and N450/conflict SP amplitude) are related to measures of deficit

awareness.

Methods

Participants, neuropsychological and mood measures, measures of deficit awareness, and

the experimental task are the same as those utilized in Experiment 1. The reader is referred above

for these indices (pages 23-30).

Electrophysiological Data Recording

Electroencephalogram was recorded from 64 scalp sites using a geodesic sensor net and

Electrical Geodesics, Inc., (EGI; Eugene, Oregon) amplifier system (20K gain, nominal

bandpass=. 10-100Hz). Electrode placements enabled recording vertical and horizontal eye

movements reflecting electro-oculographic (EOG) activity. Electroencephalogram data were

initially referenced to Cz and digitized continuously at 250Hz with a 16-bit analog-to-digital

converter. A right posterior electrode approximately two inches behind the right mastoid served

as common ground. Electrode impedance was maintained below 50kQ. Eye movement and blink

artifacts were corrected using a spatial filtering method (Berg and Scherg, 1994; Ille, Berg, and

Scherg, 1997, 2002) utilized through Brain Electric Source Analysis (BESA) software (Scherg,

1990). Data from the EEG were then segmented into condition-related epochs and single trial

epochs with voltages that exceeded 150.IV or transitional (sample-to-sample) thresholds of

100lV discarded. Electroencephalogram data were digitally re-referenced to an average

reference (Bertrand et al., 1985) in order to yield a reference-free representation of

electrophysiological activity and to reconstruct the EEG at the Cz reference, then digitally low-

pass filtered at 15Hz.









Event-related Potential Reduction and Measurement

Individual-subject stimulus-locked averages were derived for correct trials only for each

congruency (congruent, incongruent) and sequential trial repetition possibility (congruent-

congruent, congruent-incongruent, incongruent-congruent, and incongruent-incongruent).

Epochs spanned 100ms prior to and 900ms following stimulus presentation. Data were baseline

corrected using the 100ms pre-stimulus window. Analyses of electrophysiological data focused

on selected electrode sites based on previous findings indicating that the ERP modulations of

interest are relatively focal over fronto-medial (N450; Liotti et al., 2000; West & Alain, 1999,

2000) and posterior parietal sites (conflict SP; Liotti et al., 2000; West & Alain, 2000), as well as

the scalp-distribution maps of the present data which indicated the ERP deflections of interest

were greatest in amplitude over these regions. Consistent with our previous ERP study of

cognitive control in TBI (Perlstein et al., 2006), the stimulus-locked phasic fronto-central N450

was quantified as the mean voltage between 450-500ms at sites 4 (FCz), 65 (Cz), 5, and 55 (see

Figure 2-1), while values for the more tonic conflict SP were measured as the mean voltage from

650-750ms at electrode sites 34 (Pz), 38, 33 and 41 (see Figure 2-1). Measured voltages for both

components of interest were averaged across all four sites prior to analyses. Latency

measurements for the N450 component were indexed as the time of the peak negative-going

amplitude. No latency measurements are provided for the conflict SP, as it is a slow, tonic

component.

To assess the potential for non-specific or generalized ERP amplitude decrements and/or

latency shifts in TBI participant ERP waveforms, P1 amplitude and latency data reflecting

extrastriate cortex activity (Di Russo et al., 2002) were extracted. Both P1 amplitude and latency

were quantified at the first peak positive deflection in the ERP between 50 and 150ms for









congruent and incongruent trials averaged across the bilateral locations of maximum P1

amplitude (average of posterior electrode sites 32 and 45-see Figure 2-1).

Data Analysis

Median correct-trial RTs (Ratcliff, 1993), arcsine transformed error rates (Neter et al.,

1985) excluding non-response trials, and ERP component amplitude and latency data were

analyzed using separate repeated-measures analyses of variance (ANOVA). In an effort to isolate

conflict adaptation activity, trials immediately following errors were excluded from analyses of

RTs and error rates. The dependent variables were RTs (msec), error rates, and ERP component

amplitudes and latencies. The Huynh-Feldt epsilon adjustment was applied for ANOVAs with

more than two levels of a within-subject factor to correct for possible violations of sphericity and

partial-eta2 (n2) reported as a measure of effect size. Tests of between-group simple effects were

used to decompose interactions, while planned comparisons were used to examine congruency

effects within each group. Cohen's-d effect sizes (Cohen, 1988) were calculated for condition-

related effects.

Each dependent variable was analyzed separately. Initial analyses focused on overall task

performance via two-factorial ANOVAs with group (TBI, control) as the between-subjects factor

and congruency (congruent, incongruent) as the within-subject factor. To examine potential

conflict adaptation effects, 'congruency-related adjustment scores' were calculated by taking the

incongruent minus congruent difference for trials preceded by a congruent trial (i.e., congruent-

incongruent minus congruent-congruent trials) or an incongruent trial (i.e., incongruent-

incongruent minus incongruent-congruent). Difference scores were subjected to a two-factorial

ANOVA with group (TBI, control) as the between subjects factor and 'congruency-related









adjustment score' (difference score for trials preceded by congruent trials, difference scores for

trials preceded by incongruent trials) as the within-subjects factor.

We next conducted a series of Pearson product-moment correlations to test specific

predictions regarding the relationship between ERP reflections of conflict detection/processing

(i.e., N450 and conflict SP amplitude) and awareness of deficits. For initial correlations, an

incongruent minus congruent difference score was calculated on the amplitude of the N450 and

conflict SP components and compared with measures of deficit awareness (SADI and FrSBe

concordance score) in TBI participants. We predicted TBI participants with lower deficit

awareness scores would show smaller incongruent minus congruent differences on ERP

component amplitudes. A second set of correlations tested the prediction that TBI participants

who were less aware of their deficits would show smaller RT conflict adaptation effects and

smaller ERP manifestations of conflict adaptation. These correlations included the 'congruency-

related adjustment scores' incongruentt minus congruent trials) for RTs as well as N450 and

conflict SP amplitude. Similar to Experiment 1, we recomputed the correlations including only

those participants with only positive, rather than absolute value, FrSBe concordance scores (i.e.,

higher significant other than TBI survivor scores) to account for participants who may be

hypervigilent to their deficits.

Results

Behavioral Performance

Overall RTs and error rates for the Stroop task were not significantly correlated in control

participants, r(20)=-0.17, p>.47, but were significantly positively correlated in participants with

TBI, r(18)=.47, p<.04. Results suggest speed/accuracy trade-off did not influence control or TBI

participants, as a positive correlation indicates longer RTs were associated with increased error

rates, opposite the direction suggestive of a speed/accuracy trade-off









Response times. Data for correct-trial RTs as a function of group, previous trial

congruency, and current trial congruency are presented in Table 3-1 and depicted in Figure 3-1.

Analyses on correct-trial RTs revealed the expected generalized slowing in participants with

severe TBI, as reflected in a significant main effect of group, F(1,38)=11.75, P<.001, 12 =.24. A

main effect of current trial congruency reflected the anticipated RT interference, F(1,38)=73.19,

p<.001, 2 =.66, with both groups showing longer RTs to the incongruent than congruent

condition (i.e., the standard Stroop effect [TBI: t(18)=4.97, 2<.001, d= .97; controls: t(20)=9.43,

p<.001, d=1.04]). The Group x Congruency interaction was not statistically reliable, F(1,38)=.84,

p>.37, 2 .02, indicating the two groups showed similar levels of current trial congruency-

related RT interference.

Of greater interest to the present study were the potential conflict adaptation effects (Figure

3-1; Table 3-3). The Group x Congruency-Related Adjustment Score ANOVA yielded a main

effect of adjustment score, F(1,38)=12.59, p<.001, =.25, indicated an overall conflict

adaptation effect; however, the Group x Adjustment Score interaction was not significant,

F(1,38)=.74, p>.40, 12 =.02, indicating the magnitude of the conflict adaptation effect was

similar between groups. Supporting this observation, planned contrasts indicated incongruent

minus congruent trial RTs were greater following congruent than following incongruent trials for

both TBI, t(18)=2.53, p<.02, d=.45, and control participants, t(20)=2.54, p<.02, d=.44. Survivors

of severe TBI showed a 205.42ms (SD = 146.54) Stroop effect incongruentt minus congruent

RTs) when preceded by a congruent trial and a 149.4ms (99.3) Stroop effect when preceded by

an incongruent trial incongruentt minus congruent preceding trial difference = 56.0ms). Control

participants showed a 157.9ms (76.0) Stroop effect when preceded by congruent trials and a









123.7ms (+80.9) effect when preceded by incongruent trials incongruentt minus congruent

preceding trial difference = 34.19ms).

Error rates. Data for mean error rates as a function of group, previous trial congruency,

and current trial congruency are presented in Table 3-2 and depicted in Figure 3-2. The Group x

Congruency ANOVA on arcsine-corrected error rates indicated comparable error rates between

groups, as the main effect of group was not statistically significant, F(1,38)=2.21, p>.14, 2 =.06.

A significant main effect of current trial congruency, F(1,38)=83.68, p<.001, !1 =.69, reflected

error rate interference, with both groups committing more errors to the incongruent than

congruent condition (TBI: t(18)=6.37, 2<.001, d=.58; controls: t(20)=6.57, P<.001, d=1.34). A

non-significant Group x Congruency interaction, F(1,38)=1.47, p>.23, 2 =.04, indicated similar

error rate profiles between groups as a function of congruency.

Similar to the data for RTs, the Group x Congruency-Related Adjustment Score ANOVA

on arcsine-corrected error rates yielded a main effect of adjustment score, F(1,38)=4.00, p=.05,

12 =.10, indicating the presence of a conflict adaptation effect when collapsed across groups

(Table 3-3). The Group x Adjustment Score interaction was not significant, F(1,38)=.03, p>.86,

12 =.001, nor were planned comparisons of the incongruent minus congruent difference scores

for TBI, t(18)=1.53, 1>.18, d=.34, or healthy control participants, t(20)=1.30, 1>.20, d=.32.

ERP Data

Healthy control participants and survivors of severe TBI did not differ on number of trials

retained for averaging on congruent, t(38)=1.16, p>.25, d=.37, or incongruent conditions,

t(38)=1.40, p>.17, d=.44. Congruent trial waveforms contained an average ( SD) of 326.1+70.5

trials for participants with TBI and 346.3+35.0 trials for controls, while incongruent waveforms

contained an average of 132.236.6 trials for participants with TBI and 144.616.7 trials for









controls. When broken down to examine sequential trial effects, groups did not differ on number

of trials retained for congruent-congruent, t(38)=1.21, p>.23, d=.38 (TBI = 216.553.8 trials;

controls = 232.1+23.6 trials), congruent-incongruent, t(38)=1.26, p>.22, d=.40 (TBI = 91.127.5

trials; controls = 99.512.9 trials), or incongruent-congruent conditions, t(38)=1.27, p>.21, d=.40

(TBI = 90.127.8 trials; controls = 98.813.2 trials). Groups did significantly differ on number

of trials retained for the incongruent-incongruent condition, t(38)=2.15, p<.04, d=.68 (TBI =

34.3+11.3 trials; controls = 40.25.4 trials) due to more artifact trials rejected for participants

with TBI, rather than increased error rates, as noted above.

P1 amplitude and latency. A Group x Congruency ANOVA on stimulus-locked grand

average ERP waveforms averaged across the two channels of greatest P1 amplitude (channels 32

and 45; one from each hemisphere at posterior scalp locations-see Figure 2-1) was conducted to

examine the possibility of generalized amplitude decrements or latency shifts for TBI

participants. Results of the analysis of P1 amplitude indicate no main effect of congruency,

F(1,38)=.03, p>.86, r =.001, no Group x Congruency interaction, F(1,38)=1.52, p>.22, 1=.04,

and no main effect of group, F(1,38)=.70, p>.41, 1r=.02. Latency data for the P1 component

were similar, with no significant main effect of congruency, F(1,38)=.07, 2>.79, r2=.002, no

Group x Congruency interaction, F(1,38)=.70, p>.41, n2=.02, and no main effect of group,

F(1,38)=1.73, 2>.20, q2=.04. Thus, data suggest that there is not a significant generalized

amplitude decrement or latency shift in the ERPs of the TBI participants relative to healthy

controls.

Stimulus-locked grand average ERP waveforms and spline interpolated current source

density maps for the fronto-medial N450 as a function of group and congruency are presented in

Figure 3-3, those for the conflict SP are presented in Figure 3-4. Grand average ERPs for both









groups and each repetition category (i.e., Previous x Current Trial averages) are presented in

Figure 3-5. Mean (+ SD) component amplitude data are presented in Table 3-4 and depicted in

Figure 3-6 for the N450 and Figure 3-7 for the conflict SP.

N450 amplitude. Examination of stimulus-locked ERP waveforms (Figure 3-3) revealed a

negative-going deflection that is more negative to incongruent than congruent trials in control

participants, but does differentiate congruencies for participants with TBI. Contrary to

predictions, the Group x Congruency ANOVA on N450 amplitude did not yield a significant

main effect of current trial congruency, F(1,38)=2.57, p>.12, 2 =.06; neither group showed

reliable N450 amplitude differentiation of the incongruent and congruent conditions (TBI:

t(18)=.88, >.39, d=.09; controls: t(20)=1.38, p>.18, d=.11). The main effect of group on N450

component amplitude was not significant, F(1,38)=.01, 2>.99, 2 =.00.

Consistent with the absence of congruency differentiation on N450 component amplitude,

the Group x Congruency-Related Adjustment Score ANOVA on incongruent minus congruent

difference scores did not demonstrate a conflict adaptation effect as evidenced by a non-

significant main effect of congruency, F(1,38)=.03, p>.87, 2 =.001. Similarly, there was not a

significant Group x Congruency interaction, F(1,38)=1.60, P>.21,12 =.04, nor a main effect of

group, F(1,38)=.88, 2>.35, 2=.02 (see Table 3-4; Figures 3-5 and 3-6). Planned comparisons on

incongruent minus congruent difference scores confirmed the absence of conflict adaptation

changes in N450 amplitude for both TBI, t(18)=.87, p>.39, d=.28, and control participants,

t(20)=.93, >.36, d=21.

N450 latency. A Group x Congruency ANOVA indicated N450 peak latencies were

similar for both congruencies, as reflected by a non-significant main effect of current trial

congruency, F(1,38)=.60, p>.45, 12 =.02. There were no group differences in N450 latency, with









no significant Group x Congruency interaction, F(1,38)=.01, p>.90, 2 =.001, or main effect of

group, F(1,38)=1.50, p>.23, 2 =.04. Similarly, there were no main effects or interactions

involving group or congruency-related adjustment scores for N450 latency data, Fs < 1.66,

ps>.20.

Conflict SP amplitude. In contrast to results of N450 amplitude, examination of conflict

SP amplitudes (Figure 3-4) revealed a significant main effect of current trial congruency,

F(1,38)=21.15, p<.001, 2 =.36, as well as a significant Group x Congruency interaction,

F(1,38)=5.12, p<.03, 2 =. 12. The current trial congruency effect reflected greater positivity to

the incongruent than congruent condition; planned contrasts revealed the conflict SP was

significantly more positive to the incongruent than congruent condition in controls, t(20)=4.44,

p<.001, d=.79, and at trend level for survivors of severe TBI, t(18)=1.90, 2=.07, d=.34. The

Group x Congruency interaction was found in the absence of an overall main effect of group on

conflict SP component amplitude, F(1,38)=.88, p>.35, 12 =.02.

For conflict adaptation effects on the conflict SP (Figures 3-5 and 3-7), the Group x

Congruency-Related Adjustment Score ANOVA on incongruent minus congruent trials yielded a

non-significant main effect of adjustment score, F(1,38)=.02, 1P>.89, 112 =.001, as well as a non-

significant Group x Adjustment Score interaction, F(1,38)=1.40, P>.24, 2 =.04. Planned

contrasts, however, indicated the conflict SP for the incongruent minus congruent difference was

greater following congruent than incongruent trials for control, t(20)=2.10, p<.05, d=.41, but not

TBI participants, t(18)=.53, p>.61, d=.20.

Impact of Repetition Priming

As pointed out above, recent research challenges the interpretation of sequential trial

effects as reflecting top-down conflict adaptation, suggesting instead that such effects are due to

bottom-up repetition priming mechanisms (Mayr et al., 2003; di Pellegrino et al., 2007). Given









this, we re-analyzed both behavioral (RT and error rate) and ERP (N450 and conflict SP) data

excluding sequential trials of the same color. Excluding trials based on stimulus color was

chosen because responses on the version of the Stroop task employed were color-naming only

and exclusion of color repeats ensures possible direct stimulus repetitions are excluded from the

congruent-congruent and incongruent-incongruent conditions.

Behavioral data. The pattern of results for the Group x Congruency-Related Adjustment

Score ANOVA on RTs and error rates was largely consistent with previous analyses following

removal of color repetitions (see the right side of Tables 3-1 and 3-2). For RTs, a main effect of

adjustment score remained, F(1,38)=52.50, p<.001, 12 =.15, while the Group x Adjustment Score

interaction was not significant, F(1,38)=2.40, p>. 13, 12 =.06. For arcsine-corrected error rates,

the main effect of difference score was not maintained, F(1,38)=1.44, P>.24, 12 =.04, indicating

the modest sequential trial effect on error rates reported above may be influenced by repetition

priming. The Group x Adjustment Score ANOVA remained non-significant, F(1,38)=.25, P>.62,

1 =.006.

ERP data. When color repetitions were removed, the pattern of N450 and conflict SP

results remained consistent with data presented previously (see right side of Table 3-2). For the

N450, neither the main effect of adjustment score, F(1,38)=.70, P>.41,112 =.02, nor the Group x

Adjustment Score interaction, F(1,38)=.57, p>.46, 12 =.02, were statistically significant.

Similarly for the conflict SP, the main effect of adjustment score was not significant,

F(1,38)=1.52, p>.23, 1 =.04, nor was the Group x Adjustment Score interaction, F(1,38)=.30,

p>.59, Y2=.008.

Correlational Analyses

Due to the relatively small influence of repetition priming in the variables of interest for

the correlations (RT and N450/conflict SP amplitude), Pearson's correlation analyses (one-









tailed) were conducted on all trials. Initial correlations indicated that the conflict SP incongruent

minus congruent difference score significantly correlated with both the SADI, r(18)=-.42, p2<.04

(Figure 3-8), and the FrSBe concordance score, r(17)=.49, p<.024 (Figure 3-9); no significant

correlations were noted with N450 amplitude, rs<. 11, ps>.25. Subsequent examination of the

conflict SP correlation with deficit awareness measures revealed an outlier that, when removed

from analyses, rendered the correlations with both the SADI, r(18)=-.12, p>.31, and the FrSBe

concordance score, r(17)=-.006, p>.49, non-significant. Correlations (excluding the single

outlier) of RT and ERP congruency-related adjustment scores with measures of deficit awareness

yielded no statistically significant associations, rs< .36 ps> .07. Similarly, when FrSBe

concordance score analyses were re-computed with only participants who endorsed fewer

symptoms than their caregivers no significant correlations were present, rs< .52 |, ps>.07.

Discussion

In this experiment, we examined the behavioral and electrophysiological correlates of

conflict processing and adaptation effects in survivors of severe TBI and healthy control

participants. Behavioral data revealed the anticipated increases in RTs and error rates on

incongruent relative to congruent trials (i.e., Stroop interference) for both TBI and control

participants. Contrary to predictions, TBI and control participants did not differ on the magnitude

of RT or error rate interference. Likewise, both groups showed a conflict adaptation effect

wherein the incongruent minus congruent Stroop RT effect disproportionately decreased when

preceded by incongruent relative to congruent stimuli. Error rates on incongruent trials similarly

decreased when preceded by incongruent relative to congruent trials, but only when pooled

across control and TBI groups.









In contrast to predictions, participants with TBI showed RT and error rate conflict

adaptation effects of similar magnitude to those of healthy control participants. These results are

consistent with a recent study indicating patients with focal lesions to the rostral ACC following

anterior communicating artery (AcoA) aneurysm demonstrated abolished conflict adaptation

effects, while neurologically-injured control participants with more diffuse neural damage or

aneurysm not specifically affecting the ACC showed conflict adaptation effects the same in

magnitude to those of neurologically-healthy controls (di Pellegrino et al., 2007). As noted

above, several studies suggest interplay between medial and lateral frontal cortices (including the

ACC and dlPFC, respectively) in monitoring for conflict and utilizing conflict information to

dynamically allocate cognitive control resources and improve task performance (Kerns et al.,

2004; Egner & Hirsch, 2005). The presence of behavioral conflict adaptation effects that did not

differ from those of healthy control participants in the current heterogeneous TBI sample-none

of whom, to the best of our knowledge, experienced focal ACC lesions--indicates direct insult to

the ACC (or potentially the dlPFC) may be necessary for disruption of conflict adaptation

mechanisms. Supporting this view, West & Moore (2005) found conflict adaptation effects of

similar magnitude between young and old adults-despite previous findings that cognitive

control mechanisms are impaired in older adults (West, 2004).

Event-related potentials were used to temporally dissociate neural activity reflecting

conflict monitoring and conflict adaptation (Perlstein et al., 2006; West, 2004; West, 2003; West

& Moore, 2005). Consistent with predictions, a distinct slow potential, the conflict SP,

differentiated congruent and incongruent trials. The conflict SP is thought to reflect regulative

aspects of cognitive control, perhaps involving processes devoted to the resolution of response

conflict or signaling for increased implementation of attentional control (Liotti et al., 2001;









Perlstein et al., 2006; West, 2003; West & Alain, 2000). While both healthy controls and

participants with TBI demonstrated a clear conflict SP, control participants showed significantly

greater differentiation between incongruent and congruent trials than participants with TBI.

Considered in the context of previous studies indicating impaired conflict resolution processes

following severe TBI (Perlstein et al., 2006), this finding may indicate participants with TBI did

not implement regulative control to the same extent as control participants in order to adaptively

resolve the conflict inherent in the incongruent Stroop color-naming condition. Behavioral

findings (i.e., similar levels of Stroop RT and error rate interference) and the relative similarity in

conflict SP pattern between control and TBI participants cast some doubt upon this

interpretation.

If, as suggested by cognitive control theory, the detection of response conflict signals for

the recruitment of controlled regulative strategies toward adaptive resolution of this conflict

(Botvinick et al., 1999; Kerns et al., 2004; Miller & Cohen, 2001), the conflict SP should be

smaller on trials preceded by incongruent stimuli where increased attentional control has been

implemented. In contrast to this prediction, no main effect of conflict SP adjustment score was

found, nor was there a significant Group x Adjustment Score interaction. When only control

participants were considered in a planned contrast, trials preceded by incongruent stimuli

demonstrated decreased amplitude conflict SP relative to trials preceded by congruent stimuli.

Given that there was not a significant main effect or interaction of the omnibus ANOVA, these

results are tentative and should be interpreted with caution. Moreover, the finding that TBI

participants showed similar levels of RT-related conflict adaptation argues against differential

group-related conflict resolution processes.









Event-related potential findings with regard to the conflict-detection N450 were contrary to

predictions and previous findings from our laboratory (Perlstein et al., 2006). Indeed, the lack of

N450 differentiation between incongruent and congruent color-naming stimuli regardless of

preceding trial is unexpected. The reasons for the lack of differentiation are unclear, and are

unlikely to be due to the EEG acquisition parameters, since we have successfully obtained the

N450 in previous studies using similar recording parameters (Perlstein et al., 2006), or to the

modality of response (i.e., vocal, manual), as N450 has been obtained using both response

modalities (e.g., Liotti et al., 2000), or to latency differences between groups, as the N450

latency did not differ between groups. Thus, the absence of a clear N450 that differentiates

congruencies limits our ability to make firm conclusions regarding the integrity of stimulus-

related conflict detection processes, as this component has most reliably been thought to reflect

conflict detection (see West et al., 2005 for review), as well as the function of conflict-detection

processes in the conflict adaptation effect.

As noted previously, recent research suggests conflict adaptation effects may be due to

repetition priming rather than compensatory adjustments of cognitive control processes (Mayr et

al., 2003). Current findings suggest automatic priming effects do not solely account for RT-

related conflict adaptation effects, as such effects persisted in both control and participants with

TBI when repetition of color-naming trials were removed. The conflict adaptation effect present

for error rates when pooled across control and participants with TBI was diminished when

repetition trials were removed. This may suggest errors are more sensitive to repetition priming

effects than RTs; however, the initial findings of conflict adaptation effects in the error rate data

were tenuous and not significant for either the control or participants with TBI alone. Thus, the









reduction in the number of trials contributing to the conflict adaptation effects may have been

sufficient to reduce the previously significant effect.

Largely consistent with Experiment 1, correlations between two different measures of

deficit awareness and behavioral (RT) and electrophysiological (N450, conflict SP)

manifestations of cognitive control (specifically conflict processing) were not significant. As

noted above, the lack of association may be due to the difficulties in measurement of deficit

awareness (i.e., using absolute values with the FrSBe concordance score). In addition, the lack of

differentiation between participants with TBI and their control counterparts for both RT and ERP

measurements suggests the current sample of participants with TBI may not be exhibiting the

cognitive control deficits that might be associated with deficit awareness. The absence of strong

associations between deficit awareness and error-related ERP components in the previous study

and behavioral and ERP indices of conflict processing in the current study suggests that the

hypothesis of deficit awareness corresponding with declines in evaluative control mechanisms

may not be correct. Future research utilizing improved measures of deficit awareness is clearly

required to adjudicate among these possibilities.

Limitations specific to the current study should be considered. First, while we were able

to examine sequential trial conflict adaptation effects, the task employed limited our ability to

examine post-error strategic adjustments (as noted in Experiment 1). As post-error strategic

adjustments have, similar to the conflict adaptation effect, been taken to reflect participants' top-

down adjustments in performance strategy, perhaps reflecting the dynamic interplay between

ACC-mediated evaluative and dlPFC-mediated regulative processes (Botvinick et al., 2004;

Kerns et al., 2004), the convergence of information from the two measurements would

strengthen current findings. Next, due to the complications associated with examining









individual-trial ERPs (i.e., low signal-to-noise ratio in the absence of signal averaging), ERP data

examining conflict adaptation effects were reduced by inning individual trials into epochs based

on previous and current trial congruency. Epochs were then averaged for each participant and

statistical values obtained on these averages. For behavioral data, in contrast, RT and error rate

data for previous and current trial congruencies were calculated on an individual trial level. Thus,

it is possible that the averaging of the sequential trial data may have obscured potentially

meaningful findings. In addition, we were unable to examine potentially meaningful associations

between components of cognitive control. For example, Kerns et al., (2004) in their fMRI

examination of conflict adaptation effects, used ACC activity on previous trials to predict dlPFC

activity levels on subsequent trials and vice-versa. Our inability to examine single-trial data

reliably due to the limitations inherent in the ERP methodology prevented such examination

between, for example, N450 and conflict SP amplitude across sequential trials.

In summary, the present findings indicate behavioral conflict adaptation effects are

similar for participants with heterogeneous TBI and their control counterparts. Findings, in

concert with previous studies that showed intact conflict adaptation effects in groups with known

cognitive control deficits but no direct lesions to the ACC (di Pellegrino et al., 2007; West &

Moore, 2005), may suggest direct insult to ACC- or other dlPFC-mediated cognitive control

mechanisms are necessary for impaired conflict adaptation processes. A tonic conflict SP

differentiated incongruent from congruent trials, but failed to show consistent conflict adaptation

effects. The N450 component did not differentiate congruent from incongruent trials. Thus, in

the current study, ERPs were not a sensitive measure of the conflict adaptation effect.









Table 3-1. Mean RT (Standard Deviation) for congruent (C) and incongruent (I) trials as a
function of previous trial congruency. Left columns reflect all trials, including color
repetitions. Right columns reflect mean RTs with color-naming repetitions excluded.
Previous C Previous I Previous C Previous I
Group Current Current Current Current Current Current Current Current
C I C I C I C I
TBI 719.1 924.5 723.7 873.1 656.3 843.8 666.5 711.63
(184.3) (236.0) (175.7) (218.7) (196.1) (230.3) (159.5) (162.2)
Control 583.7 741.6 601.5 725.2 524.4 695.9 552.6 631.7
(70.1) (139.2) (74.2) (136.7) (66.0) (154.7) (76.0) (125.9)

Table 3-2. Mean percent errors (Standard Deviation) for congruent (C) and incongruent (I)
trials as a function of previous trial congruency. Left columns reflect all trials,
including color repetitions. Right columns reflect percent errors with color repetitions
excluded.
Previous C Previous I Previous C Previous I
Group Current Current Current Current Current Current Current Current
C I C I C I C I
TBI .04 .11 (.14) .04 (.05) .10(.18) .05 (.09) .11 (.15) .05 (.05) .11 (.17)
(.08)
Control .02 .05 (.02) .02 (.02) .05 (.04) .02 (.02) .06 (.03) .02 (.02) .05 (.06)
(.01)

Table 3-3. Mean difference scores (Standard Deviation) for RTs and error rates of the
incongruent (I) minus congruent (C) difference. Left columns reflect all trials,
including color repetitions. Right columns reflect trials with color repetitions
excluded.
All trials including repetitions Color repetitions excluded
Controls TBI Controls TBI
Response time (RT)
I- C difference
Previous trial congruent 157.9 (76.0) 205.4 (146.5) 149.6 (64.7) 203.9 (.130.0)
Previous trial incongruent 123.7 (80.9) 149.4 (99.3) 137.7 (83.3) 173.8 (129.0)
Error rate
I- C difference
Previous trial congruent .04 (.03) .07 (.07) .04 (.03) .06 (.07)
Previous trial incongruent .03 (.04) .07 (.13) .03 (.06) .07 (.13)










Table 3-4. Mean ( Standard Deviation) ERP amplitude ([tV) data for the N450 and conflict SP
components. Left columns reflect all trials, including color repetitions. Color
repetitions are not included in right column data. Differences represent the
incongruent (I) minus congruent (C) difference.
Controls TBI Controls TBI
Amplitude (pV) Amplitude (pV)
N450
Congruent .51(2.5) .44 (1.7) .40 (2.3) .59 (1.8)
Incongruent .24 (2.6) .30 (1.6) .12(2.7) .40 (2.0)
Conflict SP
Congruent .40 (1.7) .36 (1.5) .06 (1.5) .52 (1.4)
Incongruent 1.8(1.8) .84(1.4) 1.6(1.9) 1.2(1.9)
N450 I C difference
Previous trial congruent -.23 (1.0) -.25 (.86) -.07 (.80) -.11 (.75)
Previous trial incongruent -.45 (1.1) .04 (1.2) -.09 (1.3) -.46 (1.2)
Conflict SP I C difference
Previous trial congruent 1.6(1.7) .64 (1.4) 1.4(1.4) .71(1.6)
Previous trial incongruent 1.0(1.2) 1.1 (3.3) .86 (1.2) .48 (2.2)












Mean RTs for Control & TBI


Current Trial
* Congruent
O Incongruent


Control Control TBI TBI
Congruent Incongruent Congruent Incongruent
Previous Trial by Group


Figure 3-1. Mean reaction times (RTs) as a function of group, congruency, and current/previous
trial type. Error bars reflect standard errors of the mean.




Mean Error Rates for Control & TBI



0.13

0.11

2 0.09 Current Trial
Lw Congruent
S- 0.07 [ Incongruent


Control Control TBI TBI
Congruent Incongruent Congruent Incongruent
Previous Trial by Group


Figure 3-2. Mean error rates as a function of group, congruency, and current/previous trial type.
Error bars reflect standard errors of the mean.













Congruent
Control ___. Incongruert





TBI N4r



VVL-i. r-


ZOOms


0.04IIIIIIIsMe
0.04 (iNcMrns ep


Figure 3-3. Grand average ERP waveforms of stimulus-locked congruent and incongruent trials
averaged across fronto-medial electrode locations for the N450 (left) and top view of
the spline-interpolated current source density maps at 477ms (right).



Cao gruer
Control __. Incongruten






Conflict SP'





0.04 p1V/rVmrstep
Zorns


Figure 3-4. Grand average ERP waveforms of stimulus-locked congruent and incongruent trials
averaged across posterior electrode locations for the conflict SP (left) and top view of
the spline-interpolated current source density maps at 711ms (right).


2











Parietal Conflict SP


Control


TBI







200ms


C-C
C4I
"-C


14


Figure 3-5. Grand average ERP waveforms of stimulus-locked waveforms for congruent (C) and
incongruent (I) waveforms as a function of previous trial congruency. Thus, C-C
indicates a congruent previous trial and a congruent current trial, C-I indicates a
congruent previous trial and an incongruent current trial, etc.


Mid-Frontal N45D










N450 Mean Amplitude for Control & TBI


1.2

1

. 0.8

o 0.6
0
U n A


Ei


0.2


-0.2


LI
Control Control TBI Congruent TBI
Congruent Incongruent Incongruent
Previous Trial by Group


Figure 3-6. Mean N450 amplitude as a function of group, congruency,
type. Error bars reflect standard errors of the mean.


Current Trial
Congruent
SIncongruent









and current/previous trial


Conflict SP Mean Amplitude for Control & TBI


2

1.5
0
o
2 1

0.5

0


Control Control TBI
Congruent Incongruent Congruent
Previous Trial by Group


Current Trial
0 Congruent
O Incongruent


TBI
Incongruent


Figure 3-7. Mean conflict SP amplitude as a function of group, congruency, and current/previous
trial type. Error bars reflect standard errors of the mean.


I Ilr


tr I ~I


.


I N




















S6.00-


I--

2.00-





R Sq Linear = 0.172

0.00-

-2.50 0.00 2.50
Conflict SP Incongruent minus Congruent Difference (IV)


Figure 3-8. Scatter plot reflecting the relationship between SADI total score for TBI participants
and the parietal conflict SP incongruent minus congruent difference. Point in square
reflects the outlier participant.



120.00-



S9000-



S 60.00 -










-30.00 R Sq Linear = 0.236
-2 0 0.00 2.50
S 0.00-



LL- -30,00- ^R Sq Linear 0.236




-2.50 0.00 2.50
Conflict SP Incongruent minus Congruent Difference (pV)




Figure 3-9. Scatter plot reflecting the relationship between FrSBe other- minus self-rated total
score for TBI participants and the parietal conflict SP incongruent minus congruent
difference. Point in square reflects outlier participant.









CHAPTER 4
FEEDBACK UTILIZATION AND REWARD CONTEXT SENSITIVITY IMPAIRMENT
FOLLOWING SEVERE TRAUMATIC BRAIN INJURY

Feedback processing is an important aspect of evaluative control and is critical for

appropriate decision-making. Indeed, many rehabilitation protocols following traumatic brain

injury (TBI) utilize feedback via reinforcement and reward to influence behavior and facilitate

recovery; however, previous studies suggest survivors of severe TBI demonstrate impairments in

feedback contingency utilization and sensitivity. The precise neurobiological mechanisms

underlying these deficits have not been thoroughly explored, but can be examined using the

'feedback-related negativity' (FRN)-an event-related potential (ERP) component evoked

following performance or response feedback (e.g., whether a monetary reward is obtained) with

a larger FRN following unfavorable than favorable outcomes-particularly when unfavorable

feedback occurs in the context of high reward probability. We examined ERPs elicited by

favorable (monetary gain: 'reward') and unfavorable (no monetary gain: 'non-reward') feedback

during a guessing task where probability of reward outcome was manipulated in a subset of

survivors of severe TBI and demographically-matched healthy participants. Consistent with

previous findings, healthy control participants showed larger amplitude FRN to non-reward

feedback and the largest amplitude FRN following a non-reward when reward probability

context was greatest. In contrast, FRN in severe TBI survivors did not significantly differentiate

non-reward from reward trials and their FRN was largest to reward trials in the low reward

probability context. Findings indicate an impaired evaluative control mechanism of feedback

processing and implicate an electrophysiological marker of impaired reward context sensitivity

following severe TBI.









Introduction

The previous studies indicate survivors of severe traumatic brain injury (TBI) show

deficits in the evaluative processes of monitoring and comparing performance with internal

goals. Feedback processing, a critical component of evaluative control utilized in the assessment

of actions and the adjustment of performance to these outcomes, may also be impaired following

severe TBI. Indeed, TBI survivors frequently exhibit a constellation of characteristics that

include failure to evaluate and adjust behavior to feedback/performance (Larson et al., 2006a),

and decrements in their ability to respond adaptively to the consequences of their actions or

responses (Bechara et al., 2000; Bechara et al., 1996; Schlund, 2002a, 2002b; Schlund et al.,

2001; Schlund & Pace, 2000) leading to risky decision-making (Grafman et al., 1996; Oddy et

al., 1985; Tateno et al., 2003) and impaired goal-directed action (Shallice & Burgess, 1991).

Such sequelae of injury lead not only to deficits in essential cognitive activities, but also poor

learning/re-learning of socially appropriate behaviors, deterioration of interpersonal

relationships, and ultimately poor rehabilitation outcomes and decreased rates of return to

employment (Weddell et al., 1980).

Many of the aforementioned difficulties result from decreased sensitivity to stimulus-

response contingencies (Bechara et al., 2000; Bechara et al., 1996; Salmond et al., 2005; Schlund

et al., 2001; Schlund & Pace, 2000). While brain injured individuals may remain sensitive to

certain consequences, they fail to adaptively discriminate among the relevant response-

consequence relations (i.e., contingencies), which likely accounts for some increases in risky

behaviors, as well as problems in skill acquisition and adaptive choice (Schlund, 2002a). For

example, Salmond et al., (2005) found impaired decision-making and increased impulsive

responding when head injury survivors performed a computerized gambling task. These results

were consistent with other accounts of increased levels of impulsivity associated with









dysfunction of the frontal lobe (Fuster, 1997; Miller, 1992). Although there is substantial

heterogeneity among TBI survivors, there is typically widespread damage to white matter tracts

(Meythaler et al., 2001) and cortical regions involving the orbitofrontal cortex and temporal

lobes (Levin et al., 1987). Impulsive or disinhibited behavior has been linked to orbitofrontal

(Bechara, 2004; Rolls, 2000) and ventromedial prefrontal (Bechara et al., 1994) lesions in

humans. More specifically, the actions of individuals with injuries to the prefrontal cortex show

reduced sensitivity to the consequences of their response and tend to respond preferentially to

stimuli that are associated with the possibility of an immediate reward, without regard to the

context of previous feedback or future contingencies, resulting in a form of "myopia for the

future" (Bechara et al., 2000, p. 2198).

There remains a paucity of data on the neural correlates of impaired feedback contingency

sensitivity following TBI, despite the fact feedback-based treatments (e.g., reward) are

frequently employed in the rehabilitation setting. Our understanding of the neurocognitive

processes related to feedback evaluation and monitoring has been enhanced through examination

of the scalp-recorded event-related potential (ERP) known as feedback-related negativity (FRN).

The FRN is a negative-deflecting component with medio-frontal scalp distribution that peaks

approximately 250ms following presentation of performance or reward feedback and shows

greater amplitude following unfavorable than favorable outcomes (Gehring & Willoughby, 2002;

Ruchsow et al., 2002). The FRN has been interpreted as an electrophysiological reflection of

whether a desired reward has been achieved, as evidenced by Hajcak and colleagues' (2006)

study of healthy adults that identified a dichotomous FRN response to multiple, graded forms of

feedback, with the smallest negativity following positive outcomes and largest negativity

following negative or neutral outcomes. Holroyd and colleagues' (2006) study similarly









demonstrated neutral feedback elicits FRN amplitudes similar to cost/punishment, suggesting

non-reward stimuli are processed as feedback that is inconsistent with the prevailing reward

context. Holroyd and Coles (2002) propose the FRN is produced when an error processing

system detects events that are worse than expected. More specifically, their reinforcement

learning theory of the error-related negativity (RL-ERN) proposes the FRN, like its response

error-related analogue known as the error-related negativity (ERN), is a reflection of a

dopaminergic negative feedback reinforcement-learning signal produced when response

outcomes are worse than expected. Studies of the FRN assumed participant expectation through

manipulation of reward probability, rather than direct assessment via questionnaire or otherwise.

Thus, these studies of the FRN and the RL-ERN theory assume knowledge of participant

expectation and, therefore, may be better conceptualized as studies of reward context rather than

reward prediction/expectation, with larger FRN occurring when a high reward probability

context is violated by the presentation of a non-reward stimulus.

Consistent with the RL-ERN theory, source localization studies of the FRN broadly

implicate areas of the mesial-frontal cortex, specifically the anterior cingulate cortex, as the

primary neural generator of the FRN (Gehring & Willoughby, 2002; Holroyd & Coles, 2002;

Ruchsow et al., 2002). One paradigm that has been employed to examine the FRN is a type of

guessing task (Holroyd et al., 2003; Ruchsow et al., 2002; van Meel et al., 2005). In these tasks,

participants are presented with several response options and told there is a reward associated

with one of the options. Following participant response, feedback indicating whether the

response was correct (reward obtained) or incorrect (no reward) is presented. Unknown to the

participants, feedback is presented in a pseudo-random fashion. In the high reward probability

condition, participants received positive feedback on 75% of trials, while in the low reward









probability condition participants received negative feedback on 75% of trials. This manipulation

of feedback establishes distinct forms of reward context, which are dependent on whether a

reward is likely or unlikely to be achieved. According to the RL-ERN theory (Holroyd & Coles,

2002; Holroyd et al., 2003), non-reward feedback in a low reward probability condition would be

associated with a small FRN because feedback is consistent with the reward context, while non-

reward feedback in a high reward probability condition would lead to a larger FRN because a

probability context violation has been registered by the reward monitoring system. Such

guessing paradigms also allow for study of feedback-related neural processing independent of

participant performance (van Meel et al., 2005), which would likely be impaired relative to

healthy controls following a severe head injury, and ensures that response-reinforcement

contingencies do not confound the FRN response to feedback.

The present study utilized the FRN to examine reward context sensitivity in a subset of

severe TBI survivors and healthy controls. We predicted that findings in control participants

would replicate those of previous studies using the same guessing paradigm described above

(Holroyd et al., 2003), with increased amplitude FRN following non-reward feedback when

averaged across conditions and largest FRN following non-reward feedback when reward

probability is high. In participants with severe TBI, we predicted FRN amplitude would not

differ as a function of feedback condition due to deficits in reward context sensitivity.

Methods

Participants

Study enrollment consisted of a subset of the participants who participated in the previous

studies. Initial enrollment included 11 TBI and 11 healthy control participants. Data from one

TBI participant were excluded due to too few artifact-free trials to compute reliable average ERP

epochs (< 25 trials per condition). Thus, the final sample included ten right-handed severe TBI









participants between the ages of 18 and 42 years (3 female; M=26.40 years, SD=8.21) and 11

right-handed, age- and education-matched healthy control participants (4 female; M=27.18 years,

SD=11.10; range=18-49 years). Demographic characteristics of TBI and control participants are

provided in Table 4-1. Similar to the previous studies, TBI participants were recruited from two

Northern Florida trauma and rehabilitation hospitals; control participants were recruited via flyer

and advertisement from the local community. All participants provided written informed consent

according to procedures established by the University of Florida Health Science Center

Institutional Review Board and were compensated for their participation.

As in the previous studies, TBI severity was determined from medical record review of

lowest post-resuscitation Glasgow Coma Scale (GCS) score (Teasdale & Jennett, 1974), with

severe TBI defined as a GCS score <9. Neurological indices, including neuroradiological

findings taken from acute computerized tomography (CT) scans, duration of loss of

consciousness (LOC), and duration of post-traumatic amnesia (PTA), were also acquired from

medical record review or, when LOC and PTA information were not available in medical

records, from structured participant and significant other interview (King et al., 1997; McMillan

et al., 1996). LOC and PTA data confirmed all patients met criteria for severe TBI as

traditionally defined by LOC>6 hours and/or PTA>7 days (Bigler, 1990; Bond, 1986;

Gerstenbrand & Stepan, 2001; Lezak et al., 2004).

All participants were screened for major psychiatric disorder using the Mental Health

Screening Form-Ill (MHSF-III; Carroll & McGinley, 2000, 2001). Potential participants were

excluded from the study for the following reasons: history of psychotic or bipolar disorder,

learning disability, alcohol or substance abuse within six months prior to testing, other acquired

brain disorders (e.g., epilepsy, stroke), inpatient psychiatric treatment predating brain injury,









clinically-significant depression or anxiety within two years prior to injury, or color-blindness as

measured by the Ishihara pseudo-isochromatic color plates (Clark, 1924). Participants with

language comprehension deficits or uncorrected visual impairments were also excluded.

Injury characteristics and neuroradiological findings for this subset of TBI participants are

presented in Table 4-2. TBI participants were at least six months post-injury, with the exception

of one who was functioning well and desired to complete the study before returning to

employment. No participants were engaged in legal action at the time of the study. Participant

groups were well matched for age, t(19)=.18, p>.85, and education, t(19)=.79, p>.43. TBI

participants endorsed significantly more depressive symptoms, as measured by the Beck

Depression Inventory-2nd Edition (BDI-II; Beck, 1996), t(19)=3.15, 2<.01; however, no

individual scores met common clinical cut-offs for depression (BDI-II>21) and mean scores for

both groups were well within normal limits-not meeting criteria for even mild levels of

depressive symptomatology (BDI-II>13; see Beck, 1996). Groups did differ on their report of

apathy symptoms on a modified version of the Apathy Evaluation Scale (Marin, 1991; Marin et

al., 1991; Starkstein et al., 1992), t(20)=2.22, p<.04, with TBI participants endorsing significant

more symptoms. TBI participants endorsed higher levels of state, t(19)=2.15, p<.05, but not trait

anxiety symptoms, t(19)=1.10, p>.29, as measured by the State-Trait Anxiety Inventory (STAI;

Speilberger et al., 1983).

Experimental Task

We utilized the experimental task employed by Holroyd et al., in their 2003 investigation

of reward context and the FRN. In this task, participants viewed four circles in a row (0000)

and were told that one of the circles contained a reward of five cents that would be summed

throughout the task and provided in addition to their hourly compensation. Circles remained on

the screen until the participant responded by pressing one of four keys placed directly below









each circle on a response pad. A black screen was then presented for 500ms, followed by the

feedback stimulus that remained on the screen for 2000ms. Reward feedback consisted of four

dollar signs in a row ($$$$), while non-reward feedback consisted of four Xs (XXXX). The

interstimulus interval between the feedback stimulus and the subsequent trial was 500ms. All

stimuli during the task were printed in yellow font on black background, visually centered, 0.60

high and 5.00 wide, and appeared on a 15 inch computer monitor -40cm from the participant's

head.

Participants were instructed that presentation of a reward feedback stimulus indicated they

had received five cents, while presentation of a non-reward feedback stimulus indicated they

received no money for that trial and that the goal of the task was to respond in a manner that

would maximize their earnings. Unknown to the participants, feedback stimuli were presented

randomly according to two separate reward probability conditions. In the high reward probability

condition, participants received positive feedback on 75% of trials, while in the low reward

probability condition participants received positive feedback on only 25% of trials. Each

condition consisted of one block of 200 trials. For example, participants presented with 200 trials

during the high reward probability block received reward ($$$$) feedback on 150 trials (75%),

while 50 trials (25%) showed non-reward feedback (XXXX) for a sum of $7.50 earned. The

probability of reward feedback was reversed in the low reward probability block. Order of block

presentation was counterbalanced across participants. Following completion of the first block,

participants were told to take as much time as they desired to relax, and the amount of money

they had achieved was displayed on the computer monitor (either $2.50 or $7.50). After

completing the task, participants were debriefed, and all were provided with $10 additional









compensation. All participants responded to all trials and were awarded the same amount of

compensation.

Electrophysiological Data Recording and Reduction

Electroencephalographic activity was recorded from 64 scalp sites using a geodesic sensor

net and Electrical Geodesics, Inc., (EGI; Eugene, Oregon) amplifier system (20,000 gain,

nominal bandpass=. 10-100 Hz). Electroencephalogram data were referenced to Cz and digitized

continuously at 250Hz with a 16-bit analog-to-digital converter. A right posterior electrode

served as common ground. Electrode impedance was maintained below 50 kM. Eye movement

and blink artifacts were corrected using a spatial filtering method (Berg & Scherg, 1994; Ille et

al., 1997, 2002). Data were segmented off-line and single trial epochs with voltages that

exceeded 100b V or transitional (sample-to-sample) thresholds of 75 V were discarded.

Electroencephalogram data were re-referenced to an average reference (Bertrand et al., 1985),

and digitally low-pass filtered at 15 Hz.

Individual-subject feedback-locked ERPs were derived separately for reward and non-

reward trials for the two different feedback blocks (high and low reward probability) from 200ms

before- and 600ms following-feedback and were baseline corrected using the 200ms pre-

feedback stimulus window. The FRN was quantified at electrode FCz. This electrode location

was chosen because the FRN was largest there upon examination of grand-averaged waveforms

and based on previous studies showing the FRN is maximal at this medio-frontal site (Hajcak et

al., 2006; Holroyd et al., 2006; Holroyd et al., 2004; Holroyd et al., 2003).

In light of previous findings that measurement of the FRN can be confounded by potential

overlap with other components (e.g., P300; Holroyd et al., 2004; Holroyd et al., 2003), initial

analyses of the FRN were completed by calculating difference waves subtracting the ERP









associated with reward feedback from the ERP associated with non-reward feedback. The "non-

reward minus reward" difference waves were also calculated for frequent and infrequent

stimulus presentation contexts. The FRN was quantified as the maximum negative amplitude of

the difference wave between 125ms and 325ms post-feedback presentation.

We next employed the peak-to-peak scoring approach used by Holroyd et al., (2003) and

others (Hajcak et al., 2006; Holroyd et al., 2006; Yasuda et al., 2004). Specifically, FRN peak-to-

peak amplitude was defined as the difference of the maximum value between 125ms and 325ms

following feedback onset and the most negative point between this maximum and 325ms post-

feedback presentation. One control participant had no measurable negative deflection, thus the

FRN amplitude for this participant was scored as zero.

To assess the potential for generalized ERP amplitude decrements or latency shifts in TBI

participant ERP waveforms, N1 amplitude and latency data was extracted as the amplitude and

latency of the first peak negative deflection in the ERP between 50 and 200ms for both reward

and non-reward trials at posterior electrode site 38 (location of maximum N1 amplitude).

Data Analysis

Median RTs as well as ERP (N1, FRN) amplitude and latency data were analyzed

separately using repeated-measures analyses of variance (ANOVAs). The Huynh-Feldt epsilon

adjustment was applied for ANOVAs with more than two levels of a within-subject factor and

partial-eta2 (l2) reported as a measure of effect size. Initial ANOVAs for RT and feedback-

related ERP activity included group (TBI, control) as the between-subjects factor and feedback

probability condition (high, low reward probability) as the within-subject factor. Planned

comparisons were used to decompose main effects and interactions and to examine the feedback









factor separately within the high and low reward probability blocks. Cohen's-d effect sizes

(Cohen, 1988) were calculated for condition-related effects.

Results

Behavioral Data

Median RTs for each feedback type in the high and low reward probability conditions are

presented in Table 4-3. A Group x Feedback ANOVA showed no significant main effect of

reward condition, F(1,19)=2.46, p>. 14, r2=. 11, no Group x Feedback interaction, F(1,19)=.38,

p>.38, r2=.04, and no significant main effect of group, F(1,19)=1.71, p>.21, r2=.08.

ERP Data

A total of 12% of trials were rejected from averaging due to artifact in the EEG. Control

and TBI participants did not differ on number of trials retained for averaging under either high or

low reward probability conditions, ts(19)<.96, es>.35. Per participant, reward waveforms

contained an average of 180 (SD=+10; range=166 to 193) trials for controls and 174 (SD=+17;

133 to 193) trials for TBI participants, while non-reward waveforms contained an average of 179

(SD=+14; 151 to 198) trials for controls and 170 (SD=+25; 108 to 197) trials for TBI

participants.

N1 amplitude and latency. A Group x Feedback ANOVA on feedback-locked grand

average ERP waveforms was conducted to examine the possibility of generalized amplitude

decrements or latency shifts for TBI participants. Results of the analysis of N1 amplitude

indicate no main effect of reward condition, F(1,19)=1.13, p>.30, 1 =.06, no Group x Feedback

interaction, F(1,19)=.23, p>.63, ai=.01, and no main effect of group, F(1,19)=1.84, p>.19,

r12=.09. Latency data were similar, with no significant Group x Feedback interaction,

F(1,19)=2.12, p>.16, 2=.21, and no main effect of group, F(1,19)=1.39, p>.25, &2=.07. Thus,









data suggest that there is not a significant generalized amplitude decrement or latency shift in the

ERPs of the TBI participants relative to healthy controls.

FRN difference wave analysis. Feedback-locked grand average ERP waveforms for

reward and non-reward conditions and accompanying non-reward minus reward difference

waves are presented collapsed across reward context conditions in Figure 4-1 and as a function

of feedback frequency (high or low reward probability) in Figure 4-2. Spline-interpolated scalp

voltage maps of the difference waves are presented in Figure 4-3, with FRN difference wave

amplitude data shown in Table 4-4. As anticipated, feedback-locked ERPs showed an FRN

occurring at a mean latency of 261ms in control and 233ms in TBI participants. Planned

comparisons of non-reward minus reward difference waves showed no differences between

groups, t(19)=.72, p>.47, d=.32. Subsequent between-groups analyses on FRN difference waves

as a function of frequent and infrequent feedback presentation also yielded no group differences

on either frequent, t(19)=.93, p>.37,d=.41 or infrequent, t(19)=-.71, p>.48, d=.30, stimulus

presentation.

As evident in Figures 4-1 and 4-2, difference waves are insensitive to equivalent changes

across feedback conditions. For example, the positivity following reward trials in the low reward

probability block for TBI participants is increased in direct proportion to the slight negativity

following non-reward trials (FRN)--leading to the appearance of a large negative difference. In

contrast, the amplitude of the negativity (FRN) at approximately the same latency for control

participants in the low reward probability block is much greater than the positivity. Thus, the

finding of equivalent FRN difference waves between TBI and control participants is spurious

and confounded by the variations in waveform morphology between-groups. Consequently,

although unable to make direct conclusions about the FRN without taking into account the









possibility of component overlap, we conducted peak-to-peak analyses to directly examine the

negative deflection of the FRN.

FRN peak-to-peak analysis. FRN component amplitude and latency data are presented in

Table 4-4. A Group x Feedback ANOVA yielded a non-significant main effect of feedback

condition, F(1,19)=1.84, p>.19, 1 =.09. More importantly, there was a significant Group x

Feedback interaction, F(1,19)=9.76, 2<.006, r2 =.34. Planned contrasts revealed that the FRN

was significantly larger following non-reward than reward feedback in controls, t(10)=2.64,

p<.025, d=.67, but not TBI participants, t(9)=-1.85, p>.10, d=.25. The interaction was found in

the absence of an overall main effect of group on FRN amplitude, F(1,19)=0.19, p>.66, 12=.01,

further suggesting the effect is not due to an overall attenuation of ERP component amplitudes in

TBI participants.

After verifying the two groups exhibited different neural responses to feedback, we

conducted a series of planned contrasts to test the specific hypotheses that: 1) control participants

would show the largest FRN in response to non-reward feedback when a reward was expected

(i.e., non-reward feedback in the high reward probability block); 2) FRN amplitude would not

differ as a function of feedback condition when non-reward stimuli were predicted (i.e., during

the low reward probability block); and, 3) FRN amplitude would not differ as a function of

condition during the high and low reward probability blocks in TBI participants due to

impairments in reward context sensitivity. Paired-samples t-tests conducted separately for each

group confirmed these hypotheses, with control participants showing significantly larger FRN

amplitude to non-reward stimuli during the high reward probability block, t(10)=2.40, p<.03,

d=.80; control participants not differentiating between reward and non-reward feedback during

the low reward probability block, t(10)=.03, p>.90, d=.01; and, TBI participants showing no









differences between feedback conditions in the high reward probability block, t(9)=.52, p>.60,

d=. 12. Interestingly, TBI participants showed significantly larger FRN amplitude to reward

stimuli during the low reward probability block, t(9)=2.54, p<.03, d=.47. Figure 4-2 presents the

grand average waveforms as a function of feedback type and reward probability condition for

TBI and control groups.

FRN latency. A Group x Feedback ANOVA yielded no significant main effects or

interactions on FRN latency (ps>. 18).

Discussion

Results of the current study largely supported our primary hypotheses regarding impaired

neural processing of reward and non-reward stimuli following severe TBI. First, TBI participants

demonstrated generally reduced feedback-related ERP differentiation between reward and non-

reward conditions relative to healthy control participants. That is, TBI participants showed

feedback-related ERP activity, but the amplitude of this activity did not differentiate between

reward and non-reward feedback. In contrast, control participants showed significantly larger

FRN amplitude following non-reward relative to reward trials. The results in control participants

replicate previous studies of reward feedback on guessing tasks (Holroyd et al., 2003; Ruchsow

et al., 2002), while results in TBI participants suggest that these survivors are largely responsive

to feedback, but do not generally differentiate reward and non-reward contingencies at the

electrophysiological level. Moreover, the finding that the control and TBI groups did not differ

on N1 amplitude or latency, or in the overall amplitude of feedback-related ERPs, provides

evidence that the feedback-related differences do not simply reflect a more generalized ERP

decrement in the TBI survivors.

Second, TBI and control participants differed in their sensitivity to reward context.

Consistent with the hypothesis that the FRN is largest when reward-probability context is high









but a non-reward is obtained (Holroyd & Coles, 2002; Holroyd et al., 2003), control participants

showed the largest FRN to non-reward stimuli in the high reward-probability context, but did not

differentiate between reward conditions in the low-reward probability context. TBI participants

showed the opposite pattern of findings, with no differentiation between reward and non-reward

trials in the high reward-probability context, but significantly larger FRN following reward

stimulus presentation in the low reward-probability context. This finding was unanticipated, as

FRN amplitude in TBI participants did not generally differentiate reward and non-reward

feedback and previous studies show FRN amplitude is largest when rewards/goals are not

obtained, rather then when feedback indicates reward attainment (Hajcak et al., 2006; Holroyd et

al., 2004). This reversal in the direction of the reward-context effect on FRN in TBI participants

could reflect the possibility that obtaining a monetary reward is more meaningful and less

expected in TBI participants. That is, it may be that monetary incentives had a stronger

motivating effect on TBI participants as they were largely unemployed or on disability at the

time of the study. More likely is the possibility that survivors of severe TBI show generally

altered reactivity to feedback and change in reward context. As a whole, the current findings that

TBI participants did not respond differentially to non-reward trials in the high reward-probability

context and that FRN amplitude increased when a reward was presented during low reward

probability blocks provides support for the hypothesis that reward feedback processing is

impaired relative to control participants. Notably, between-groups FRN differences were found

in the absence of significant effects of RT or frequency of feedback presentation (i.e., frequent

vs. infrequent feedback within reward or non-reward blocks), suggesting speed of

response/reward presentation and frequent/infrequent feedback presentation are not underlying

reasons for the current findings.









To the author's knowledge, this is the first study to expose deficiencies in reward-context

sensitivity in participants with TBI. That is, neural reflections of reward processing in both high

and low reward probability conditions were not differentiated in TBI participants and did not

follow the pattern of results in control participants. Findings fit well into a burgeoning literature

that implicates performance-monitoring deficits likely associated with medial-frontal

cortex/ACC dysfunction following severe TBI (see General Discussion below). Results are also

consistent with studies of individuals who have sustained damage to neuroanatomical structures

strongly implicated in reward-processing, such as the ventral striatum, ventromedial/orbitofrontal

cortex, and limbic system (Bechara et al., 2000; Bechara et al., 1996) that show impaired

sensitivity to reward contingencies. Furthermore, recent studies suggest altered striatal dopamine

activity following head injury contributes to deficits in cognitive performance (Wagner et al.,

2005) and dopamine agonists have been shown to improve some aspects of cognitive

performance following TBI (Kaelin et al., 1996; McAllister et al., 2004; Napolitano et al., 2005;

Plenger et al., 1996). Thus, future research should examine the role of the dopaminergic system

in reward context sensitivity deficits following TBI, as well as the possible pharmaco-therapeutic

role of dopamine agonists (c.f., McAllister et al., 2004).

Results of this study suggest several implications for clinical application and future

research. First, this study adds to the literature by suggesting participants with TBI show reduced

sensitivity to reward context-a key component to learning (and re-learning) of appropriate

behaviors in the rehabilitation setting. Thus, clinicians should be vigilant to these decrements and

realize learning of appropriate and non-risky behaviors and decision-making strategies may be

difficult and time-consuming. Second, results provide insight into the neural mechanisms

underlying previous findings of impaired stimulus-response contingencies in behavioral studies









by demonstrated alterations in the neurobiological reflections of reward context sensitivity

following TBI. Thus, a potential future line of research might examine the neurobiological

instantiation of reward context processing with response-based contingencies as well as reward

context utilization changes following rehabilitation targeting feedback processing, contingency-

utilization skills, and risk-taking behaviors. Finally, results suggest a continued need for

emphasis on decision-making skills in rehabilitation. Few empirically supported treatments

currently target such deficits, though studies have begun to examine this domain (Levine et al.,

2000; Park et al., 2003). Utilization of cognitive neuroscience methods (e.g., ERPs, functional

magnetic resonance imaging) may aid in elucidating the mechanisms and corroborating the

efficacy of potential rehabilitation strategies.

Findings of the current study must be considered within the context of potential limitations

and alternative explanations. First, the small sample size limits the extent findings can be

generalized to a larger population of TBI survivors. Second, the current study employed a

guessing paradigm where feedback stimuli were presented in a pseudo-random fashion, rather

than according to participant performance; that is, feedback was not response contingent. Thus,

the task paradigm precludes our ability to examine behavioral data and strategic adjustments

critical to evaluative control following feedback presentation. In addition, the ambiguous results

of the difference-wave analyses and utilization of peak-to-peak measurement leave open

questions regarding the possibility of component overlap and alternative contributions to FRN

differences between groups (e.g., potential overlap of the P300 or N2 components). Third, it is

possible that individuals with abnormal reward processing are more likely to suffer a TBI. Thus,

group differentiation of the FRN could be due to pre-existing differences, rather than a direct









consequence of TBI. Finally, groups differed on levels of depression, anxiety, and apathy. Each

of these factors may have contributed to reduce FRN amplitude in participants with TBI.

Present findings implicate impaired evaluative control mechanisms in survivors of severe

TBI. The finding of an electrophysiological marker of impaired reward context sensitivity adds

to the growing body of literature suggesting that, compared to control participants, severe TBI

survivors have difficulty monitoring their performance and environment. This study also places

further emphasis on the need for continued use of cognitive neuroscience methods to increase

understanding of the neurobiological bases of TBI-related dysfunction and provide a strong

foundation for the potential development and validation of rehabilitation treatments.











Table 4-1. Mean (+ Standard Deviation) demographic data for control and TBI participants
Control TBI
(n = 11) (n_= 10)
# males/# females 7/4 7/3
Age (years) 27.2(11.1) 26.4 (8.2)
Education (years) 14.1(1.6) 13.5 (1.8)
BDI-II 2.8 (2.8) 9.6 (6.5)
Apathy evaluation scale 11.0 (5.2) 7.0 (3.0)
STAI-state 26.1 (4.8) 30.9 (5.5)
STAI-trait 29.5 (6.4) 32.7 (7.3)

Definition of abbreviations: BDI-II = Beck Depression Inventory-II; STAI= State-Trait Anxiety
Inventory










Table 4-2. Injury characteristics and neuroradiological information for TBI participants.
Age Sex Etiology GCS LOC PTA Months Neuroradiological Findings
(yrs) (days) (days) Post
Injury


21 M MVA


20 F MVA



25 F MVA

22 F Rollover
MVA


21 M MVA
35 M Collision
with wall


36 M Motorcycle
accident

18 M MVA



42 M MVA

21 M Motorcycle
accident


3 42 90 20 Right frontal subdural hematoma;
multiple skull fractures
3 14 16 19 Right frontal contusions; shear
injury to left frontoparietal lobe;
subarachnoid hemorrhage with
interpeduncular cistern
3 30 21 17 Left occipital condoyle fracture;
subdural hematoma
3 7 21 19 Left supraorbital hematoma; right
frontal hematoma; bifrontal
contusions-left greater than
right
3 41 50 6 Unavailable
8 7 N/A 15 Nondepressed right temporal
bone fracture leading to subdural
hematoma; blood on right
thalamus and left internal capsule;
small uncal herniation
3 30 36 4 Small bilateral intraventricular
hemorrhages; no additional
findings
7 4 31 12 Bilateral frontal contusions--
more prominent right frontal;
effacement of cortical sulci and
basal cisterns
3 10 120 6 Intraventricular hemorrhage,
basilar skull fracture
3 12 33 18 Right temporal contusions; right
frontal subarachnoid hemorrhage;
microhemorrhages along gray-
white junction of left hemisphere
and right parietal lobe


26.4 -- 3.9 19.7 46.4 13.6 --
(8.2) (1.9) (14.6) (35.4) (6.1)
Note: Last row is Mean (+ Standard Deviation) values. LOC and PTA are shown in days unless
otherwise specified. Neuroradiological findings taken from medical record review of
neuroradiological reports from CT scans taken acutely after injury. MVA = Motor Vehicle
Accident; GCS = Glascow Coma Scale; LOC = Loss of consciousness; PTA = Post-traumatic
amnesia










Table 4-3. Mean (+ Standard Deviation) reaction times for control and TBI participants
Control (n = 11) TBI (n = 10)
Reaction Times (ms)
Non-Reward 474.7 (231.4) 731.3 (577.5)
Reward 454.9 (252.3) 659.4 (445.8)


Table 4-4. Mean (+ Standard Deviation) non-reward minus reward difference wave ([tV)


Control


FRN difference
Frequent difference
Infrequent difference


(n= 11) TBI (n = 10)
Amplitude (pV)
-2.7(1.5) -2.2 (
-2.9(1.8) -2.2(
-2.1 (2.6) -2.8 (


Table 4-5. Mean ( Standard Deviation) peak-to-peak component amplitude ([tV) and latency
(ms) as a function of feedback condition for the FRN.
Control TBI Control TBI
Amplitude (pV) Latency (ms)
FRN
Reward -2.4 (1.7) -2.89 (1.9) 239.6 (35.5) 229.6 (34.8)
Non-reward -3.6(1.9) -2.42(1.7) 261.5 (26.1) 232.8 (41.6)
Frequent presentation
Reward -2.4 (1.6) -2.89 (1.9) 238.4 (37.1) 230.8 (33.5)
Non-reward -3.6(1.9) -2.46(1.7) 259.3 (28.2) 217.6(41.2)
Infrequent presentation
Reward -3.6(2.6) -3.22(1.6) 251.6(30.8) 239.6 (39.4)
Non-reward -4.0 (2.4) -3.09 (1.5) 266.9 (25.0) 249.6 (41.2)


:1.2)
1.7)
1.6)











Control


2pV 1 Non-Reward
L Reward
10lms Difference
Figure 4-1. Grand average ERP waveforms depicting feedback-locked reward and non-reward
activity as well as the non-reward minus reward difference wave at recording site FCz
for control (top) and TBI (bottom) participants. denotes approximate location of
FRN.


Frequent Presentation Infrequent Presentation

Control I






TBI





2pV Non-Reward
L Reward
100ms Difference
Figure 4-2. Grand average feedback-locked ERP waveforms showing reward and non-reward
activity as well as non-reward minus reward difference waves at recording site FCz
for the high frequency trials (e.g., reward trial in a high reward probability condition)
and low frequency trials (e.g., reward trial in low reward probability condition) in
control (top) and TBI bottom) participants. denotes approximate location of the
FRN.












Frequent Difference Infrequent Difference


Control


Adak





TBI








-2.SwV 0 2,6W


Figure 4-3. Spline-interpolated voltage maps of the non-reward minus reward difference wave at
280ms for control (top) and TBI (bottom) participants.









CHAPTER 5
GENERAL DISCUSSION

The previous chapters examined evaluative control processes following severe TBI.

Specific aims of these studies were to: 1) test the prediction that survivors of severe TBI show

impairments in their ability to detect errors and response conflict (i.e., when representations of

more than one response are simultaneously activated) and subsequently show decrements in their

ability to reactively adjust performance to adapt to changing task demands; 2) test the prediction

that survivors of severe TBI exhibit deficits in the evaluative control process of reward context

monitoring and, subsequently, show decrements in their ability to evaluate feedback and reward;

3) compare behavioral and neurobiological indices of evaluative control to measurements of

deficit awareness in TBI participants, with the prediction that larger magnitude evaluative

control deficits would be associated with poorer deficit awareness.

Findings indicate impaired electrophysiological manifestations of evaluative control

(including feedback processing) following severe TBI. The ERN, an ERP reflection of error- and

performance-monitoring, was attenuated in participants with TBI as was the conflict SP, an ERP

deflection thought to reflect regulative aspects of conflict processing. Similarly, the FRN, an

index of feedback context and monitoring, demonstrated generally reduced feedback-related

ERP differentiation between reward and non-reward contexts in participants with TBI.

Importantly, group-wise differences in these reflections of evaluative control were found in the

absence of differences in early sensory components of the ERP (i.e., P1 or Ni amplitude or

latency) and the absence of group main effects on ERP amplitudes--suggesting differences do

not simply reflect more generalized attenuations in ERP signatures following TBI. Given this,

the ERN, FRN, and potentially the conflict SP represent possible neurobiological markers of

impaired evaluative control following severe TBI.









While supporting our hypothesis that survivors of TBI exhibit impaired evaluative control

processes, the ERP results do not directly address critical questions regarding the source or

mechanism underlying the ERP manifestation of evaluative control dysfunction. Reduced-

amplitude ERP components may be due to a number of factors not directly reflective of an

underlying impairment in the process of interest. For example, signal averaging for creation of

ERPs is based on the assumption of across-trial time (and amplitude) invariance. It is

conceivable that participants with TBI exhibit greater variability in the latency of peak response

(i.e., "latency jitter"), violating this invariance assumption, and resulting in spuriously reduced-

amplitude ERP components. While methods exist for evaluating single-trial ERP data and

adjusting for latency jitter (e.g., Mocks et al., 1988; Picton et al., 1995; Woody, 1967), their

effectiveness is limited to large-amplitude ERP components (e.g., P300) and may not yield

reliable or valid effects for the smaller components examined in the present research. In addition,

the possibility of alterations in cortical geometry, volume, and electrical conductivity in the TBI

patient group (e.g., lesions, pooling blood, etc) may give rise to spurious amplitude reductions in

ERP component amplitudes. Specifically, the propagation or volume conduction of potentials to

the scalp surface, and therefore their scalp distribution, can be altered by the presence of injury-

related factors. These can result in altered amplitude or scalp distribution of the ERP,

consequently challenging the assumption that using identical measurement electrode sites across

the different groups will yield similar measurement sensitivity to the ERP components of

interest.

Another alternative explanation is that the current sample of participants with TBI is quite

heterogeneous, as are the majority individuals in the severe TBI population. Thus, the

heterogeneity of mechanism of injury, lesion location, and level of recovery post-TBI preclude









specific conclusions regarding lesion location or pathology and evaluative control deficits in the

current sample. Finally, many studies comparing neurologically-impaired participants with

healthy controls have difficulty with the interpretation of ERP results due to differences in

behavioral performance. For example, TBI participants had a higher number of errors included in

analyses of the ERN than control participants. This may lead to differences in signal-to-noise

ratio, potentially reducing or amplifying ERP components of interest.

Control and TBI participants did not differ on several behavioral (i.e., RT, error rate)

indices of evaluative control. On the Stroop task, participants with TBI did not commit more

errors than control participants nor did they commit disproportionately more errors on

incongruent trials. These findings were not completely unexpected. Seignourel et al., (2005)

utilized a cued version of the single-trial Stroop task to demonstrate error rate differences

between severe TBI participants and healthy controls were due to deficits in the ability to

maintain context information (i.e., whether the task was color-naming or word-reading) as

opposed to a more general deficit in inhibition of pre-potent response tendencies. Due to task

context being maintained throughout the current color-naming paradigm for the participants (i.e.,

the appropriate response was to name the color for all trials), the lack of differences between

groups provides further support for deficits in context-maintenance, rather than response

inhibition, following severe TBI.

More unexpected was the finding that, other than generalized slowing in participants with

TBI, groups did not differ on reactive conflict adaptation adjustments. While consistent with

other findings of non-ACC specific head trauma and older adult patient groups, the findings can

lead to questions regarding the heterogeneity of injury in the current sample and the specificity

of ACC-mediated cognitive control mechanisms (di Pellegrino et al., 2007). For example, some









TBI participants may have specific deficits in regulative function, but intact evaluative functions.

Others, in contrast, may have intact regulative control processes and impaired evaluative

processes. Examination of the data in group format, therefore, obscures our ability to look at

individual-specific deficits in cognitive control component processes. Future research that

capitalizes on the heterogeneity present in TBI samples by identifying clinically-meaningful

subtypes would be beneficial in elucidating the cognitive control deficits, but even more helpful

in the context of rehabilitation where rehabilitation techniques can be empirically tested and

tailored to improve specific deficits in cognitive control function. As the current paradigm does

not temporally dissociate regulative and evaluative aspects of cognitive control without potential

component overlap, future research is needed to address this possibility.

Results of the current studies do not support an association between evaluative control

functioning and awareness of TBI-related deficits. Behavioral and ERP indices of conflict/error

processing were not related to two measures of deficit awareness. Deficit awareness represents a

challenging measurement construct as caregiver bias and hypervigilance to deficits can prejudice

self-/other concordance scores and a strong knowledge of participant functioning is required for

clinical rated measures. Thus, the two measures employed in the current studies may not have

been sensitive to the potential relationships between deficit awareness and evaluative control. In

addition, deficit awareness is a different construct than the "on-line" evaluation of performance

and errors associated with evaluative control. Thus, future research directly examining a

participant's knowledge of performance while the task is completed may be more sensitive to

potential relationships with deficit awareness.

As a whole, this dissertation represents an important step in the application of cognitive

neuroscience principles and tools to elucidate evaluative control mechanisms following severe









TBI. Future research and longer-term goals that build upon this research examining cognitive

control adjustments in TBI as a function of TBI severity (as in Larson et al., 2006a), subtyping

TBI survivors based on primary deficits in regulative or evaluative control processes, testing the

neurobiological manifestations of recovery pre- and post-rehabilitation with techniques designed

to remediate difficulties in regulative control or evaluative control, elucidating the relationship

between evaluative control manifestations and "on-line" awareness of errors (rather than general

awareness of deficits), and examining the role of performance feedback (rather than randomly

presented monetary feedback) to predict corrective behavior following severe TBI.









LIST OF REFERENCES


Adams, J.H. (1984). Head Injury. In J. H. Adams, J.A.N. Corsellis & C.W. Duchen (Eds.),
Greenfield's Neuropathology (4th Edition ed., pp. 85-124). London: Edward Arnold.

Adams, J. H., Graham, D. I., Murray, L. S., & Scott, G. (1982). Diffuse axonal injury due to
nonmissile head injury in humans: An analysis of 45 cases. Annals ofNeurology, 12,
557-563.

Adams, J. H., Scott, G., Parker, L. S., Graham, D. I., & Doyle, D. (1980). The contusion index:
A quantitative approach to cerebral contusions in head injury. Neuropathology and
Applied Neurobiology, 6, 319-324.

Allen, C. C., & Ruff, R. M. (1990). Self-rating versus neuropsychological performance of
moderate versus severe head-injured patients. Brain Injury, 4, 7-17.

Anderson, V., Levin, H. S., & Jacobs, R. (2002). Executive functions after frontal lobe injury: A
developmental perspective. In D. T. Stuss & R. T. Knight (Eds.), Principles offrontal
lobe function. New York: Oxford University Press.

Bate, A. J., Mathias, J. L., & Crawford, J. R. (2001). Performance on the Test of Everyday
Attention and standard tests of attention following severe traumatic brain injury. Clinical
Neuropsychology, 15, 405-422.

Beck, A. T. (1996). Beck Depression Inventory Second Edition (BDI-II). USA: The
Psychological Corporation.

Bechara, A. (2004). The role of emotion in decision-making: Evidence from neurological
patients with orbitofrontal damage. Brain Cognition, 55, 30-40.

Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future
consequences following damage to human prefrontal cortex. Cognition, 50, 7-15.

Bechara, A., Tranel, D., & Damasio, H. (2000). Characterization of the decision-making deficit
of patients with ventromedial prefrontal cortext lesions. Brain, 123, 2189-2202.

Bechara, A., Tranel, D., Damasio, H., & Damasio, A. R. (1996). Failure to respond
autonomically to anticipated future outcomes following damage to the prefrontal cortex.
Cerebral Cortex, 6, 215-225.

Benton, A., & Hamsher, K. (1976). Multilingual aphasia examination. Iowa City: University of
Iowa.

Berg, P., & Scherg, M. (1994). A multiple source approach to the correction of eye artifacts.
Electroencephalography and Clinical Neurophysiology, 90, 229-241.









Bergquist, T. F., & Jacket, M. P. (1993). Awareness and goal setting with the traumatically brain
injured. Brain Injury, 7, 275-282.

Bertrand, O., Perrin, F., & Pernier, J. (1985). A theoretical justification of the average-reference
in topographic evoked potential studies. Electroencephalography and Clinical
Neurophysiology, 62, 462-464.

Bigler, E. D. (1990). Neuropathology of traumatic brain injury. In E. D. Bigler (Ed.), Traumatic
Brain Injury. Austin, TX: Pro-ed.

Bigler, E.D. (1999). Neuroimaging in mild TBI. In N.R. Varney & R.J. Roberts (Eds.), The
evaluation and treatment of mild traumatic brain injury (pp. 63-80). Mahwah, New
Jersey: Lawrence Erlbaum Associates.

Bogod, N. M., Mateer, C. A., & Macdonald, S. W. S. (2003). Self-awareness after traumatic
brain injury: A comparison of measures and their relationship to executive functions.
Journal of the International Neuropsychological Society, 9, 450-458.

Bond, M. R. (1986). Neurobehavioral sequelae of closed head injury. In I. Grant & K. M. Adams
(Eds.), Neuropsychological assessment of neuropsychological disorders (pp. 347-373).
New York: Oxford University Press.

Botvinick, M., Carter, C. S., Braver, T. S., Barch, D. M., & Cohen, J. D. (2001). Conflict
monitoring and cognitive control. Psychological Review, 108, 624-652.

Botvinick, M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate
cortex: An update. Trends in Cognitive Sciences, 8, 539-546.

Botvinick, M., Nystrom, L. E., Fissell, K., Carter, C. S., & Cohen, J. D. (1999). Conflict
monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402, 179-181.

Botwinick, J., Storandt, M., Berg, L., & Boland, S. (1988). Senile dementia of the Alzheimer's
type: Subject attrition and testability in research. Archives ofNeurology, 45, 493-496.

Buchanan, R. W., Strauss, M. E., Kirkpatrick, C. H., Breier, A., & Carpenter, J. (1994).
Neuropsychological impairments in deficit and non-deficit forms of schizophrenia.
Archives of General Psychiatry, 51, 801-811.

Butters, M. A., Kaszniak, A. W., Glisky, E. L., Eslinger, P. J., & Schachter, D. L. (1994).
Recency discrimination deficits in frontal lobe patients. Neuropsychology, 8, 343-353.

Brandt, J., & Benedict, R.H.B. (2001). Hopkins VerbalLearning Test--Revised. Professional
Manual. Lutz, Fl: Psychological Assessment Resources.









Braver, T. S., Barch, D. M., & Cohen, J. D. (1999). Cognition and control in schizophrenia: A
computational model of dopamine and prefrontal function. Biological Psychiatry, 46,
312-328.

Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M., Noll, D., & Cohen, J.D. (1998).
Anterior cingulate cortex, error detection, and the online monitoring of performance.
Science, 280, 747-749.

Carroll, J. F. X., & McGinley, J. J. (2000). Mental Health Screening Form-III (MHSF-III). New
York, N.Y.: Project Return Foundation, Inc.

Carroll, J. F. X., & McGinley, J. J. (2001). A screening form for identifying mental health
problems in alcohol/other drug dependent persons. Alcoholism Treatment Quarterly, 19,
33-47.

Cazalis, F., Feydy, A., Valabregue, R., Pelegrini-Issac, M., Pierot, L., & Azouvi, P. (2006). fMRI
study of problem-solving after severe traumatic brain injury. Brain Injury, 20, 1019-
1028.

Centers for Disease Control (1999). Traumatic brain injury in the United States: A report to
congress. Atlanta, GA: Centers for Disease Control and Prevention.

Christodoulou, C., DeLuca, J., Ricker, J. H., Madigan, N. K., Bly, B. M., Lange, G., Kalnin,
A.J., Liu, W.C., Steffener, J., Diamond, B.J., & Ni, A.C. (2001). Functional magnetic
resonance imaging of working memory impairment following traumatic brain injury.
Journal ofNeurology, Neurosurgery, and Psychiatry, 71, 161-168.

Clark, J. H. (1924). The Ishihara test for color blindness. American Journal ofPhysiological
Optics, 5, 269-276.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum
Associates.

Cohen, J. D., Botvinick, M., & Carter, C. S. (2000). Anterior cingulate and prefrontal cortex:
Who's in control? Nature Neuroscience, 3, 421-423.

Cohen, J.D., Servan-Schreiber, D., & McClelland, J.L. (1992). A parallel distributed processing
approach to automaticity. American Journal ofPsychology, 105, 239-269.

Damasio, A. R., & Anderson, S. W. (1993). The frontal lobes. In K. M. Heilman & E. Valenstein
(Eds.), Clinical Neuropsychology (pp. 409-460). New York: Oxford University Press.

Dias, R., & Aggleton, J. P. (2000). Effects of selective excitotoxic prefrontal lesions on
acquisition of non-matching and matching-to-place in the T-maze in the rat: Differential
involvement of the prelimbic-infralimbic and anterior cingulate cortices in providing
behavioral flexibility. European Journal of Neuroscience, 12, 4457-4466.










Dirette, D. (2002). The development of awareness and the use of compensatory strategies for
cognitive deficits. Brain Injury, 16, 861-871.

Di Russo, F., Martinez, A., Sereno, M.I., Pitzalis, S., & Hillyard, S.A. (2002). Cortical sources of
the early component of the visual evoked potential. Human Brain Mapping, 15, 95-111.

Di Pellegrino, G., Ciaramelli, E., & Ladavas, E. (2007). The regulation of cognitive control
following rostral anterior cingulate cortex lesion in humans. Journal of Cognitive
Neuroscience, 19, 275-286.

Egner, T., & Hirsch, J. The neural correlates of functional integration of cognitive control in a
Stroop task. Neuroimage, 15, 539-547.

Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a
target letter in a nonsearch task. Perception & Psychophysics, 16, 143-149.

Falkenstein, M., Hohnsbein, J., Hoormann, J., & Banke, L. (1991). Effects of crossmodal divided
attention on late ERP components. II. Error processing in choice reaction tasks.
Electroencephalography and Clinical Neurophysiology, 78, 447-455.

Falkenstein, M., Hoormann, J., Christ, S., & Hohnsbein, J. (2000). ERP components on reaction
errors and their functional significance: A tutorial. BiologicalPsychology, 51, 87-107.

Finkelstein, E.A., Corso, P.S., & Miller, T.R. (2006). Incidence and economic burden of injuries
in the United States. New York, NY: Oxford University Press.

Flashman, L.A., & McAllister, T.W. (2002). Lack of awareness and its impact in traumatic brain
injury. Neurorehabilitation, 17, 285-296.

Fleming, J., & Strong, J. (1995). Self-awareness of deficits following acquired brain injury:
Considerations for rehabilitation. British Journal of Occupational Therapy, 58, 55-60.

Fleming, J. M., Strong, J., & Ashton, R. (1996). Self-awareness of deficits in adults with
traumatic brain injury: How best to measure? Brain Injury, 10, 1-15.

Fontaine, A., Azouvi, P., Bussel, B., & Samson, Y. (1996). Prefrontal and cingulate dysfunction
at the subacute stage following severe closed head injury: A high resolution PET study.
Proceedings of the Australian Brain Injury Society, 1, 98-104.

Fuster, J. M. (1997). The prefrontal cortex. Anatomy, physiology, and neuropsychology of the
frontal lobe. (3rd ed. ed.). Philadelphia: Lippincott-Raven.

Gehring, W. J., & Fencsik, D. E. (2001). Functions of the medial frontal cortex in the processing
of conflict and errors. The Journal ofNeuroscience, 21, 9430-9437.









Gehring, W. J., Goss, B., Coles, M. G. H., Meyer, D. E., & Donchin, E. (1993). A neural system
for error detection and compensation. Psychological Science, 4, 385-390.

Gehring, W. J., & Knight, R. T. (2000). Prefrontal-cingulate interactions in action monitoring.
Nature Neuroscience, 3, 516-520.

Gehring, W. J., & Willoughby, A. R. (2002). The medial frontal cortex and the rapid processing
of monetary gains and losses. Science, 295, 2279-2282.

Gemba, H., Sasaki, K., & Brooks, V. B. (1986). 'Error' potentials in limbic cortex (anterior
cingulate area 24) of monkeys during motor learning. Neuroscience Letters, 70, 223-227.

Gerstenbrand, F., & Stepan, C. H. (2001). Mild traumatic brain injury. Brain Injury, 15, 95-97.

Grace, J., & Malloy, P. F. (2001). Frontal Systems Behavior Scale Professional Manual. Lutz,
FL: Psychological Assessment Resources, Inc.

Grafman, J., Schwab, K., Warden, D., Pridgen, A., Brown, H. R., & Salazar, A. M. (1996).
Frontal lobe injuries, violence, and aggression: A report of the Vietnam Head Injury
Study. Neurology, 46, 1231-1238.

Grapperon, J., Vidal, F., & Leni, P. (1988). The contribution of cognitive evoked potentials to
knowledge mechanisms of the Stroop color-word interference effect. Neuropsychologia,
38, 701-711.

Gratton, G., Coles, M.G., & Donchin, E. (1992). Optimizing the use of information: Strategic
control of activation of responses. Journal ofExperimental Psychology: General, 121,
480-506.

Gronwall, D., & Wrightson, P. (1981). Memory and information processing capacity after closed
head injury. Journal ofNeurology, Neurosurgery, and Psychiatry, 44, 889-895.

Hajcak, G., McDonald, N., & Simons, R. F. (2003a). To err is autonomic: Error-related brain
potentials, ANS activity, and post-error compensatory behavior. Psychophysiology, 40,
895-903.

Hajcak, G., McDonald, N., & Simons, R. F. (2003b). Anxiety and error-related brain activity.
Biological Psychology, 64, 77-90.

Hajcak, G., Moser, J. S., Holroyd, C. B., & Simons, R. F. (2006). The feedback-related
negativity reflects the binary evaluation of good versus bad outcomes. Biological
Psychology, 71, 148-154.

Hart, T., Giovannetti, M. S., Montgomery, M. W., & Schwartz, M. F. C. (1998). Awareness of
errors in naturalistic action after traumatic brain injury. Journal ofHead Trauma, 13, 16-
28.










Hart, T., Whyte, J., Junghoon, K., & Vaccaro, M. (2005). Executive function and self-awareness
of "real-world" behavior and attention deficits following traumatic brain injury. Journal
ofHead Trauma Rehabilitation, 20, 333-347.

Hart, T., Whyte, J., Polansky, M., Millis, S., Hammond, F. M., Sherer, M., Bushnik, T., Hanks,
R., & Kreutzer, J. (2003). Concordance of patient and family report of neurobehavioral
symptoms at 1 year after traumatic brain injury. Archives of Physical Medicine and
Rehabilitation, 84, 221-230.

Henry, J.D., & Crawford, J.R. (2004). A meta-analytic review of verbal fluency performance in
patients with traumatic brain injury. Neuropsychology, 18, 621-628.

Holroyd, C.B. (2004). A note on the Oddball N200 and the feedback ERN. In M. Ullsperger &
M. Falkenstein (Eds.), Errors, Conflicts, and the Brain. Current Opinions in Performance
Monitoring, (pp. 211-218). Leipzig: MPI of Cognitive Neuroscience.

Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing:
Reinforcement learning, dopamine, and the error-related negativity. Psychological
Review, 109, 679-709.

Holroyd, C. B., Hajcak, G., & Larsen, J. T. (2006). The good, the bad, and the neutral:
Electrophysiological responses to feedback stimuli. Brain Research, 1105, 93-101.

Holroyd, C. B., Larsen, J. T., & Cohen, J. D. (2004). Context dependence of the event-related
potential associated with reward and punishment. Psychophysiology, 41, 245-253.

Holroyd, C. B., Nieuwenhuis, S., Yeung, N., & Cohen, J. D. (2003). Errors in reward predication
are reflected in the event-related potential. Neuroreport, 14, 2481-2484.

Hommel, B., Proctor, R.W., & Vu, K.P. (2004). A feature-intergration account of sequential
effects in the Simon task. Psychological Research, 68, 1-17.

Ille, N., Berg, P., & Scherg, M. (1997). A spatial components method for continuous artifact
correction in EEG and MEG. Biomedical Technology, 42, 80-83.

Ille, N., Berg, P., & Scherg, M. (2002). Artifact correction of the ongoing EEG using spatial
filters based on artifact and brain signal topographies. Journal of Clinical
Neurophysiology, 19, 113-124.

Kaelin, D. L., Cifu, D. X., & Matthies, B. (1996). Methylphenidate effect on attention deficit in
the acutely brain-injured adult. Archives ofPhysical Medicine and Rehabilitation, 77,
6-9.

Kerns, J.G. (2006). Anterior cingulate and prefrontal activity in an fMRI study of trial-to-trial
adjustments on the Simon task. Neuroimage, 15, 399-405.











Kerns, J. G., Cohen, J. D., MacDonald, A. W., Cho, R. Y., Stenger, V. A., & Carter, C. S.
(2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303,
1023-1026.

King, N. S., Crawford, S., Wenden, F. J., Moss, N. E., & Wade, D. T. (1997). Interventions and
service need following mild and moderate head injury: The Oxford Head Injury Service.
Clinical Rehabilitation, 11, 13-27.

Larson, M. J., Jones, V., Kelly, K. G., & Perlstein, W. M. (2004, February). Dissociating
components of cognitive control i iih high-density ERPs: Implementation of control,
conflict processing, and error monitoring. Paper presented at the 32nd Annual Meeting
of the International Neuropsychological Society, Baltimore, MD.

Larson, M. J., Perlstein, W. M., Demery, J. A., & Stigge-Kaufman, D. (2006a). Cognitive control
impairments in traumatic brain injury. Journal of Clinical and Experimental
Neuropsychology, 28, 968-986.

Larson, M. J., Perlstein, W. M., Stigge-Kaufman, D. A., Kelly, K. G., & Dotson, V. M. (2006b).
Affective context-induced modulation of the error-related negativity. Neuroreport, 17,
329-333.

Leclercq, M., Couillet, J., Azouvi, P., Marlier, N., Martin, Y., Strypstein, E., & Rousseaux, M.
(2000). Dual task performance after severe diffuse traumatic brain injury or vascular
prefrontal damage. Journal ofExperimental and Clinical Neuropsychology, 22, 339-350.

Leon-Carrion, J., Alarcon, J.C., Revuelta, M., Murillo-Cabezas, F., Dominguez-Roldan, J.M.,
Dominguez-Morales, M.R., Machuca-Murga, F., & Forastero, P. (1998). Executive
functioning as outcome in patients after traumatic brain injury. International Journal of
Neuroscience, 94, 75-83.

Levander, M. B., & Sonesson, B. G. (1998). Are there any mild interhemispheric effects after
moderately severe closed head injury. Brain Injury, 12, 165-173.

Levin, H. S., Amparo, E., Eisenberg, H. M., Williams, D. H., High, W. M., Jr., McArdle, C. B.,
& Weiner, R.L. (1987). Magnetic resonance imaging and computerized tomography in
relation to the neurobehavioral sequelae of mild and moderate head injuries. Journal of
Neurosurgery, 66, 706-713.

Levin, H. S., Gary, H., Eisenberg, H. M., Ruff, R. M., Barth, J. T., Kreutzer, J., High, W.M.,
Portman, S., Foulkes, M.A., Jane, J.A., Mamarou, A., & Marshall, L.F. (1990).
Neurobehavioral outcome one year after severe head injury: Experience of the Traumatic
Coma Data Bank. Journal ofNeurosurgery, 73, 699-709.









Levine, B., Katz, D. I., Dade, L., & Black, S. E. (2002). Novel approaches to the assessment of
frontal damage and executive deficits in traumatic brain injury. In D. T. Stuss & R. T.
Knight (Eds.), Principles of frontal lobe function (pp. 448-465). New York: Oxford
University Press.

Levine, B., Robertson, I. H., Clare, L., Carter, G., Hong, J., Wilson, B. A., Duncan, J., & Stuss
D.T. (2000). Rehabilitation of executive functioning: An experimental-clinical validation
of goal management training. Journal of the International Neuropsychological Society, 6,
299-312.

Lezak, M. D., Howieson, D., & Loring, D. (2004). Neuropsychological assessment (4th Edition
ed.). New York: Oxford Press.

Liotti, M., Woldorff, M. G., Perez, R., & Mayberg, H. S. (2000). An ERP study of the temporal
course of the Stroop color-word interference effect. Neuropsychologia, 38, 701-711.

MacDonald, A. W., Cohen, J. D., Stenger, V. A., & Carter, C. S. (2000). Dissociating the role of
the dorsolateral prefrontal cortex in cognitive control. Science, 288, 1835-1838.

Marin, R. S. (1991). Apathy: A neuropsychiatric syndrome. Journal of Neuropsychiatry and
Clinical Neuroscience, 3, 243-254.

Marin, R. S., Biedrzycki, R. C., & Firinciogullari, S. (1991). Reliability and validity of the
Apathy Evaluation Scale. Psychiatry Research, 38, 143-162.

Mathalon, D. H., Fedor, M., Faustman, W. O., Gray, M., Askari, N., & Ford, J. M. (2002).
Response-monitoring dysfunction in schizophrenia: An event-related brain potential
study. Journal ofAbnormal Psychology, 111, 22-41.

Mayr, U., Awh, E., Laurey, P. (2003). Conflict adaptation effects in the absence of executive
control. Nature Neuroscience, 6 450-452.

McAllister, T. W., Flashman, L. A., Sparling, M. B., & Saykin, A. J. (2004). Working memory
deficits in traumatic brain injury: Catecholaminergic mechanisms and prospects for
treatment--A review. Brain Injury, 18, 331-350.

McAllister, T.W., Saykin, A.J., Flashman, L.A., Sparling, M.B., Johnson, S.C., Guerin, S. J.,
Mamourian, A.C., Weaver, J.B., & Yanofsky, N. (1999). Brain activation during working
memory one month after mild traumatic brain injury: A functional MRI study.
Neurology, 12, 1300-1308.

McAllister, T. W., Sparling, M. B., Flashman, L. A., Guerin, S. J., Mamourian, A. C., & Saykin,
A. J. (2001). Differential working memory load effects after mild traumatic brain injury.
Neurolmage, 14, 1004-1012.









McDowell, S., Whyte, J., & D'Esposito, M. (1997). Working memory impairments in traumatic
brain injury: Evidence from a dual-task paradigm. Neuropsychologia, 35, 1341-1353.

McMillan, T. M., Jongen, E. L., & Greenwood, R. J. (1996). Assessment of post-traumatic
amnesia after severe closed head injury: Retrospective or prospective? Journal of
Neurology, Neurosurgery, and Psychiatry, 60, 422-427.

Meythaler, J. M., Peduzzi, J. D., Eleftheriou, E., & Novack, T. A. (2001). Current concepts:
Diffuse axonal injury-associated traumatic brain injury. Archives ofPhysical Medicine
and Rehabilitation, 82, 1461-1471.

Miller, E. K. (2000). The prefrontal cortex and cognitive control. Nature Reviews: Neuroscience,
1, 59-66.

Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex. Annual Review
ofNeuroscience, 24, 167-202.

Miller, L. A. (1992). Impulsivity, risk-taking, and the ability to synthesize fragmented
information after frontal lobectomy. Neuropsychologia, 30, 69-79.

Miltner, W. H. R., Lemke, U., Weiss, T., Holroyd, C. B., Scheffers, M. K., & Coles, M. G. H.
(2003). Implementation of error-processing in the human anterior cingulate cortex: A
source analysis of the magnetic equivalent of the error-related negativity. Biological
Psychology, 64, 157-166.

Mocks, J., Koohler, W., Gasser, T., & Pham, D.T. (1988). Novel approaches to the problem of
latency jitter. Psychophysiology, 25, 217-226.

Napolitano, E., Elovic, E. P., & Qureshi, A. I. (2005). Pharmacological stimulant treatment of
neurocognitive and functional deficits after traumatic and non-traumatic brain injury.
Medical Science Monitor, 11, RA212-220.

National Institute of Health. (1998). NIH Consensus Statement on Rehabilitation of Persons n i/h
TBI, Bethesda, MD.

Neter, J., Wasserman, W., & Kutner, M. H. (1985). Applied linear statistical models:
Regression, analysis of variance, and experimental designs (2nd ed.). Homewood, Ill.:
R.D. Irwin.

Newsome, M.R., Scheibel, R.S., Steinberg, J.L., Troyanskaya, M., Sharma, R.G., Rauch, R.A.,
Li, X., & Levin, H.S. (2007). Working memory brain activation following severe
traumatic brain injury. Cortex, 43, 95-111.

Nieuwenhuis, S., Ridderinkhof, K. R., Blom, J., Band, G. P., & Kok, A. (2001). Error-related
brain potentials are differentially related to awareness of response errors: Evidence from
an antisaccade task. Psychophysiology, 38, 752-760.










Nieuwenhuis, S., Stins, J.F., Posthuma, D., Polderman, T.J., Boomsma, D.I., & de Geus, E.J.
(2006). Accounting for sequential trial effects n the flanker task: Conflict adaptation or
associative priming. Memory & Cognition, 34, 1260-1272.

Niki, H., & Watanabe, M. (1979). Prefrontal and cingulate unit activity during timing behaviour
in the macaque. Brain Research, 171, 213-224.

Noe, E., Ferri, J., Caballero, M. C., Villodre, R., Sanchez, A., & Chirivella, J. (2005). Self-
awareness after acquired brain injury: Predictors and rehabilitation. Journal of
Neurology, 252, 168-175.

Notebaert, W., Gevers, W., Verbruggen, F., & Liefooghe, B. (2006). Top-down and bottom-up
sequential modulations of congruency effects. Psychonomic Bulletin & Review, 13, 112-
117.

Oddy, M., Coughlan, T., Tyerman, A., & Jenkins, D. (1985). Social adjustment after closed head
injury: A further follow-up seven years after injury. Journal of Neurology, Neurosurgery,
and Psychiatry, 48, 564-568.

O'Keeffe, F. M., Dockree, P. M., & Robertson, I. H. (2004). Poor insight in traumatic brain
injury mediated by impaired error processing? Evidence from electrodermal activity.
Cognitive Brain Research, 22, 101-112.

Overbeek, T.J.M., Nieuwenhuis, S., Ridderinkhof, K.R. (2005). Dissociable components of error
processing: On the functional significance of the Pe vis-a-vis the ERN/Ne. Journal of
Psychophysiology, 19, 319-329.

Ownsworth, T. L., Fleming, J., Desbois, J., Strong, J., & Kuipers, P. (2006). A metacognitive
contextual intervention to enhance error awareness and functional outcome following
traumatic brain injury: A single-case experimental design. Journal of the International
Neuropsychological Society, 12, 54-63.

Ownsworth, T. L., McFarland, K., & Young, R. M. (2000). Development and standardization of
the Self-regulation Skills Interview (SRSI): A new clinical assessment tool for acquired
brain injury. Clinical Neuropsychology, 14, 76-92.

Ownsworth, T. L., McFarland, K., & Young, R. M. (2002). The investigation of factors
underlying deficits in self-awareness and self-regulation. Brain Injury, 16, 291-309.

Ownsworth, T. L., & Oei, T. P. S. (1998). Depression after traumatic brain injury:
Conceptualization and treatment considerations. Brain Injury, 12, 735-751.

Park, N. W., Conrod, B., Hussain, Z., Murphy, K. J., Rewilak, D., & Black, S. E. (2003). A
treatment program for individuals with deficient evaluative processing and consequent
impaired social and risk judgement. Neurocase, 9, 51-62.










Perlstein, W. M., Cole, M. A., Demery, J., Seignourel, P. J., Dixit, N. K., Larson, M. J., &
Briggs, R.W. (2004). Parametric manipulation of working memory load in traumatic
brain injury: Behavioral and neural correlates. Journal of the International
Neuropsychological Society, 10, 724-741.

Perlstein, W. M., Larson, M. J., Dotson, V. M., & Kelly, K. G. (2006). Temporal dissociation of
components of cognitive control dysfunction in severe TBI: ERPs and the cued-Stroop
task. Neuropsychologia, 44, 260-274.

Picton, T.W., Lins, O., & Scherg, M. (1995). The recording and analysis of event-related
potentials. In F. Boller & J. Grafman (Series Eds.), & R. Johnson, Jr. (Section Ed.),
Handbook of neuropsychology: Vol. 10, section 14. Event-related brain potentials and
cognition (pp. 3-73). Amsterdam: Elsevier.

Plenger, P. M., Dixon, C. E., Castillo, R. M., Frankowski, R. F., Yablon, S. A., & Levin, H. S.
(1996). Subacute methylphenidate treatment for moderate to moderately severe traumatic
brain injury: A preliminary double-blind placebo-controlled study. Archives of Physical
Medicine and Rehabilitation, 77, 536-540.

Ponsford, J., & Kinsella, G. (1992). Attentional deficits following closed-head injury. Journal of
Clinical and Experimental Neuropsychology, 14, 822-838.

Potter, D. D., Jory, S. H., Basset, M. R., Barret, K., & Mychalkiw, W. (2002). Effect of mild
head injury on event-related potential correlates of Stroop task performance. Journal of
the International Neuropsychological Society, 8, 828-837.

Prigatano, G. P., Bruna, O., Mataro, M., Munoz, J. M., Fernandez, S., & Junque, C. (1998).
Initial disturbances of consciousness and resultant impaired awareness in Spanish patients
with traumatic brain injury. Journal of Head Trauma Rehabilitation, 13, 29-38.

Rabbitt, P.M.A. (1966). Errors and error correction in choice reaction tasks. Journal of
Experimental Psychology, 71, 264-272.

Rabbitt, P.M.A. (1968). Three kinds of error-signaling responses in a serial choice task.
Quarterly Journal ofExperimental Psychology, 20, 179-188.

Ratcliff, R. (1993). Methods for dealing with reaction time outliers. Psychological Bulletin, 114,
510-532.

Rebai, M., Bernard, C., & Lannou, J. (1997). The Stroop test evokes a negative brain potential,
the N400. International Journal ofNeuroscience, 91, 85-94.

Reitan, R.M. (1958). Validity of the Trail Making Test as an indicator of organic brain damage.
Perceptual andMotor .k//l, 8, 271-276.










Ridderinkhof, K.R. (2002). Activation and suppression in conflict tasks: Empirical clarification
through distributional analyses. In W. Prinz & B. Hommel (Eds.), Attention and
Performance XIX(pp. 494-519). Oxford University Press: Oxeford.

Rios, M., Perianez, J. A., & Munoz-Cespedes, J. M. (2004). Attentional control and slowness of
information processing after severe traumatic brain injury. Brain Injury, 18, 257-272.

Rolls, E. T. (2000). The orbitofrontal cortex and reward. Cerebral Cortex, 10(3), 284-294.

Ruchsow, M., Grothe, J., Spitzer, M., & Kiefer, M. (2002). Human anterior cingulate cortex is
activated by negative feedback: Evidence from event-related potentials in a guessing task.
Neuroscience Letters, 14, 203-206.

Ruchsow, M., Herrnberger, B., Wiesend, C., Gron, G., Spitzer, M., & Kiefer, M. (2004). The
effect of erroneous responses on response monitoring in patients with major depressive
disorder: A study with event-related potentials. Psychophysiology, 41, 833-840.

Ruchsow, M., Spitzer, M., Gron, G., Grothe, J., & Kiefer, M. (2005). Error processing and
impulsiveness in normals: Evidence from event-related potentials. Cognitive Brain
Research, 24, 317-325.

Ruchsow, M., Hernberger, B., Beschoner, P., Gron, G., Spitzer, M. & Kiefer, M. (2006). Error
processing in major depressive disorder: Evidence from event-related potentials. Journal
ofPsychiatry Research, 40, 37-46.

Rushworth, M. F. S., Hadland, K. A., Gaffan, D., & Passingham, R. E. (2003). The effect of
cingulate cortex lesions on task switching and working memory. Journal of Cognitive
Neuroscience, 15, 338-353.

Rushworth, M. F. S., Walton, M. E., Kennerley, S. W., & Bannerman, D. M. (2004). Action sets
and decisions in the medial frontal cortex. Trends in Cognitive Sciences, 9, 410-417.

Salmond, C. H., Menon, D. K., Chatfield, D. A., Pickard, J. D., & Sahakian, B. J. (2005).
Deficits in decision-making in head injury survivors. Journal ofNeurotrauma, 22(6),
613-622.

Scheibel, R.S., Newsome, M.R., Steinberg, J.L., Pearson, D.A., Rauch, R.A., Mao, H.,
Troyanskaya, M., Sharma, R.G., & Levin, H.S. (2007). Altered brain activation during
cognitive control in patients with moderate to severe traumatic brain injury.
Neurorehabilitation and Neural Repair, 21, 36-45.

Scheibel, R.S., Pearson, D.A., Faria, L.P., Kotrla, K.J., Aylward, E., Bachevalier, J., & Levin
H.S. (2003). An fMRI study of executive functioning after severe diffuse TBI. Brain
Injury, 17, 919-930.










Scherg, M. (1990). Fundamentals of dipole source potential analysis. In F. Grandori & M. Hoke
(Eds.), Auditory evoked magnetic fields and electric potentials. Advances in audiology
(Vol. 6, pp. 65-78). Basel: Karger.

Schlund, M. W. (2002a). Effects of acquired brain injury on adaptive choice and the role of
reduced sensitivity to contingencies. Brain Injury, 16, 527-535.

Schlund, M. W. (2002b). The effects of brain injury on choice and sensitivity to remote
consequences: Deficits in discriminating response-consequence relations. Brain Injury,
16, 347-357.

Schlund, M. W., & Pace, G. M. (2000). The effects of traumatic brain injury on reporting and
responding to causal relations: An investigation of sensitivity to reinforcement
contingencies. Brain Injury, 14, 573-583.

Schlund, M. W., Pace, G. M., & McGready, J. (2001). Relations between decision-making
deficits and discriminating contingencies following brain injury. Brain Injury, 15, 347-
357.

Seignourel, P.J., Robins, D.L., Larson, M.J., Demery, J.A., Cole, M., & Perlstein, W.M. (2005).
Cognitive control in closed head injury: Context maintenance dysfunction or prepotent
response inhibition deficit? Neuropsychology, 19, 578-590.

Shallice, T., & Burgess, P. W. (1991). Deficits in strategy application following frontal lobe
damage in man. Brain, 114, 727-741.

Sherer, M., Bergloff, P., Boake, C., High, W., & Levin, E. (1998). The Awareness
Questionnaire: Factor structure and internal consistency. Brain Injury, 12, 63-68.

Sherer, M., Hart, T., Whyte, J., Nick, T. G., & Yablon, S. A. (2005). Neuroanatomic basis of
impaired self-awareness after traumatic brain injury: Findings from early computed
tomography. Journal ofHead Trauma Rehabilitation, 20, 287-300.

Simmond, M., & Fleming, J. (2003). Reliability of the self-awareness of deficits interview for
adults with traumatic brain injury. Brain Injury, 17, 325-337.

Soeda, A., Nakashima, T., Okumura, A., Kuwata, K., Shinoda, J., & Iwama, T. (2005). Cognitive
impairment after traumatic brain injury: A functional magnetic resonance imaging study
using the Stroop task. Neuroradiology, 47, 501-507.

Speilberger, C. D., Gorusch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for
the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.

Spreen, O., & Strauss, E. (1991). A compendium ofneuropsychological tests: Administration,
norms, and commentary. New York: Oxford University Press.










Starkstein, S.E., Mayberg, H.S., Preziosi, T.J., Andrezejewski, P., Leiguarda, R., & Robinson,
R.G. (1992). Reliability, validity, and clinical correlates of apathy in Parkinson's disease.
Journal ofNeuropsychiatry and Clinical Neuroscience, 4, 134-139.

Stemmer, B., Segalowitz, S. J., Witzke, W., & Schonle, P. W. (2004). Error detection in patients
with lesions to the medial prefrontal cortex: An ERP study. Neuropsychologia, 42, 118-
130.

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental
Psychology, 18, 643-662.

Stuss, D. T. (1991). Self, awareness, and the frontal lobes: A neuropsychological perspective. In
J. Strauss & G. R. Goethals (Eds.), The self. Interdisciplinary approaches (pp. 255-278).
New York: Springer-Verlag.

Stuss, D. T., & Gow, C. A. (1992). "Frontal dysfunction" after traumatic brain injury.
Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 5, 272-282.

Swick, D., & Turken, A. U. (2002). Dissociation between conflict detection and error-monitoring
in the human anterior cingulate cortex. Proceedings of the National Academy of Sciences,
99, 16354-16359.

Tateno, A., Jorge, R. E., & Robinson, R. G. (2003). Clinical correlates of aggressive behavior
after traumatic brain injury. The Journal ofNeuropsychiatry and Clinical Neurosciences,
15, 155-160.

Teasdale, G., & Jennett, B. (1974). Assessment of coma and impaired consciousness: A practical
scale. Lancet, ii, 81-84.

Toglia, J., & Kirk, U. (2000). Understanding awareness deficits following brain injury.
Neurorehabilitation, 15, 57-70.

Trudel, T. M., Tyron, W., & Purdum, C. (1998). Awareness of disability and long-term outcome
after traumatic brain injury. Rehabilitation Psychology, 43, 276-281.

Ullsperger, M., Bylsma, L.M., & Botvinick, M.M. (2005). The conflict adaptation effect: It's not
just priming. Cognitive, Affective, and Behavioral Neuroscience, 5, 467-472.

van Meel, C. S., Oosterlaan, J., Heslenfeld, D. J., & Sergeant, J. A. (2005). Telling good from
bad news: ADHD differentially affects processing of positive and negative feedback
during guessing. Neuropsychologia, 43, 1946-1954.

van Veen, V., & Carter, C. S. (2002a). The anterior cingulate as a conflict monitor: fMRI and
ERP studies. Physiology and Behavior, 77, 477-482.









van Veen, V., & Carter, C. S. (2002b). The timing of action-monitoring processes in the anterior
cingulate cortex. Journal of Cognitive Neuroscience, 14, 593-602.

Verbruggen, F., Notebaert, W., Liefooghe, B., & Vandierendonck, A. (2006). Stimulus- and
response-conflict-induced cognitive control on the flanker task. Psychonomic Bulletin &
Review, 13, 328-333.

Vidal, F., Hasbroucq, T., Grapperon, J., & Bonnet, M. (2000). Is the 'error negativity' specific to
errors. Biological Psychology, 51, 109-128.

Wagner, A. K., Sokoloski, J. E., Ren, D., Chen, X., Khan, A. S., Zafonte, R. D., Michael, A.C.,
& Dixon, C.E. (2005). Controlled cortical impact injury affects dopaminergic
transmission in the rat striatum. Journal ofNeurochemistry, 95, 457-465.

Walton, M. E., Bannerman, D. M., Alterescu, K., & Rushworth, M. F. S. (2003). Functional
specialization within medial frontal cortex of the anterior cingulate for evaluating effort-
related decisions. Journal ofNeuroscience, 23, 6475-6479.

Wechsler, D. (1987). Wechsler Memory Scale--Revised. San Antonio, TX: The Psychological
Corporation.

Wechsler, D. (1997). Wechsler Adult Intelligence Scale--ThirdEdition. San Antonio, TX: The
Psychological Corporation.

Weddell, R., Oddy, M., & Jenkins, D. (1980). Social adjustment after rehabilitation: A two year
follow-up of patients with severe head injury. Psychological Medicine, 10, 257-263.

West, R. (2003). Neural correlates of cognitive control and conflict detection in the Stroop and
digit-location tasks. Neuropsychologia, 41, 1122-1135.

West, R. (2004). The effects of aging on controlled attention and conflict processing in the
Stroop task. Journal of Cognitive Neuroscience, 16, 103-113.

West, R., & Alain, C. (1999). Event-related neural activity associated with the Stroop task.
Cognitive Brain Research, 8, 102-111.

West, R., & Alain, C. (2000). Effect of task context and fluctuations of attention on neural
activity supporting performance of the Stroop task. Brain Research, 873, 102-111.

West, R., Jakubek, K., Wymbs, N., Perry, M., & Moore, K. (2005). neural correlates of conflict
processing. Experimental Brain Research, 167, 38-48.

West, R., & Moore, K. (2005). Adjustments of cognitive control in younger and older adults.
Cortex, 41, 570-581.









Woody, C.D. (1967). Characterization of an adaptive filter for the analysis of variable latency
neuroelectric signals. Medical and Biological Engineering, 5, 539-553.

Woods, S.P., Scott, J.C., Conover, E., Marcotte, T.D., Heaton, R.K., Grant, I. (2005). Test-retest
reliability of component process variables within the Hopkins Verbal Learning Test-
Revised. Assessment, 12, 96-100.

Yasuda, A., Sato, A., Miyawaki, K., Kumano, H., & Kuboki, T. (2004). Error-related negativity
refelcts detection of negative reward prediction error. Neuroreport, 15, 2561-2565.

Yeung, N., & Cohen, J. D. (2006). The impact of cognitive deficits on conflict
monitoring. Predictable dissociations between the error-related negativity and
N2. Psychological Science, 17, 164-171

Yeung, N., Cohen, J. D., & Botvinick, M. (2004). The neural basis of error detection:
Conflict monitoring and the error-related negativity. Psychological Review, 111,
931-954.









BIOGRAPHICAL SKETCH

Michael James Larson obtained a bachelor of science degree in psychology from Brigham

Young University in Provo, Utah in 2002. He subsequently began his doctoral training in the

Department of Clinical and Health Psychology at the University of Florida, where he earned his

master of science degree in 2004. Michael earned his Ph.D. in psychology, with a specialization

in clinical neuropsychology, in August 2008 following a one-year clinical internship at Emory

University in Atlanta, Georgia.





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1 COGNITIVE CONTROL DISRUPTION IN TRAUMATIC BRAIN INJURY By MICHAEL JAMES LARSON A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

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2 2008 Michael James Larson

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3 ACKNOWLEDGMENTS I wish to acknowledge my chair and ment or, William M. Perlstein, Ph.D., for his assistance and support on this project and his guid ance throughout graduate sc hool. I also wish to express gratitude to my other dissertation co mmittee members, Russell M. Bauer, Ph.D., Dawn Bowers, Ph.D., Michael Robinson, Ph.D., and Linda Shaw, Ph.D., for their assistance with this endeavor. I would like to thank David Stigge-K aufman, Cortney Mauer, Megan McIntyre, Drew Nagle, Allen Sirizi, and Raechel Steckley for their assistance in participant recruitment and data collection. This research was s upported by pre-doctoral National In stitute of Health Fellowship #F31-NS-053335.

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4 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................3 LIST OF TABLES................................................................................................................. ..........6 LIST OF FIGURES................................................................................................................ .........7 ABSTRACT....................................................................................................................... ..............9 CHAPTER 1 GENERAL INTRODUCTION..............................................................................................11 Cognitive Control and Traumatic Brain Injury (TBI).............................................................11 Awareness of Deficits in TBI.................................................................................................15 2 AWARENESS OF DEFICITS, PE RFORMANCE MONITORING, AND EVALUATIVE CONTROL FOLLOWING SE VERE TRAUMATIC BRAIN INJURY.....19 Introduction................................................................................................................... ..........19 Awareness of Deficits, Perfor mance Monitoring, and TBI.............................................22 Current Study.................................................................................................................. .23 Methods........................................................................................................................ ..........23 Assessment of TBI Symptoms and Deficit Awareness...................................................26 Experimental Task...........................................................................................................29 Electrophysiological Data Recordi ng, Reduction, and Measurement.............................30 Data Analysis.................................................................................................................. .31 Results........................................................................................................................ .............32 Behavioral Data...............................................................................................................32 Event-related Potential (ERP) Data: Response-related Activity.....................................33 Correlational Analyses....................................................................................................35 Discussion..................................................................................................................... ..........35 3 COGNITIVE CONTROL ADJUSTMENT PROCESSES FOLLOWING SEVERE TRAUMATIC BRAIN INJURY............................................................................................47 Introduction................................................................................................................... ..........47 Conflict Adaptation vs. Repetition Priming....................................................................53 Current Study.................................................................................................................. .54 Methods........................................................................................................................ ..........55 Electrophysiological Data Recording..............................................................................55 Event-related Potential Reduction and Measurement.....................................................56 Data Analysis.................................................................................................................. .57 Results........................................................................................................................ .............58 Behavioral Performance..................................................................................................58

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5 ERP Data....................................................................................................................... ..60 Impact of Repetition Priming..........................................................................................63 Correlational Analyses....................................................................................................64 Discussion..................................................................................................................... ..........65 4 FEEDBACK UTILIZATION AND REWARD CONTEXT SENSITIVITY IMPAIRMENT FOLLOWING SEVERE TRAUMATIC BRAIN INJURY.........................78 Introduction................................................................................................................... ..........79 Methods........................................................................................................................ ..........82 Participants................................................................................................................... ...82 Experimental Task...........................................................................................................84 Electrophysiological Data Recording and Reduction......................................................86 Data Analysis.................................................................................................................. .87 Results........................................................................................................................ .............88 Behavioral Data...............................................................................................................88 ERP Data....................................................................................................................... ..88 Discussion..................................................................................................................... ..........91 5 GENERAL DISCUSSION...................................................................................................101 LIST OF REFERENCES.............................................................................................................106 BIOGRAPHICAL SKETCH.......................................................................................................122

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6 LIST OF TABLES Table page 2-1 Demographic and mean summary data fo r severe traumatic br ain injury (TBI) and control participants........................................................................................................... ..41 2-2 Injury characteristics and neurorad iological information for TBI participants.................42 2-3 Error rates and reaction times on the Stroop Task.............................................................43 2-4 Error-related negativity and post-erro r positivity component amplitude data as a function of task condition..................................................................................................44 3-1 Reaction times for congrue nt and incongruent trials as a function of previous trial congruency..................................................................................................................... ....71 3-2 Percent-errors for congruent and incongr uent trials as a function of previous trial congruency..................................................................................................................... ....71 3-3 Difference scores for reaction times and error rates of th e incongruent minus congruent difference..........................................................................................................71 3-4 Amplitude data for the N450 and conflict slow potential components.............................72 4-1 Demographic data for the subs et of control and TBI participants.....................................96 4-2 Injury characteristics and neuroradio logical information for the subset of TBI participants................................................................................................................... ......97 4-3 Reaction times for control and TBI participants on the guessing task..............................98 4-4 Non-reward minus rewa rd difference wave means...........................................................98 4-5 Peak-to-peak component amplitude and latency as a function of feedback condition......98

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7 LIST OF FIGURES Figure page 2-1 Electrical geodesics sensor layout and in ternational 10 equivalents for the 64channel geodesic sensor net...............................................................................................45 2-2 Grand average event-related potential (ERP) waveforms depicting response-locked correctand error-related ac tivity averaged across frontomedial electrode locations for the error-related negativity (ERN) and top view of the spline-interpolated voltage distribution maps showing mean vo ltages for error-trial activity......................................46 2-3 Grand average ERP waveforms depicti ng response-locked correctand error-related activity averaged across centro-parietal electrode locations for the post-error positivity (Pe) and top view of the splineinterpolated voltage distribution maps showing mean voltages for error-trial activity...................................................................46 3-1 Mean reaction times as a function of group, congruency, and current/previous trial type........................................................................................................................... ..........73 3-2 Mean error rates as a function of gro up, congruency, and current/ previous trial type......73 3-3 Grand average ERP waveforms of stimul us-locked congruent a nd incongruent trials averaged across fronto-medial electrode locations for th e N450 and top view of the spline-interpolated curren t source density maps................................................................74 3-4 Grand average ERP waveforms of stimul us-locked congruent a nd incongruent trials averaged across posterior elec trode locations for the conflic t slow potential (conflict SP) and top view of the spline-interp olated current source density maps.........................74 3-5 Grand average ERP waveforms of s timulus-locked waveforms for congruent and incongruent waveforms as a functio n of previous trial congruency..................................75 3-6 Mean N450 amplitude as a function of group, congruency, and current/previous trial type........................................................................................................................... ..........76 3-7 Mean conflict SP amplitude as a func tion of group, congruency, and current/previous trial type..................................................................................................................... ........76 3-8 Scatter plot reflecting the relationship between self-awareness of deficits interview total score for traumatic brain injury (TB I) participants and the parietal conflict SP incongruent minus c ongruent difference...........................................................................77 3-9 Scatter plot reflecting the relations hip between frontal systems behavior scale (FrSBe) otherminus self-rated total score for TBI participants and the parietal conflict SP incongruent minus congruent difference.........................................................77

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8 4-1 Grand average ERP waveforms depi cting feedback-locked reward and non-reward activity as well as the non-reward minus re ward difference wave at recording site FCz for control and TBI participants.................................................................................99 4-2 Grand average feedback-locked ERP wave forms showing reward and non-reward activity as well as non-reward minus reward difference waves at recording site FCz for the high frequency trials and low frequency trials.......................................................99 4-3 Spline-interpolated vo ltage maps of the non-reward minus reward difference wave for control and TBI participants.......................................................................................100

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9 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy COGNITIVE CONTROL DISRUPTION IN TRAUMATIC BRAIN INJURY By Michael James Larson August 2008 Chair: William M. Perlstein Major: Psychology Cognitive control comprises two essential inte ractive component processes: a regulative component supporting the activati on and implementation of contro l and an evaluative component that monitors the need for regulative control and signals when adjustments in control are necessary. Survivors of severe traumatic br ain injury (TBI) experience cognitive control impairments that frequently contribute to long-t erm disability, but the sp ecific nature of these impairments is poorly characterized. Moreove r, research on TBI-related cognitive control dysfunction has focused primarily on regulative control deficits. The current series of studies utilized behavioral (i.e., response time [RT] and error rates) and electroph ysiological (i.e., eventrelated potentials [ERPs]) measures of cognitive control to test th e hypotheses that: (1) survivors of severe TBI exhibit impairments compared to demographically-matched healthy control participants in the ev aluative control functions of performance-monito ring, conflict detection, feedback utilization, and signaling for increased implementation of regulative control; and (2) both behavioral and electrophysiolo gical manifestations of evalua tive control impairment are associated with impairments in deficit awaren ess. Relative to healthy control participants, survivors of severe TBI showed attenuated ne ural reflections of both performance-monitoring and feedback context utilization; however, gr oups did not differ on putative measures of the

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10 evaluative control process of signaling for e nhanced regulative control following conflict. Neither behavioral nor electrophysio logical manifestations of eval uative control were associated with awareness of deficits in TBI survivors. Ta ken together, these finding s suggest that survivors of severe TBI are impaired in the evaluative control functions of performance monitoring and feedback context utilization, but can still utilize c onflict information to reactively adjust performance to changing task demands. Future re search based on these findings may allow us to capitalize on the heterogeneity associated with TBI to identify clinically meaningful subtypes and appropriately tailor reha bilitation efforts to specific cognitive control deficits.

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11 CHAPTER 1 GENERAL INTRODUCTION Traumatic brain injury (TBI) is one of th e most common neurologi cal disorders in the United States. The estimated incidence rate is nearly 100 per 100,000 individuals, with approximately 52,000 deaths annually (National Institute of Health, 1998). TBI occurs approximately two times more often in males th an females (Centers for Disease Control, 1999), with direct medical costs and i ndirect costs (e.g., lost productivity ) estimated to be approximately $60 billion per year in the United States alone (Fi nkelstein et al., 2006). Mild injuries account for approximately 80% of all cases of TBI, and may result in recovery of function without intervention (Levin et al., 1987). In contrast, moderate-to-severe TB I tends to be associated with worse outcomes and requires extensive and costly rehabilitation in order to maximize functional recovery (Levin et al., 1990). The debilitating behavioral and cognitive consequences of TBI often dramatically alter survivors life-course due in part, to disruption of the family, income loss, and illness-related lifetime expenses (Nat ional Institute of Health, 1998). Given the high prevalence, extensive disability, and expens e associated with TBI, a comprehensive understanding of the cognitive impairments, th eir potential common neural bases, and their relationship to outcome is critic al to developing effective rehabi litation strategies and monitoring rehabilitation effects on brain function. Cognitive Control and Traumatic Brain Injury Although the pattern of impairment following TBI varies across individuals and severity of injury, the preponderance of curre nt evidence suggests that TBI is associated with severitydependent deficits in cognitive control-that is, i n the ability to orchestrate thought and action in accord with internal goals (Miller & Cohen, 2001, p. 167) Such deficits appear to exist either in

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12 addition or in contrast to more generalized c ognitive impairment (Larson et al., 2006a; Levin et al., 1990; Levine et al., 2002; Perlstein et al., 2004, 2006; Seignourel et al., 2005). Little systematic research has explicitly examined c ognitive control impairment in TBI. Additionally, until only recently, examinati on of cognitive functioning in TBI has employed tasks that primarily examine dorsolateral pr efrontal cortex (dlPFC)-media ted cognitive control functions. The use of such tasks has been a critical step in identifying some of the specific cognitive processes impaired in patients with TBI and the brain regions most vulnerable to disruption in such patients; however, other aspects of cognitiv e control dysfunction in TBI have received little attention despite their potential importance in adaptation to, and recovery from, injury. A basic understanding of the construct of cogni tive control is requisite to full appreciation of cognitive control dysfunction in TBI. Two broad sets of dissociable processes are considered central to cognitive control: regulative and evalua tive control processes (Botvinick et al., 2001; Kerns et al., 2004; Miller, 2000; Miller & Cohen, 2001). Regulative contro l processes are those involved in the top-down control of cognition an d include such functions as representing and maintaining goals (i.e., context maintenance) and implementing control (i.e., allocating limited attentional resources). These func tions rely on the integrity of the dlPFC (Cohen et al., 2000) and are most critical when faced with competing response options (e.g., the representations of both correct and incorrect response optio ns). A second set of processes essential for cognitive control are evaluative in nature and involve the on-lin e assessment of performance (e.g., detection of processing conflicts, error-monitori ng). These evaluative functions are critical for flexible adjustments of top-down contro l and adaptation to a constantly changing environment. The monitoring of performance for erro rs and detection of conflict can subsequently act as a signal to allocate the increased attentional control necessa ry to overcome errors/conflict and successfully

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13 perform goal-directed behaviors (Botvinick et al., 2001; van Veen & Carter, 2002a). A convergence of human and animal research implicat es the medial frontal cortex, specifically the anterior cingulate cortex (ACC), as essential to these evaluative control processes (Botvinick et al., 2001; Rushworth et al., 2004; van Veen & Cart er, 2002a,b). In sum, cognitive control is a dynamic process implemented in a distributed network in the brain that involves closely interacting, but dissociable components. Ante rior cingulate-mediated evaluative control processes indicate when control needs to be more strongly enga ged and signal to the dlPFC for increased attention allocation and top down support of task appropriate be haviors (Kerns et al., 2004; MacDonald et al., 2000). Much of the theoretical and empirical work related to cognitive control functioning has focused on impaired regulative processes and th eir association with impairments in the dlPFC and related circuitry. This is appropriate, as the frontal lobes a nd temporal poles are preferentially susceptible to damage followi ng TBI (Bigler, 1999), giving rise to the preponderance of cognitive control dysfunction s een due to focal frontal/prefrontal cortical contusions (Adams et al., 1980) or diffuse white matter injury that disrupts dopaminegic input to the prefrontal cortex (e.g., Adams, 1984; Ad ams et al., 1982). Several recent functional neuroimaging studies demonstrate al tered dlPFC activity in patients with mild (McAllister et al., 1999, 2001) and moderate-to-severe TBI (Cazalis et al., 2006; Christodoulou et al., 2001; Newsome et al., 2007; Perlstein et al., 2004; Scheib el et al., 2003) while they performed working memory tasks heavily dependent upon regulative control functions. Experimental cognitive neuroscience tasks designed to precisely is olate specific dlPFC-related regulative control processes are also reliably identifying TBI-rela ted dysfunction (Larson et al., 2006a; Levine et al., 2002; Perlstein et al., 2004, 2006; Seignourel et al., 2005). Speci fically, performance deficits

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14 in TBI patients relative to controls have b een identified on the AX-CP T task (Larson et al., 2006a), the n-back task (Perlstein et al., 2004) the cued-Stroop paradigm (Seignourel et al., 2005; Perlstein et al., 2006), and dual-task paradigms (Leclercq et al., 2000; McDowell et al., 1997), suggesting the presence of cognitive control deficits involving processes such as working memory, context maintenance, response inhibiti on, performance adjustme nt, and the ability to coordinate simultaneous performance of multiple task demands. In addition, studies employing traditional neuropsychological assessment methods have reliably identified TBI-related performance difficulties on traditional measures of dlPFC function, including the Stroop ColorWord Task (Bate et al., 2001; Ponsford & Kinsel la, 1992; Potter et al., 2002), Trail Making Test Part B (Rios et al., 2004), Wisconsin Card Sor ting Test (Leon-Carrion et al., 1998; Rios et al., 2004), and the Paced Auditory Serial Addition Test (Gronwall & Wrightson, 1981; Levander & Sonesson, 1998; Ponsford & Kinsella, 1992). Little attention has been paid to impaired evaluative component processes in TBI. We belie ve that many cognitive deficits in TBI are related to dysfunction in the evaluative process of monitoring and signa ling of errors/conflict, and that its remediation is important to the de velopment of future rehabilitation strategies. Cognitive control deficits in TBI are most debilitating outside the laboratory setting where complex demands are ubiquitous and fluid pe rformance adjustments critical. For example, many TBI survivors do well on automatic, well-re hearsed tasks yet experience tremendous difficulty when required to use flexible, novel approaches to solve new and complex problems (Levine et al., 2000). Insufficiencies in these proc esses may serve as a foundation for some of the most debilitating functional deficits following TBI, such as difficulty making decisions, performing complex tasks, dual-tasking, and planning (Anderson et al ., 2002; Bergquist & Jacket, 1993; Levine et al., 2002; Stuss & Gow, 1992). Based on these observations, one would

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15 expect cognitive control deficits as measured in the laboratory to correlate with functional impairment in TBI, particularly in domains of functioning requiring awareness of performance and adaptive thinking (see Perl stein et al., 2004, 2006 for exampl es). Thus, deficits in the monitoring and evaluation of conf lict should be manifest outside of the laboratory as difficulties recognizing discrepancies in actions and subsequent failures to adap t actions appropr iately to the situation (i.e., impaired deficit and performance awareness). Awareness of Deficits in TBI Several studies of moderate-to-severe TBI survivors document lack of awareness of cognitive deficits (Damasio & Anderson, 1993; Sher er et al., 1998; Toglia & Kirk, 2000), lack of insight into impaired interpersonal skills (Bergquist & Jacket, 1993), and impaired selfmonitoring of behavior (Stuss, 1991). Research suggests that up to 45% of individuals with moderate-to-severe TBI demonstrat e reduced or complete lack of awareness of their deficits (see Flashman & McAllister, 2002). Surv ivors of TBI who are unaware of their deficits may display a lack of motivation to change (Sherer et al., 1998), limited self-regulatory behaviors (Fleming & Strong, 1995), and decreased compliance in the rehabilitation setting (Allen & Ruff, 1990). Deficits in the detection of di fficulties may lead to poor performa nce and decreased recovery of function in the rehabilita tion setting. Awareness of deficit is a major factor in predicting overall rehabilitation outcomes, with decreased awar eness of deficits associated with worse rehabilitation outcomes (Sherer et al., 1998) a nd decreased likelihood of regaining employment (Hart et al., 2005). Some rese archers hypothesize poor functiona l outcomes associated with reduced awareness of deficits are associated w ith a lack of ability to detect and acknowledge problems in performance and make the necessary adjustments to perform activities accurately (Dirette, 2002).

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16 Awareness of deficits is a dynamic, rather than static, component of cognitive function following TBI (Noe et al., 2005; Toglia & Kirk, 2000). Thus, different variables may contribute to a patients awareness of deficits throughout the recovery process. Length of posttraumatic amnesia (PTA) is the only injury severity index that has been reliably associ ated with severity of deficits in awareness (Priga tano et al., 1998; Trudel et al ., 1998), although a recent study indicates that severity of injury is associated with impairments in deficit recognition (Sherer et al., 2005). This same study (Sherer et al., 2005) examined lesion location and severity in association with awareness of deficits. Findings indicate the number of brain lesions was predictive of degree of impaired awareness of de ficits; however, right hemisphere contusion or frontal lobe contusion volumes we re not predictive of degree of impaired deficit awareness. Emotional status (i.e., presence of mood or anxiet y disorder) is also associated with deficit awareness, as several studies indicate emotional st atus is inversely correlated with measures of deficit awareness (Ownsworth & Oei, 1998). Fo r example, Ownsworth and Oei (1998), in a review of the TBI literature, re ported improved awareness of defi cits is one of the strongest predictors of depression post-TBI and that Axis I psychopathology is increased in association with improvements in awareness. Furthermore, recent studies indicate increased awareness of deficits is associated with improved neurops ychological test performanceparticularly on measures of executive functioning and both ve rbal and spatial memory, higher levels of functional independence, and decreased psyc hopathological symptoms (Noe et al., 2005; Ownsworth et al., 2000, 2002). Awareness can be divided into two theoretica l categories, metacognitive knowledge and on-line abilities (Toglia & Kirk, 2000). Metacognitive knowledge refers to knowledge about ones own abilities, and implies knowledge from the present and pa st, as well as anticipating and

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17 planning for the future. On-line awareness is on going monitoring of actual task performance and implies identification of inappropriate task completion and subsequent adjustments in performance to complete the task successfully. In other words, metacognitive knowledge is what an individual brings to the task in terms of cognitive abilities and awareness of ones functioning, while monitoring reflects awareness of performance on a task and the ability to change strategies and adjust performance according to previous ex perience (i.e., performance monitoring; Toglia & Kirk, 2000). Both aspects of awareness are crucial to effective interactions with the environment. Deficits in metacognitive knowledge can lead to inappropriate expectations and goals, increasing the pote ntial for let down and subsequent decreases in emotional functioning. On-line monitoring of performance, on the other hand, is crucial to appropriate actions in the work environment, where repeated errors can lead to poor performance and potential termination, as well as impairments on everyday tasks that require activ e problem solving and confrontation of nove l situations. Utilizing neurobiological indices of evalua tive control (scalp-recorded event-related potentials [ERPs]) and measures of symptom expression and de ficit awareness, the studies presented below provide insight into the relationships betwee n evaluative control dysfunction, brain activity reflecting this dysfunction, and measures of deficit awareness. The specific aims of these studies were to, first, test the hypothesis that survivors of severe TBI exhibit impairments in behavioral and neurobiological manifestations of ACC-mediated evaluative control processes. We specifically predicted survivors of severe TB I would show impairment s in their ability to detect errors and response conf lict (i.e., when representations of more than one response are simultaneously activated) and subsequently show decrements in their ability to adjust performance to adapt to task demands. Since be havioral data alone do not address the potential

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18 neural underpinnings of impaired performance, we employed high-density ERPs to test the prediction that TBI surv ivors exhibit attenuated neural si gnals for measures of performance monitoring, conflict monitoring, and subsequent control adjustment. Second, we compared behavioral and neurobiologi cal indices of evaluative control to measures of deficit awareness in participants with TBI. We predicted cognitive co ntrol deficits as measured in the laboratory would correlate with deficits in the monitoring and evaluation of performa nce and abilities (i.e., deficit awareness). Finally, we examined TBI-relat ed changes in the evalua tive control ability to monitor and respond to feedback. We predicted surv ivors of severe TBI woul d exhibit deficits in the evaluative control process of reward contex t monitoring and, subsequently, show decrements in their ability to evaluate feedback and reward.

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19 CHAPTER 2 AWARENESS OF DEFICITS, PERFORMA NCE MONITORING, AND EVALUATIVE CONTROL FOLLOWING SEVERE TRAUMATIC BRAIN INJURY Individuals with severe traumatic brain inju ry (TBI) often demons trate impairments in performance monitoringan evaluative control pr ocess that can be meas ured using the errorrelated negativity (ERN) and post-error positiv ity (Pe). The ERN and Pe are event-related potential (ERP) components gene rated following errors, with cu rrent theories suggesting the ERN reflects automatic performance monitori ng and the Pe reflects error processing and awareness. To elucidate the elect rophysiological mechanisms of performance monitoring deficits following severe TBI, behavioral and ERP measur ements were obtained while participants with severe TBI and neurologically -healthy comparison participants performed a modified colornaming version of the Stroop task. Behaviorall y, both groups demonstrated robust RT and error rate interference; no significan t between-groups differences were noted. ERP results indicate ERN amplitude was attenuated in participants with TBI, while the pattern of Pe amplitude did not clearly differentiate groups. No meaningful relationships between ERN or Pe component amplitude and measures of deficit awareness were present. Results suggest the ERN as a potential electrophysiological marker of evalua tive control/performance monitoring impairment following TBI. Introduction Survivors of traumatic brain injury (TB I) frequently exhibit severity-dependent impairments in a number of cognitive domains, in cluding those that compromise the accuracy of action and performance monitoring. Impairments of th is type belong to a br oader constellation of deficits in the evaluative compone nt of cognitive control (Botvinick et al., 2001; Braver et al., 1999). Evaluative component processes include monitoring fo r the presence of response conflict

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20 (simultaneously activated competing responses ), monitoring performance for errors, and signaling the need to implement or adjust to p-down control processes. These evaluative functions are critical for flexible adjustment s of top-down control n eeded for adaptation to performance demands (e.g., correcting an error). The ACC plays a key role in the evaluative component of cognitive control (Gehring & Fencsi k, 2001; Kerns et al., 2004; MacDonald et al., 2000; Miltner et al., 2003; va n Veen & Carter, 2002a, 2002b). Dysfunction of ACC-mediated evaluative contro l processes has direct implications for survivors of brain injuries. For example, animal research demonstrates ACC lesions alter the normal pattern of corrective behavior following e rrors, such that consecutive errors without appropriate correction are more common (Dia s & Aggleton, 2000; Rushworth et al., 2003; Walton et al., 2003). Similar evidence comes from a human patient with a rare focal lesion of the rostral-to-middorsal ACC who was le ss likely than healthy controls to correct mistakes (Swick & Turken, 2002). In participants with TBI, wher e axonal shearing may be prominent in medial frontal regions, little research has examined th e neural instantiation of evaluative control functions. One PET study suggested abnormalities of ACC glucose metabolism at rest in participants with TBI that corr elated with subsequent neuropsy chological performance (Fontaine et al., 1996), an fMRI study using the Stroop task found a relative decrease in ACC activity in participants with TBI compared with controls (Soeda et al., 2005), an fMRI study reported impaired ACC activity in TBI survivors with pr oblem solving deficits (Cazalis et al., 2006), and recent studies from our lab observed ACC dysfu nction in survivors of severe TBI during performance of a task requiring working memory (Perlstein et al., 2004 ), and a diminished electrophysiological reflection of evaluative control, presumably mediated by the ACC (i.e., N450 component of the scalp-record ed event-related potential [ERP]) in a single-trial version of

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21 the Stroop task; Perlstein et al ., 2006). A growing consensus fro m these studies is that ACCmediated changes following TBI are the result of diffuse axonal damage that disturbs frontocortical and subcortical networ ks leading to subsequent ev aluative control impairment. The physiological and cognitive bases of evaluati ve control have been the subjects of many recent investigations. One putative reflection of the evaluative process of performance monitoring is an electrophysiol ogical signature in the scalp re corded ERP known as the errorrelated negativity (ERN). The ERN is a front o-medial maximal response-locked potential peaking within 100ms after the commission of an error (Falkenstein et al., 1991). The precise cognitive mechanisms generating the ERN ar e under active debate (Holroyd & Coles, 2002; Yeung & Cohen, 2006), but have been attributed to detection of response c onflict (Carter et al., 1998), detection of errors (i.e., mismatch be tween an intended a nd produced response; Falkenstein et al., 1991; Gehring et al., 1993), or an emotional res ponse to errors (Larson et al., 2006b; Vidal et al., 2000). Source localization ER P as well as fMRI studies consistently implicate a region in the dorsal ACC as the prim ary neural generator of the ERN (van Veen & Carter, 2002a). Although the ERN has received considerab le attention in electrophysiological investigations of performan ce monitoring, researchers also examined a positive deflection occurring between 100 and 400ms following the ERN known as the post-error positivity (Pe). The functional significan ce of the Pe remains controversial (Overbeek et al., 2005); however, the Pe can be differentiated from the P300 (Falkenste in et al., 2000) and may be associated with conscious error recognition, as it is diminished when subjects are unaware of performance errors (Nieuwenhuis et al., 2001). Moreover, post-error RT slowing occurs only on trials that exhibit an

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22 observable Pe (Mathalon et al., 200 2), and Pe amplitude varies in relation to the degree of posterror slowing and autonomic nervous sy stem activity (Hajcak et al., 2003a). Awareness of Deficits, Performance Monitoring, and TBI Several studies of TBI survivors document lack of awareness of cognitive and physical deficits (Damasio & Anderson, 199 3; Sherer et al., 1998; Sherer et al., 2 005; Toglia & Kirk, 2000). One important aspect of awareness abilit ies is that of mon itoring performance and implementing strategic adjustments when current performance is inadequate. Stemmer et al., (2004) examined overt behavioral signs of error responses (e.g., exclamations, swearing, grimaces) during a flanker task and found that thr ee of five stroke patients who experienced anterior communicating artery (ACA) aneurysms and subsequent lesions to the medial PFC, including the ACC, demonstrated poor ability to monitor performance. This study utilized ERPs to examine error-related neural activity; findings indicate decreased errorrelated neural activity in the individuals with lesions to the medial PFC. Of note, some patients were aware of errors but did not produce a discernable Ne/ERN. Another study examined error awareness in ever yday situations, such as wrapping a gift or packing a schoolbag. TBI patients showed less awareness and corrected significantly fewer errors than control participan ts (Hart et al., 1998). OKeeffe and colleagues (2004) utilized measures of electrodermal activity to examine autonomic respons es to errors in TBI participants. TBI participants detected significantly fewe r errors on the task than matched-control counterparts. In addition, elec trodermal activity following erro rs was decreased in the TBI participants relative to controls, with error detection rates and elec trodermal activity being significantly correlated. Findings in dicate TBI participants exhibit impairments in the evaluative process of conflict detection a nd processing, leading to impaired performance of error-related conflicting information and poor adjustments in pe rformance (O'Keeffe et al., 2004). No studies

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23 to date have examined the elec trophysiological instantiations of performance monitoring deficits in survivors of severe TBI or the relationshi p of evaluative control dysfunction with deficit awareness in these individuals. Given the im portant role that ACC-mediated conflictdetection/performance monitoring processes appear to play in signaling for the recruitment of regulative control mechanisms and the prevalence of deficits in awareness, it is important to characterize the functioning of such a process in survivors of TBI. Current Study The primary aims of the current study were to extend previous findings of impaired performance monitoring in survivors of severe TBI and determine if electrophysiological indices of evaluative controlthe ERN and Pe components of the scalp-recorded ERPare attenuated following severe TBI and if these ERP components are related to awareness of deficit. We predicted that TBI par ticipants would show smaller-amp litude electrophysiological activity (ERN) to error, relative to correct trials, comp ared to neurologically h ealthy controls, and that ERN amplitude would correlate with deficit awarene ss, such that larger ERN is associated with increased awareness of deficit. Additionally, we te sted the hypothesis that the Pe is related to awareness of deficit, as previous studies of th e Pe have shown a specific relationship between Pe amplitude and awareness of performan ce errors (Nieuwenhuis et al., 2001). Methods Participants with severe TBI were recrui ted from two Northern Florida trauma and rehabilitation hospitals; control participants were recruited via flyer and advertisement from the local community. Study enrollment initially incl uded 21 participants with severe TBI and 21 healthy control participants. ERP data for one pa rticipant with TBI were lost due to equipment malfunction and one TBI participan t performed the task incorrectly (i.e., responded to the word rather than the color for every tr ial); therefore, final analyses in cluded 19 participants with severe

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24 TBI and 21 healthy control participants. All par ticipants provided written informed consent according to procedures established by the Univ ersity of Florida Health Science Center Institutional Review Board and were compensated for their participation. TBI severity was determined from medical r ecord review of lowe st post-resuscitation Glasgow Coma Scale (GCS) score (Teasdale & Je nnett, 1974), with severe TBI defined as a GCS score < 9. Neurological indi ces, including neuroradiologica l findings taken from acute computerized tomography (CT) scans, duration of loss of consciousness (L OC), and duration of post-traumatic amnesia (PTA), were also acquire d from medical record review or, when LOC and PTA information were not available in medi cal records, from structured participant and significant other interview (Ki ng et al., 1997; McMillan et al., 1996). LOC and PTA data confirmed all TBI participants met criteria for severe TBI as traditionally defined by LOC > 6 hours and/or PTA > 7 days (Bigler, 1990; Bond, 1986; Lezak et al., 2004). All participants were screened for major ps ychiatric disorder usi ng the Mental Health Screening Form-III (MHSF-III; Carroll & McGinley, 2000, 2001). The MHSF-III provides excellent inter-rater reliab ility (> .95), good internal consistency (Cronbachs > .83), and good construct validity (87% rate of agreement be tween independently assigned mental health diagnoses and endorsed items on the MHSF-III; Carroll & McGinley, 2001). In addition, the MHSF-III is useful as a screening instrument because it is quite brief, consisting of 18 questions, and can be administered in approximately 15 minutes. Potential participants were excluded from the study if they endorsed a history of psychotic or bipolar disorder, learning disa bility, alcohol or substance abus e, other acquired brain disorders (e.g., epilepsy, stroke), inpatient psychiatric treatment predat ing brain injur y, clinicallysignificant depression or anxiety currently or within two y ears prior to injury, current anti-

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25 epileptic medication use, or color-blindness as measured by the Ishihara pseudo-isochromatic color plates (Clark, 1924). Partic ipants with language comprehe nsion deficits or uncorrected visual impairments were also excluded. Demographic characteristics and neuropsychol ogical test summary data for control and TBI study participants are provided in Table 21. Injury characteristics (etiology, GCS, LOC, PTA, time since injury) and ne uroradiological findings for th e participants with TBI are presented in Table 2-2. Survivors of severe TBI we re at least four months post-injury, with the exception of one TBI survivor (two months postinjury) who was functioning well and desired to complete the study early before returning to empl oyment responsibilities. No participants were engaged in legal action at the time of the study. Participant groups were comparable in age and education (see Table 2-1); groups did not si gnificantly differ in gender distribution 2(1)=2.16, p >.14 (TBI: 15 male/4 female; Control: 12 male/9 female). Since previous studies demonstrate differences in ERN amplitude as a function of de pressive or anxious symptoms (Hajcak et al., 2003b; Ruchsow et al., 2004; Ruchsow et al., 20 06), TBI and control participants were administered the Beck Depression Inventory-2nd Edition (BDI-II; Beck, 1996), a modified version of the Apathy Evaluation Scale (Marin, 1991; Marin et al., 1991; Starkstein et al., 1992), and the State-Trait Anxiety Inventory (STAI; Sp eilberger et al., 1983). Co mpared to controls, participants with TBI endorsed significantly mo re depressive symptoms ; however, no individual scores met common clinical cut-offs for moderate depression (BDI-II > 21) and mean scores for both groups were within normal limits not mee ting criteria for minimal depression (BDI-II > 13; see Beck, 1996). Groups did not differ on their report of apathy symptoms, but participants with TBI endorsed higher levels of state and trait anxiety symptoms.

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26 Assessment of TBI Symptoms and Deficit Awareness In an effort to characterize the cognitive f unctioning of participants with TBI, a brief battery of neuropsychological test s was administered to all partic ipants. Measures administered included the Digit Span forward and backward su btests from the Weschler Adult Intelligence TestThird Edition (WAIS-III; Wechsler, 1997), Trail Making Test Parts A and B (Reitan, 1958), the Controlled Oral Word Association Test [COWAT] and Cate gory Fluency (Benton & Hamsher, 1976), the Hopkins Verbal Learning Te st--Revised (HVLT-R; Brandt & Benedict, 2001) and the Wechsler Memory Scale-Revised (WMS-R) Logical Memory I and II subtests (Wechsler, 1987). Order of neuropsychological ta sk presentation was counterbalanced across participants, with the exception of the WMS-R that was presented first and last to allow adequate time for the long-recall delay (see below). Br ief summaries of each measure utilized are presented below. Digit span forward and backward. In the digit span forw ard test of the WAIS-III, increasingly longer strings of numbers are recalled (1-9 letters). In the backward version, subjects repeat the numbers in reverse order. Span length is de fined as the numbers of digits recalled correctly before two string s of the same length were failed Reliability estimates of the Digit Span range from 0.84 to 0.93 and its correlation with the working memory index of the WAIS-III was estim ated at 0.83 in a normative sample (Wechsler, 1997). Trail Making Test parts A and B. Trail Making Test parts A and B are well-documented measures of visual scanning, pr ocessing speed, and task switchi ng (Lezak et al., 2004). The Trail Making Test consists of two parts. In Part A, participants connect consecutively numbered circles, while in Part B, participants connect consecutively numbered and lettered circles that alternate between the two sequences. Psychometric st udies indicate reliability coefficients above

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27 .80 (Spreen & Strauss, 1991), and several studies indicate that the two Trail Making tests are sensitive to the global effects of brain injury (Botwinick et al., 1988; Buchanan et al., 1994); Trail Making Test Part B is repor ted to be specifically sensitive to prefrontal dysfunction because of the requirement to shift se ts (Butters et al., 1994). Controlled Oral Word Association Test (COWAT) and Category Fluency (Animals). In the COWAT, participants are asked to produce as many words as possible that begin with the letters F,A, and S in one minute. Participants are instructed to avoi d using proper names and words that are only changed based on different suffixes (e.g., eat, eating). Similarly, for semantic or category fluency participants are asked to na me as many animals as possible in a one minute time period. Thus, fluency measures require efficient organization of verbal retrieval and recall as well as self-monitoring aspect s of cognition, self-i nitiation, and inhibitio n of inappropriate responses (Henry & Crawford, 2004). A recent me ta-analysis indicates fluency measures are more sensitive to the presence of severe TBI than the Wisconsin Card Sorting task (Henry & Crawford, 2004). WMS-R Logical Memory I and II. Logical memory is a test of paragraph or passage recall that consists of two stor ies, each containing 25 items of information. For Logical Memory I participants are asked to immediately recall th e passages after each reading to assess verbal memory, while Logical Memory II asks for a re call of the passages approximately 30-minutes later. Reliability es timates are .74 for Logical Memory I and .75 for Logical Memory II (Wechsler, 1987). Hopkins Verbal Learning Test-Revised. The HVLT-R is a measure of list-learning memory that consists of one 12-item word list th at can be semantically grouped into categories. The list is presented such that words from th e same category do not occur in sequence and

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28 participants are not informed of the semantic stru cture. Three initial learning trials are presented, with a total learning score calcu lated by adding trials 1 through 3. After a 20-minute delay, longdelay free recall and a forced choice recognition trial are administered. The HVLT-R has modest reliability estimates across shortand l ong-delay recalls (> .49; Woods et al., 2005). As presented in Table 2-1, and consistent with typical impairments s een after severe TBI, participants with severe TBI performed significantly worse th an controls on tests broadly assessing attention (Digit Span Forward fr om the WAIS-III), processing speed (Trail Making Test Part A), verbal fluency (COWAT and category fluency), executive functioning (Trail Making Test Part B; Digit Span Backward from the WAIS-III), and delayed verbal memory (HVLT-R long delay and WM S-R Logical Memory II). In contra st, participants with TBI did not differ from controls on the ini tial encoding/immediate recall of verbal memory information (HVLT-R immediate recall/WMS-R Logical Memory I). Two independent measures were used to assess selfand significant other-reported clinical symptomatology and quantify level of deficit awareness: 1) the Frontal Systems Behavior Scale (FrSBe; Grace & Malloy, 2001); and, 2) the Se lf-awareness of Deficits Interview (SADI; Fleming et al., 1996). The FrSBe is a 46-item be havior rating scale originally designed to measure behavioral change associated with frontal lobe injury. Each item is rated on a one to five point Likert-type scale, with one indicating almost never a nd five almost always. Thus, higher scores indicate more TBI-related symp toms. The FrSBe gathers information regarding preand post-injury behaviors from the partic ipant (self-report) and a significant other and includes an overall composite score and three subscales that assess ap athy, disinhibition, and executive function and shows adequa te reliability (inter nal consistency 0.96; split half 0.93) and validity (Grace & Malloy, 2001). Significant others who completed ratings in the current study

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29 were the primary caregivers of the participan ts with TBI and included eight spouse/fiance, seven parents, two siblings, one grandparent, and one aunt. Aware ness of deficits was initially calculated by computing a concordance between selfand other-reported FrSBe responses and taking the absolute value of the difference scor e from selfand other-ratings. To account for participants who were possibly hype rvigilant to their deficits (i.e ., greater selfth an other-report of deficits), subsequent analyses utilized only those participants with positive concordance scores (i.e., greater otherthan self-re ported deficits). The concor dance score method is commonly utilized in the self-awareness literature and is considered a sensitive measurement of selfawareness following TBI (see Hart et al., 2003 for review). The SADI is a nine-question structured inte rview given to participants with TBI that facilitates questioning in three areas: 1) self-awa reness of deficit, 2) se lf-awareness of functional implications of deficit, and 3) ability to set rea listic goals. Scores for these areas are combined to produce a composite self-awareness score. The S ADI exhibits high inter-r ater reliability (>.82; Fleming et al., 1996), test-retest reliability (0.94; Simmond & Fleming, 2003), can accurately discriminate TBI participants based on severi ty of injury (Bogod et al., 2003), and is highly correlated with measures of executive function, including Go -No-Go and Stroop Color-Word task errors (Bogod et al., 2003). Experimental Task Participants performed a modified color-nami ng version of the singletrial Stroop task. In this task, participants are pres ented with one of three words (RED, GREEN, BLUE) printed in one of the same three colors. Congruent trials co mprised words presented in their same color of ink (e.g., the word BLUE printed in blue ink); in congruent trials comprised color-words printed in a different color of ink (e.g., the word BLUE pr inted in red ink). Participants were instructed to respond as quickly and accurately as possible to the color of the word (while ignoring the

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30 word itself) with a button press to one of th ree color-coded response keys using the index, middle, and ring fingers of their right hand. Colo r-to-key mapping was practiced prior to task performance using 40 presentati ons of each color-key combination. Stroop trials were three seconds in duration and consisted of a Stroop color-word presented for 1.5s followed by a 1.5sduration fixation cross to allow electrophysiological activity to return to ba seline. Six blocks of 100 trials, for a total of 600 trials and approxima tely 30 minutes in EEG testing were presented. To increase the potency of the conflict stimulus, 70% of trials were congruent (approximately 420 trials) and 30% were incongrue nt (approximately 180 trials). Electrophysiological Data Recording, Reduction, and Measurement Electroencephalogram (EEG) data were reco rded from 64 scalp sites using a geodesic sensor net and Electrical Geodesi cs, Inc., (EGI; Eugene, Oregon) amplifier system (20K gain, nominal bandpass=.10-100Hz). Electr ode placements enabled record ing vertical and horizontal eye movements reflecting electro-oculographic (EOG) activity. Data from the EEG were initially referenced to Cz and digitized continuously at 250Hz with a 16-b it analog-to-digital converter. A right posterior electrode approxi mately two inches behind the ri ght mastoid served as common ground. Electrode impedance was maintained below 50k Electroencephalographic data were segmented off-line and single trial epochs were re jected if voltages exceeded 100V, transitional (sample-to-sample) thresholds were greater than 100V, or eye-channel amplitudes were above 70V. Data were digitally re-referenced to an av erage reference (Bertrand et al., 1985) in order to yield a reference-free representation of elect rophysiological activity and to reconstruct the EEG at the Cz reference, then digitally low-pass filtered at 15Hz. Individual-subject response-loc ked averages were derived separately for correct and incorrect trials, collapsed across congruency to afford adequate signal -to-noise ratio, spanning

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31 200ms prior to and 500ms following response a nd baseline corrected using the 200ms preresponse window. ERP trials containing errors of omission were excluded from averages. Electrode locations utilized were based on previ ous findings that the ERN and Pe are relatively focal over fronto-medial locations and centro-parietal areas, resp ectively (Falkenstein et al., 2000; Gehring et al., 1993), as well as the scalp-distribution maps of the present data. To ensure accurate characterization of ERN amplitude and prevent spurious findings as a result of potential group-wise latency differences, ERN amplitudes as well as the corresponding correct-trial amplitudes were extracted as the average of 15ms preto 15ms post-peak negative amplitude between 0ms and 100ms and averaged across four fronto-central electrode sites (FCz), 65 (Cz), 5, and 55 (both sites ante rior and slightly lateral to Czsee Figure 2-1). Latency measurements for the ERN component were inde xed as the time of the peak negative-going amplitude averaged across the four fronto-central electrode locations. Given previous findings that the Pe is found at centropari etal electrode locations and is less punctate and more tonic than the ERN (see Overbeek et al., 2005), Pe amplitude was measured as the averaged activity from 200ms 400ms of five centroparietal electrode sites (65 [Cz], 18, 43, 30, and 34 [Pz]; Figure 2-1). Data Analysis Median correct-trial RT (Rat cliff, 1993), arcsine transforme d error rates (Neter et al., 1985), and ERP component amplitude and latency da ta were analyzed using separate repeatedmeasures analyses of variance (ANOVAs). In order to correct for po ssible violations of sphericity in the data, the Huynh-Feldt epsilon adjustment was applied for ANOVAs with more than two levels of a within-s ubject factor and partial-eta2 ( 2 ) reported as a measure of effect size. ANOVAs for RTs and error rates included th e factors group (TBI, control) and congruency

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32 (congruent, incongruent), while ANOVAs for e rror-related ERP activity included the factors group and accuracy (correct, inco rrect trial amplitudes). Tests of between-group simple effects were used to decompose interactions, while pl anned comparisons were used to examine the accuracy factor within each group. Cohens-d effect sizes (Cohen, 1988) were calculated for condition-related effects. Pear son-product-moment correlations (one-tailed) examined relationships between task performance and the difference between correctand error-trial ERP amplitudes (e.g., error-trial Pe amplitude correct trial Pe amplitude) with measures of deficit awareness (SADI and FrSBe concordance score) in TBI participants. In an effort to control for TBI participant who may have been hypervigilant to deficits we also recomputed the correlations including only those participants with only positive, rather than absolute value, FrSBe concordance scores (i.e., higher signif icant other than TBI survivor scores). Results Behavioral Data Stroop task behavioral performance. Overall RTs and error rates for the Stroop task (Table 2-3) were not significantly correlated in control participants, r (20)=-0.17, p >.47, but were significantly positively correlated in participants with TBI, r (18)=.47, p <.04. Results suggest speed/accuracy trade-off did not influence contro l or TBI participants, as a positive correlation indicates longer RTs were associated with incr eased error rates, opposite the direction suggestive of a speed/accuracy trade-off. Error rates. Control and TBI participant groups di d not differ on total number of raw errors, t (38)=1.54, p >.13, d =.49; participants with TBI averaged 48.79 74.75 errors, while controls averaged 23.10 16.53 errors. Similarly, groups did not reliably differ on the number of

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33 omission errors, t(38)=1.13, p>.27, d=.36. Participants with TBI committed an average of 13.52 25.21 omission errors, while contro l participants averaged 6.40 13.38 omission errors. A Group x Congruency ANOVA on arcsine-tr ansformed error rates yielded only a significant main effect of congruency, F (1,38)=83.68, p <.001, 2 =.69, reflecting si gnificant error rate interference, with both groups committing more errors to the incongruent than congruent condition, as revealed by planned contrasts (TBI: t (18)=6.37, p <.001, d =.58; controls: t (20)=6.57, p <.001, d =1.34). Neither the main effect of group, F (1,38)=2.21, p >.15, 2 =.06, nor the Group x Congruency interaction, F (1,38)=1.47, p >.23, 2 =.04, were significant. Response times. A Group x Congruency ANOVA on RTs revealed the expected generalized slowing in participants with TBI, as reflected in a significant main effect of Group, F (1,38)=11.75, p <.001, 2 =.24. Paralleling the erro r rate data, a main effect of congruency reflected the anticipated RT interference, F (1,38)=73.19, p <.001, 2 =.66, with both groups showing longer RTs to the incongruent than congruent condition (TBI: t (18)=4.97, p <.001, d = .97; controls: t (20)=9.43, p <.001, d =1.04). The Group x Congruency interaction was not significant, F (1,38)=0.84, p >.37, 2 =.02, indicating the two groups s howed equivalent levels of RT interference. ERP Data: Response-related Activity We first examined the number of trials re tained for each condition to test for betweengroups differences in signal-to-noi se ratio (SNR). Controls and su rvivors of severe TBI did not differ on number of trials retain ed for averaging in correct, t (38)=0.55, p >.59, d =.17, or error conditions, t (38)=-1.24, p >.22, d =.39. Response-locked correct-tri al waveforms contained an average ( SD) of 401.1 132.9 trials for participants with TBI and 422.5 116.1 trials for controls, while response-locked error waveforms contained an average of 23.1 33.96 trials for

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34 participants w ith TBI and 13.7 7.9 trials for controls. Respon se-locked grand average ERP waveforms and spline-interpolated voltage maps for correct and error response-locked trials reflecting the fronto-medial ERN are shown in Fi gure 2-2, while those for the centro-parietal Pe are shown in Figure 2-3. Mean ( SD) component amplitude data are presented in Table 2-4. ERN As anticipated, response-lock ed ERPs showed an early negative deflection that was larger in amplitude to error than correct trials in both groups, as confirmed by a Group x Accuracy ANOVA, which yielded a signi ficant main effect of accuracy, F (1,38)=41.09, p <.001, 2 =.52, and significant correctvs. error-tria l planned contrasts in both the TBI, t (18)=2.62, p <.02, d =.70, and control participants, t (20)=6.12, p <.001, d =1.65. More importantly, a significant Group x Accu racy interaction, F (1,38)=12.99, p <.001, 2 =.26, reflected greater amplitude differences between corr ectand error-related negativities in control than participants with TBI. Follow-up contrasts revealed the error-trial ERN was reliably larger in the control participants than the surv ivors of severe TBI, t (38)=2.65, p <.01, d =.83. The ERP related to correct responses (correct -response negativity; CRN) did not differ between groups, t (38)=1.69, p >.10, d =.54, suggesting a degree of specificity in the error-related differences. Furthermore, the Group x Accuracy interaction was found in the ab sence of an overall main effect of group on ERP component amplitude, F (1,38)=2.58, p >.12, 2 =.06. Pe. The Group x Accuracy ANOVA on the centro-pa rietal Pe revealed a significant main effect of accuracy, F (1,38)=45.12, p <.001, 2 =.54, reflecting a more positive-going Pe on error than correct-trials in both the TBI, t (18)=4.84, p <.001, d =1.26, and control participants, t (20)=4.91, p <.001, d =1.22; the Group x Accuracy inte raction was not significant, F (1,38)=1.67, p >.20, 2 =.04. Subsequent tests of simple effects i ndicated the Pe significantly differed between groups on error, t (38)=1.97, p =.05, d =.61, but not correct trials, t (38)=.60, p >.55, d =.18. These

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35 results are difficult to interpret in the absence of a significant interaction effect and due to the relatively small sample size. Similar to the ER N, the main effect of group on Pe component amplitude was not significant, F (1,38)=2.52, p >.13, 2 =.06. Peak latencies A Group x Accuracy ANOVA yielded no significant main effects or interactions involving error-re lated component latencies (p s>.09). Correlational Analyses In addition to examining error -related ERP activity in TBI surv ivors, an important goal of the current study was to determin e if electrophysiological reflectio ns of performance monitoring correlate with measures of deficit awareness. Pe amplitude (difference between Pe on wrong and correct trials) inversely correlate d with deficit awareness as m easured by the FrSBe concordance score, r (17)=-.48, p <.02; Pe amplitude did not significan tly correlate with SADI score, r (18)=.04, p >.40. ERN amplitude (difference between erro r and correct-trial waveforms) did not correlate with either FrSBe conc ordance score or SADI score, r s<.02, p s>.47. No significant correlations were noted for either the Pe or the ERN when only TBI survivors with positive concordance scores (i.e., hi gher otherthan self-report scores) were included, r s<.39, p s>.12, or when only the amplitude of error-trial ERN and Pe waveforms were included, r s<.34, p s>.09. Discussion Results of the current study were largely consistent with our primary prediction that participants with TBI would s how a reduced-amplitude ERN on error relative to correct trials-reflective of an impaired neural mechanism of error detection or performance monitoring. Notably, participants with TBI did, on averag e, demonstrate a clearly discernable ERN, suggesting that, while error-related performance monitoring was impaired, it was not completely absent. Additionally, the finding th at the control and TBI groups did not significantly differ in correct-trial ERP amplitudes or the overall magnitude of response-related ERP amplitudes

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36 provides some evidence for specificity of the ER N reflection of performance monitoring deficits and indicating the difference does not reflect a mo re generalized decrement of response-locked ERP amplitudes in the TBI survivors. We also observed a discernable positive-goi ng deflection following the ERN in both TBI and control participant groups. Th is more phasic component, routin ely referred to as the Pe, is thought to be closely related to automatic mon itoring of response conflic t and error processing (van Veen & Carter, 2002a). A lthough both TBI and control part icipants showed a significant difference in Pe amplitude between correct and error trials, there was not a significant Group x Accuracy interaction. Thus, despite the significan t difference between cont rol and participants with TBI on subsequent contrasts for error, bu t not correct trials, no firm conclusions can currently be drawn about Pe amplitude in severe TBI, particularly in light of the small sample size employed. Correlations between two different measures of deficit awareness and the difference between correct and error trial component amplitude for the ERN and Pe yielded a pattern that initially appeared congruent with previous lite rature suggesting Pe am plitude is related to awareness of errors (Nieuwenhuis et al., 2001). Th is was a single, one-tailed correlation that included the absolute value of scores for both TBI survivors who were less aware of their deficits (i.e., positive concordance score) and those that we re hypervigilant to their deficits (i.e., negative concordance score). It is possibl e that this single correlation is a chance finding given the number of correlations and the small sample size. This, coupled with the lack of a relationship between Pe amplitude and the SADI, casts significant doubt on the meaningfulness of the correlation and no speculations about the relationship between Pe amplitude and deficit awareness are drawn

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37 from the current results. Similarly, no relati onship was found between measures of deficit awareness and ERN amplitude. Several explanations of the lack of re lationship between ERN and Pe component amplitudes and deficit awareness are possible. Fi rst, the exact mechanisms of the Pe and ERN remain quite controversial (Holroyd & Coles, 2002; Overbeek et al., 2005; Yeung & Cohen, 2006). Previous studies suggesting Pe amplitude varies as a function of error-awareness primarily utilized an anti-saccade task and r eal-time ratings of wh ether an error occurred (Niewenhuis et al., 2001). The current study examin ed the more general co nstruct of awareness of deficits following brain injury, but did not ex plicitly examine real-tim e awareness of errors during task performance. The Pe could be relate d to real-time awareness of errors and neither the ERN nor Pe is sensitive to awareness of pe rformance over an extended period of time (i.e., awareness of level of functioning). A more likely explanation is the measurement of deficit awareness utilized in the current study. Utilizing absolute values between the selfand other-rati ngs on the FrSBe did not take into account TBI survivors who we re hypervigilent to th eir deficits and, thus, scored higher than the other-ratings. Taking this in to account led to the exclusion of 7 TBI participantsleaving the study underpowered to detect a rela tionship if it was present. Sim ilarly, the use of the SADI was not ideal in the present circumstances as it reli es on a vast knowledge of the participants functioning (e.g., the knowledge of a rehabilitation specia list who works closely with the patient on a regular basis) that the exam iner did not have due to the si ngle-visit, cross-sectional design of the study. Future studies should employ a larg er sample with a more valid measurement of deficit awareness (e.g., the Awareness Questionnaire ; Sherer et al., 1998) to reduce measurement error and improve the chances of finding the relationship if presen t. Finally, it is also possible

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38 that there is not a relationship between elec trophysiological manifest ations of evaluative control/error-processing and defic it awareness; however, it is pr emature to draw any specific conclusions from the current data. Results of this study suggest important impli cations for clinical a pplication and future research. First, the pursuit of effective rehabili tation and compensatory st rategies is dependent on accurate cognitive assessment and detailed understanding of the mechanisms underlying TBIrelated impairment. The current study, reflecti ng the first examination of electrophysiological marker of performance monitoring in TBI, suggests a possible experimental method and electrophysiological marker for examining the behavioral and neurobiological changes in performance monitoring abilities in response to rehabilitation. Second, results suggest a continued need for emphasis on rehabilitation of performance monitoring deficits following TBI. Few empirically supported treatments currently exist that target such deficits, though investigators are currently working to validat e potential treatments in this domain (see Ownsworth et al., 2006). Finally, future studies should further address th e potential link between performance monitoring decrements and impair ments in deficit awareness. For example, OKeeffe et al. (2004) found attenuated electrode rmal response to errors following TBI as well as a relationship between perfor mance monitoring abilities (erro r awareness) and amplitude of the error-related electrodermal re sponse. Utilization of an electrophyiological marker, such as the ERN, in studies of performance monitoring a nd deficit awareness may provide much needed clarification on the neural mechanisms underl ying impairments in deficit awareness. Findings of the current study must be consider ed within the context of several potential limitations and alternativ e explanations, in addition to the ERP-related factors mentioned above. The task paradigm employed precluded our ability to unambiguously examine participants

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39 facility to make reactive strategic adjustments following the commission of errors, such as posterror trial RT slowing, due to the probability di stribution of congruent and incongruent trials (i.e., the preponderance of partic ipant commission errors occurre d in the incongruent condition and were followed by congruent trials due to the 70% congruen t/30% incongruent proportion of trials employed; thus, post-error slowing was not evaluated as pa rticipants traditionally respond faster to congruent than incongr uent trials). Post-error strategi c adjustments, or the so-called Rabbitt effect (Rabbitt, 1966, 1968) have often been taken to reflect participants top-down adjustments in performance strategy, perhaps reflecting the dynamic interplay between ACCmediated evaluative and dlPFC-m ediated regulative processes (Bot vinick et al., 2004; Kerns et al., 2004). Nonetheless, our earlier behavioral st udy using a different task, demonstrated that participants with TBI were impaired in post-e rror RT slowing relative to healthy participants (Larson et al., 2006a). That is, relative to neurologically-normal comparison subjects, they showed smaller magnitude post-error slowing, suggestive of reduced post-error strategic adjustments in cognitive control. Another potential limitation is that the curr ent data indicate generalized slowing in participants with TBI that was not present for co ntrol participants. The potential variability in ERP component latency, often refe rred to as latency jitter, associated wi th variable response times may serve to spuriously reduce component amplitudes. Previous research also indicates individuals who respond more quickly at the ex pense of accuracy show smaller ERN amplitude than those who attend more to accuracy than speed (Ruchsow et al., 2005); however, the direction of the correlation betw een speed and accuracy in partic ipants with TBI suggests those who made more errors were taking longer to re spond to stimuli. Finall y, as a consequence of their impairment, participants with TBI committed significantly more errors on the Stroop task

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40 than the neurologically healthy control participants. Since the error-related ERP data were dependent upon error rates, the TB I group contains nearly twice as many trials included in the ERP averages than controls, increasing the signal-to-noise ratio in TBI participants and potentially making the error-related ERPs in the TBI group more reliable than those for control participants. It should also be noted that despite the higher state and trait anxiety levels in the participants with TBI relative to controls, ERN amplitude was still reduced in the participants with TBI. Previous studies demonstrate that anxiety enhances ERN (Hajcak et al., 2003b) and higher anxiety in the TBI group would appear to work in opposition to our hypothesis of reduced error processing in participants with TBI. Th at is, despite the higher anxiety scores in participants with TBI, a Group x Accuracy interaction was, none theless, observed for the ERN. Depression, on the other hand, is associated with decreased ERN amplitude (Ruchsow et al., 2004). The finding of group differences in depre ssion score may suggest that the level of depression in participants with TBI influenced findings of reduced ERP amplitude; however, depression scores for both groups were in the subc linical range and the la ck of change in the pattern of significance for the ERN and Pe compone nts when depression a nd anxiety scores were added as covariates indicates findings cannot be wholly accounted for by these variables. The present findings implicate an impair ed performance monitoring mechanism in survivors of severe TBI. Thus, the present st udy fits well into a gr owing body of research indicating impaired performance monitoring follow ing severe TBI and emphasizes the need for continued specific examination of this dysf unction and the developm ent and validation of remediation or compensatory treatments.

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41 Table 2-1. Demographic and mean summary data for severe TBI and control participants Severe TBI (n = 19) Control (n = 21) Analysis Mean SD Mean SD t p Cohens-d Age (yrs) 30.412.125.49.51.5 .15 .46 Average educational level (yrs) 13.31.714.11.3-1.7 .09 .53 BDI-II score 12.35.83.72.96.0 .001 1.91 Apathy evaluation scale 11.35.48.64.01.8 .08 .57 STAI-state 34.48.826.75.93.3 .002 1.04 STAI-trait 37.510.930.46.92.5 .02 .79 FrSBe self-rating total 98.525.370.423.13.4 .002 1.16 Apathy 28.99.223.96.81.8 .07 .62 Disinhibition 31.68.625.76.02.3 .03 .80 Executive dysfunction 38.010.535.520.10.5 .65 .15 FrSBe other-rating total 108.328.2-------Apathy 31.68.7-------Disinhibition 32.810.1-------Executive dysfunction 43.911.7-------FrSBe self/other concordance 21.525.3-------SADI 3.92.0-------HVLT total recall (trials 1-3) 21.25.224.14.4-1.8 .08 .60 HVLT long-delay recall 6.73.28.91.9-2.5 .02 .85 WMS-R logical memory I total 22.58.124.66.9-0.9 .37 .28 WMS-R logical memory II total 15.78.220.97.7-2.1 .04 .65 Digit span forward (max# of digits) 6.11.57.11.3-2.4 .02 .72 Digit span backward (max# of digits) 4.41.25.31.2-2.6 .01 .75 Trail making test part A (seconds) 31.417.621.86.82.3 .03 .73 Trail making test part B (seconds) 83.637.151.513.23.7 .001 1.18 COWAT (FAS) total 29.610.442.39.7-4.0 .001 1.27 Category fluency (animals) total 17.14.220.34.2-2.4 .02 .76 Definition of abbreviations: BD I-II = Beck Depression Inventorynd Edition; STAI=State Trait Anxiety Inventory; FrSBe=Frontal Systems Behavior Scale; S ADI=Self-Awareness of Deficits Interview; HVLT=Hopkins Verbal Learning Te st; WMS-R=Wechsler Memory ScaleRevised Edition; COWAT=Controlled Or al Word Association Test

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42 Table 2-2. Injury characteristics and neuroradiological informati on for TBI participants (N= 19) Age (yrs) Sex Etiology GCS LOC (days) PTA (days) Months Post Neuroradiology 25 M Pedestrian vs. vehicle 621245Bilateral basal ganglia hemorrhages 18 M MVA 743112Bilateral frontal contusions; effacement of cortical sulci and basal cisterns 49 M MVA 414306Bilateral frontal subdural hygromas; left anterior temporal contusion; right periventricular white matter infarct 25 M MVA 5N/A2818Bilateral subdural hygromas in frontal, parietal, and temporal convexities 18 M Motorcycle accident 37297Intraparenchymal contusions at tips of left and right frontal hornsconsistent with DAI; small right temporal lobe and right frontal lobe contusions 42 M MVA 3101206Intraventricular hemorrhage, basilar skull fracture 52 M Fall from heights 45194Left frontal, left parietal, and right frontal hemorrhagic contusions 22 F Rollover MVA 372119Left supraorbital hematoma; right frontal hematoma; bifrontal contusions 40 F MVA 611512Left temporal-occipital subarachnoid hemorrhage; multiple skull fractures 23 M MVA 418206Multiple frontal contusions/Frontal subarachnoid hemorrhage 50 F Bicycle accident 849536Right epidural hematoma; right orbitofrontal fractures 20 F MVA 3141619Right frontal contusions; shear injury to left frontoparietal lobe; subarachnoid hemorrhage with interpeduncular cistern 21 M MVA 3429020Right frontal subdural hematoma; multiple skull fractures 50 M Fall 67729Right subdural hematoma; right parietal extra-axial fluid

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43 Age (yrs) Sex Etiology GCS LOC (days) PTA (days) Months Post Neuroradiology 21 M Motorcycle accident 3123318Right temporal contusions; right frontal subarachnoid hemorrhage; Microhemorrhages along gray-white junction of left hemisphere and right parietal lobe 24 M Boating accident 39132Right temporal lobe epidural and subdural hematomas; right anterior middle cranial fossa hematoma 35 M Collision with wall 87N/A15Right temporal subdural hematoma; blood on right thalamus and left internal capsule; small uncal herniation 36 M MVA 330364Small bilateral intraventricular hemorrhages; no additional findings 21 M MVA 341506Unavailable 30.4 (12.1) --4.5 (1.8) 16.6 (14.4) 35.3 (28.4) 11.3 (7.5) -Note: Last row is Mean ( Standard Deviation) values. LOC and PTA are shown in days unless otherwise specified. Neuroradio logical findings taken from medical record review of neuroradiological reports from CT scans taken acutely af ter injury. MVA = Motor Vehicle Accident; GCS = Glascow Coma Scale; LOC = Loss of consciousness; PTA = Post-traumatic amnesia; DAI = Diffuse axonal injury Table 2-3. Mean ( Standard Deviation) error rates (percent) and reaction time (milliseconds) on the Stroop Task Control (n = 21) TBI (n = 19) Error Rates Congruent Incongruent .02 (.01) .05 (.03) .04 (.08) .11 (.15) Correct-Trial Reaction Time (ms) Congruent Incongruent 583.5 (70.3) 726.0 (132.1) 723.8 (178.2) 900.5 (216.6) Table2 2Continued.

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44 Table 2-4. Mean ( Standard Deviati on) ERN and Pe component amplitude ( V) as a function of task condition. Control (n =21) TBI (n = 19) Amplitude ( V) ERN Correct Incorrect -0.6 (1.7) -5.9 (4.2) -1.4 (1.2) -2.9 (2.8) Pe Correct Incorrect -2.3 (4.6) 3.3 (4.6) -3.0 (2.6) 0.8 (3.4)

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45 Figure 2-1. Electrical geodesics sensor layout and in ternational 10 equivalents for the 64channel geodesic sensor net (EGI; Eugene, Oregon).

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46 Figure 2-2. Grand average ERP waveforms depicti ng response-locked correct and error-related activity averaged across fronto-medial elect rode locations for the ERN and top view of the spline-interpolated voltage distribut ion maps showing mean voltages for errortrial activity at 22ms. denotes the ERN. Figure 2-3. Grand average ERP waveforms depicti ng response-locked correctand error-related activity averaged across centroparietal electrode locations for the Pe and top view of the spline-interpolated voltage distributi on maps showing mean voltages for errortrial activity at 322ms for cont roland 286ms for participants with TBI. denotes the Pe component.

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47 CHAPTER 3 COGNITIVE CONTROL ADJUSTMENT PROCESSES FOLLOWING SEVERE TRAUMATIC BRAIN INJURY Cognitive control theory suggest s conflict effects are differen tially reduced following highrelative to low-conflict trials. Such reactive adju stments in control, frequently termed conflict adaptation effects, indicate a dynamic interplay between regul ative and evaluative components of cognitive control necessary for efficient goal -directed behavior. The current study examined conflict adaptation effects while survivors of severe traumatic brain injury (TBI) and healthy control participants performed a single-trial, color-naming version of the Stroop task. The incongruent minus congruent trial Stroop effect for trials preceded by incongruent (high conflict) and congruent (low conflict) trials was compared for behavioral (i.e., RT and error rate) and electrophysiological (i.e., the N450 and conflict SP components of the ev ent-related potential [ERP]) reflections of cognitive control. Behavioral data indicate a reduction in the Stroop effect for RTs when preceded by incongruent trials th at cannot be accounted fo r by stimulus repetition priming. The magnitude of these effects did not differentiate control a nd TBI participants. ERP data indicate a conflict slow potential that differentiated inco ngruent from congruent trials and was larger in magnitude for control than TBI pa rticipants. Conflict adaptation effects were not present in the omnibus ERP data; however, plan ned comparisons revealed a decreased amplitude tonic conflict SP when preceded by incongruent trials in control participants. Measurements of conflict adaptation did not correlate with measures of deficit awarene ss in participants with TBI. Introduction Goal-directed behavior requires an adaptiv e cognitive control system for recognizing appropriate or inappropriate task completi on and dynamically adjusting performance when control is misdirected or inadequate. The eval uative control mechanis ms required to monitor performance for errors or conflict and to signal for subsequent adjustments ar e, therefore, critical

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48 to adaptive behavior (see Botvin ick et al., 2001). The first studie s of evaluative control processes were completed using single cell recordings in macaque monkeys, with findings indicating a negative field potential in the ACC following er rors (Gemba et al., 1986; Niki & Watanabe, 1979). The human analogue, the error-related negativ ity (ERN) discussed above, is generated in the ACC and was initially thought to solely reflect the detection of errors (Gehring et al., 1993; Gehring & Knight, 2000; van V een & Carter, 2002a, 2002b). Th e interpretation that ACC activation solely represents the detection of errors has been challenged on grounds that the negativity reflects response conflict (Botvinick et al., 2001; Yeung et al., 2004). Response conflict occurs when two competing response opti ons are simultaneously active. For example, on an error trial conflict occurs because both th e error and correct response are simultaneously active. The degree of co nflict may be modulated by the degree to which the error representation has been activated (e.g., pre potency), stimulus-response ma pping (e.g., simpler stimulusresponse mapping for the error representation), or because an individual is unsure of how to respond. One central aspect of cognitive control theory is that response conflict alone, even in the absence of an error, is sufficient to lead to conflict-related ACC activa tion (Botvinick et al., 2001). This has been demonstrated on tasks such as the Eriksen Flanker task (Eriksen & Eriksen, 1974) and the Stroop task (Stroop, 1935) where inc ongruent trials activat e a prepotent, highly practiced response simultaneously with a less prac ticed option. For exampl e, in the Stroop colornaming condition, participants are asked to name th e color of a word written in a different color of ink (e.g., the word RED written in blue ink). Th e more practiced response to read the word must be inhibited in favor of following the instru ction to name the color of ink; however, conflict

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49 occurs because both the color-n aming and word-reading repres entations are simultaneously activated (Cohen et al., 1992). A stimulus-locked ERP manifestation of this re sponse conflict is a la te fronto-central ERP signature referred to as the N450 (Perlstein et al., 2006; van Veen & Carter, 2002a, 2002b; West & Alain, 1999, 2000, West, 2003). The N450 is a negative-going deflection in the ERP waveform occurring approximately 450 milliseconds following the presentation of stimulus with inherent response conflict. The N450 is largest under conditions of high response conflict, such as the incongruent condition of the Stroop color-naming task (G rapperon et al., 1988; Liotti et al., 2000; Rebai et al., 1997; West & Alain, 1999), a nd has greater amplitude when the degree of conflict and stimulus prepotency is increased by util izing relatively more congruent than incongruent trials (e.g., 70% c ongruent vs. 30% incongruent; West & Alain, 2000). Functional magnetic resonance imaging studies (e.g., MacDona ld et al., 2000) and ERP source localization efforts implicate the ACC as the neural generato r of the N450 component (Liotti et al., 2000; van Veen & Carter, 2002a, 2002b; West, 2003). A recent study from our lab (Perlstein et al., 2006) demonstrated reduced N450 differentiation betw een congruent and incongruent color-naming trials in survivors of severe TBI and a previous study showed altered am plitude ERP activity in the latency range of the N450 in mild TBI participants while perf orming a single-trial version of the Stroop task (Potter et al., 2002) Similarly, findings from recen t fMRI studies suggest altered ACC activity in moderate-to-severe TBI survivor s on the Stroop or similar conflict-laden tasks (Scheibel et al., 2007; Soeda et al., 2005). Adjustments in Control Detection of response conflict is necessary to cognitive control processes only as it relates to subsequent adjustment s in cognitive control to better complete the task at hand. One prediction of cognitive control theory is that the occurrence of re sponse conflict and the

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50 subsequent signals for change in regulative control processes should result in behavioral adjustments (Botvinick et al., 2001 ). That is, conflict-related eval uative activity in ACC should signal for increased utilization of dlPFC-mediated regulative control processes leading to improved behavioral (i.e., RT and error rate) performance. Several authors have employed the Stroop colo r-naming task to suppor t this prediction. Conflict is present for incongruent Stroop trials (e.g., BLUE written in red) relative to congruent trials (RED written in red) because of the si multaneous activation of competing representations. Behavioral adjustments in control following th is type of conflict include faster RTs on incongruent trials preceded by incongruent tria ls (incongruent-incongruent) than on incongruent trials preceded by congruent trials (congruent-inc ongruent), and slower RTs for congruent trials preceded by incongruent trials (incongruent-c ongruent) and congruent trials preceded by congruent trials (congruent-congru ent). The explanation offered fo r this pattern of behavioral adjustments is that high conflict detected on an incongruent trial leads to recruitment of greater cognitive resources than on congr uent trials; the cogni tive resources are then utilized on the subsequent trial to enhance performance (Botvi nick et al., 2001; Grat ton et al., 1992; Kerns, 2006; Kerns et al., 2004; Ullspe rger et al., 2005). In cons equence, RTs on incongruentincongruent trials are faster than congruent-in congruent trials because the preceding incongruent trial results in increased signa ling for cognitive control, whil e when the preceding trial is congruent fewer cognitive res ources are allocated for use on the following trial. These adjustments in RTs are frequently referred to as conflict adaptation effects and have been demonstrated in several behavioral studies us ing tasks with both congruent and incongruent conditions (e.g., the Stroop, Simon, and Eriksen Flanker Tasks; Botvinick et al., 1999; di Pellegrino et al., 2007; Egner & Hirsch, 2005; Gra tton et al., 1992; Kerns et al., 2004; Notebaert

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51 et al., 2006; Ullsperger et al ., 2005; West & Moore, 2005; Verb ruggen et al., 2006). The neural mechanisms underlying conflict adaptation in ne urologically-normal part icipants have only recently been explored and few studies to date ha ve examined the neural mechanisms of manifest impairments in these processes (Egner & Hirs ch, 2005; Kerns, 2004, 2006; di Pellegrino et al., 2007; Stemmer et al., 2004). Kerns et al., (2004) used a conf lict adaptation paradigm (i.e., a single-trial Stroop task) and fMRI to test the prediction that conflict-related evaluative acti vity in the ACC should predict subsequent increases in dlPFC-m ediated regulative control processes. A brief summary of their findings indicates that, first, there was si gnificantly less ACC activity on incongruentincongruent trials than congruent-incongruent tr ials, presumably because increased control was recruited for incongruent-incongruent trials a nd subsequently reduced the amount of conflict associated with the second incongruent trial presentation. Second, they divided trials based on behavioral performance into high adjustment (e.g., much faster performance on incongruent trials preceded by an incongruent trial) and low adjustment (e.g., little difference between subsequent incongruent trials). Increased ACC activity on the previ ous trial was associated with high adjustment trials (i.e., increased detection of conflict and subsequent signaling for increased control) compared to low adjustment trials where the signal to implement increased control was less robust. Third, they examined dlPFC activity in conjunction with high and low adjustment trials and found trials exhibiting the greatest ad justments in behavior following conflict were associated with the greatest dlPFC activity, indi cating a recruitment of re sources subsequent to the detection of conflict. Fina lly, Kerns and colleagues tested whether ACC activity on conflict trials predicted dlPFC activity on the subsequent trial. They found a reliable correlation between ACC and dlPFC activity on subsequent trials sugg esting a direct relations hip between evaluative

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52 ACC activity and regulative dlPFC activity. In ot her words, ACC-mediated conflict monitoring processes signal for increased dlPFC-rela ted regulative cont rol processes. ERP indices of recruitment of cognitive c ontrol resources have also been examined. Researchers have observed a sustained conflict slow potential (conflict SP) that is present following the more phasic ERP conflict-detection component, the N450 (Liotti et al., 2000; West & Alain, 2000). The conflict SP reflects a sustained parietal positivity/lateral frontal negativity occurring approximately 500ms after stimulus onset that is more positive following correct incongruent trials than congruent trials or errors (Liotti et al ., 2000; West & Alain, 2000; West, 2003). The neural generator of the slow wave remains uncertain; however source localization studies suggest neural co ntributions from areas of the middle a nd inferior frontal gyri, as well as the extrastriate cortex (West, 2003). Current theories suggest the conflict SP repres ents the neural manife station of resolving response conflict and, perhaps, signaling for acti vation of regulative component processes of cognitive control (Perlstein et al., 2006; West, 2003; West & Alain, 2000). Studies from our laboratory also indicate a frontal conflict SP that is more negativ e to incongruent than congruent trials (Larson et al., 2004; Perlst ein et al., 2006) in control partic ipants. Survivors of severe TBI failed to exhibit a congruencyrelated effect on the frontal conflict SP suggesting that TBI patients did not implement regulative control to adaptively resolve the conflict inherent in the incongruent color-naming condition (P erlstein et al., 2006). No studies to date have examined the effects of sequential trials (e.g., incongruent fo llowing congruent trials) on the conflict SP. However, if the conflict SP does represent resoluti on of conflict, it is lik ely the conflict SP would be largest on congruent-incongrue nt trials and somewhat sma ller on incongruent-incongruent trials due to the hypothesized adjustments in cognitive control followi ng incongruent trials.

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53 Conflict Adaptation vs. Repetition Priming Mayr et al., (2003) suggest th at the repetition of the exact stimulus or stimulus attributes (e.g., the color of the word in the Stroop co lor-naming condition) accounts for the conflict adaptation effect following incongruent-incongruent trials relative to congruent-incongruent trials. That is, the conflict adaptation e ffect may be accounted for by bottom-up repetition priming mechanisms rather than top-down adjustments in cognitive control component processes. To test this hypothe sis, Mayr et al., (2003) conducte d two separate studies and found conflict adaptation effects were present only wh en there was an exact stimulus repetition and were not present when the experimental task ensured stimulus elements were not repeated. Subsequent studies provide support for both th e repetition priming hypot hesis (Hommel et al., 2004; Niewenhuis et al., 2006) a nd the conflict adaptation effect when repetition priming was controlled or removed (Kerns et al., 2004; Ulls perger et al., 2005) as well as a recent study suggesting both bottom-up and top-down mechanisms contribute to the co nflict adaptation effect (Notebaert et al., 2006). In one example, Niew enhuis et al., (2006) condu cted five separate experiments with and without stimulus repetiti ons. Findings extend those of Mayr et al., by indicating a response repetition led to faster RTs, while RTs did not differentiate conditions in the absence of response repetitions. In contra st, Kerns et al., (2004) removed both word and color repetitions from a singletrial Stroop task and found robus t conflict adaptation effects. Other investigators have, similarly, found intact conflict adaptation effects when stimulus repetition trials were removed from the data or not available in the task (Ullsperger et al., 2005; Verbruggen et al., 2006). An additional potential confound of examin ing the neural reflections of conflict adaptation effects is the inclus ion of error and post-error tria ls (Egner & Hirsch, 2005). Error trials are frequently associated with faster RTs (see Ridderinkhof, 2002), while post-error trials

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54 are associated with reliable RT slowing (Rabbi tt, 1966). Thus, we exclude error and post-error trials from analyses in an effort to isolate ma nifestations of conflict adaptation processes from those associated with error processing. Current Study Conflict adaptation effects on the Stroop task provide an ideal paradigm for examining reactive adjustments in cogniti ve control and, more specific ally, the relationship between evaluative and regulative control component proce sses following TBI. Thus, the primary aim of the current study was to examine the impact of se vere TBI on behavioral (RT and error rate) and electrophysiological (N450 and c onflict SP components of the ERP) manifestations of conflict adaptation effects. We predic ted control participants woul d demonstrate robust conflict adaptation effects manifest by a decreased Stroop effect (incongruent minus congruent) when preceded by incongruent relative to congruent trials and smaller N450 and conflict SP components (incongruent minus congruent differen ces) when preceded by incongruent trials. For TBI participants, we predicted if cognitive cont rol component processes (i.e., conflict monitoring and signaling for adjustments in control) are impa ired then the conflict adaptation effect should be reduced in magnitude relative to control participants for RT s and electrophysiological indices should not differentiate sequential tr ial conditions for participants with TBI. Notably, this is the first ERP investigation of conflict adaptation effects. Given the potential confound of repetition priming on conflict adaptation effects, secondary analyses examined both behavioral and electrophysiologica l manifestations of sequential trials in the absence of color repetitions. Color repetitions were chosen for exclusion because the current version of the Stroop task is color-naming only. Finally, as noted in the General Introduction and Experiment 1, one impor tant aspect of detecting, processing, and overcoming response conflict may be being aware of conflict and, subseq uently, aware of your

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55 own deficits. Thus, we also tested the hypothe sis that measures of conflict detection and processing (i.e., RT and N450/conflict SP amp litude) are related to measures of deficit awareness. Methods Participants, neuropsychologica l and mood measures, measures of deficit awareness, and the experimental task are the same as those utiliz ed in Experiment 1. The reader is referred above for these indices (pages 23-30). Electrophysiological Data Recording Electroencephalogram was recorded from 64 s calp sites using a geode sic sensor net and Electrical Geodesics, Inc., (EGI ; Eugene, Oregon) amplifier system (20K gain, nominal bandpass=.10-100Hz). Electrode placements enab led recording vertical and horizontal eye movements reflecting electro-oculographic (EOG) activity. Electroencephalogram data were initially referenced to Cz and digitized con tinuously at 250Hz with a 16-bit analog-to-digital converter. A right posterior elec trode approximately two inches behind the right mastoid served as common ground. Electrode impedance was maintained below 50k Eye movement and blink artifacts were corrected using a spatial filter ing method (Berg and Sche rg, 1994; Ille, Berg, and Scherg, 1997, 2002) utilized through Brain Electric Source Analys is (BESA) software (Scherg, 1990). Data from the EEG were then segmented in to condition-related epoc hs and single trial epochs with voltages that exceeded 150V or tr ansitional (sample-to-sample) thresholds of 100V discarded. Electroencephalogram data we re digitally re-referenced to an average reference (Bertrand et al., 1985) in order to yield a referencefree representation of electrophysiological ac tivity and to reconstruct the EEG at the Cz reference, then digitally lowpass filtered at 15Hz.

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56 Event-related Potential Reduction and Measurement Individual-subject stimulus-locke d averages were derived for correct trials only for each congruency (congruent, incongruent) and sequen tial trial repetition possibility (congruentcongruent, congruent-incongrue nt, incongruent-congruent, an d incongruent-incongruent). Epochs spanned 100ms prior to and 900ms following stimulus presentation. Data were baseline corrected using the 100ms pre-s timulus window. Analyses of el ectrophysiological data focused on selected electrode sites base d on previous findings indicati ng that the ERP modulations of interest are relatively focal over fronto-med ial (N450; Liotti et al., 2000; West & Alain, 1999, 2000) and posterior parietal sites (conflict SP; Li otti et al., 2000; West & Alain, 2000), as well as the scalp-distribution maps of the present data which indicated the ERP deflections of interest were greatest in amplitude over these regions Consistent with our previous ERP study of cognitive control in TBI (Perls tein et al., 2006), the stimulus-l ocked phasic fronto-central N450 was quantified as the mean voltage between 450-500 ms at sites 4 (FCz), 65 (Cz), 5, and 55 (see Figure 2-1), while values for the more tonic conf lict SP were measured as the mean voltage from 650-750ms at electrode sites 34 (Pz), 38, 33 and 41 (see Figure 2-1). Measured voltages for both components of interest were averaged across all four sites prior to analyses. Latency measurements for the N450 component were inde xed as the time of the peak negative-going amplitude. No latency measurements are provide d for the conflict SP, as it is a slow, tonic component. To assess the potential for non-specific or ge neralized ERP amplitude decrements and/or latency shifts in TBI participant ERP waveforms, P1 amplitude and latency data reflecting extrastriate cortex activity (Di Russo et al., 2002 ) were extracted. Both P1 amplitude and latency were quantified at the first peak positive deflection in the ERP between 50 and 150ms for

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57 congruent and incongruent trials averaged across the bilate ral locations of maximum P1 amplitude (average of posterior elec trode sites 32 and 45see Figure 2-1). Data Analysis Median correct-trial RTs (Ratcl iff, 1993), arcsine transformed error rates (Neter et al., 1985) excluding non-response trials, and ERP co mponent amplitude and latency data were analyzed using separate repeated-measures analyses of variance (ANOVA). In an effort to isolate conflict adaptation activity, trials immediately fo llowing errors were excluded from analyses of RTs and error rates. The dependent variables we re RTs (msec), error rates, and ERP component amplitudes and latencies. The Huynh-Feldt eps ilon adjustment was a pplied for ANOVAs with more than two levels of a within-subject factor to correct for possible violations of sphericity and partial-eta2 ( 2) reported as a measure of effect size. Te sts of between-group simple effects were used to decompose interactions, while planned comparisons were used to examine congruency effects within each group. Cohens-d effect sizes (Cohen, 1988) we re calculated for conditionrelated effects. Each dependent variable was analyzed separate ly. Initial analyses focused on overall task performance via two-factorial ANOV As with group (TBI, control) as the between-subjects factor and congruency (congruent, incongruent) as the within-subject factor. To examine potential conflict adaptation effects, cong ruency-related adjustment scores were calculated by taking the incongruent minus congruent difference for trials preceded by a congruent trial (i.e., congruentincongruent minus congruent-cong ruent trials) or an incongrue nt trial (i.e., incongruentincongruent minus incongruent-cong ruent). Difference scores were subjected to a two-factorial ANOVA with group (TBI, control) as the betwee n subjects factor and congruency-related

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58 adjustment score (difference score for trials pr eceded by congruent trials, difference scores for trials preceded by incongruent trials ) as the within-subjects factor. We next conducted a series of Pearson pr oduct-moment correlations to test specific predictions regarding the relati onship between ERP reflections of conflict detection/processing (i.e., N450 and conflict SP amplitude) and awarene ss of deficits. For initial correlations, an incongruent minus congruent difference score wa s calculated on the amp litude of the N450 and conflict SP components and compared with meas ures of deficit awareness (SADI and FrSBe concordance score) in TBI participants. We pr edicted TBI participants with lower deficit awareness scores would show smaller inc ongruent minus congruent differences on ERP component amplitudes. A second set of correlations tested the prediction that TBI participants who were less aware of their de ficits would show smaller RT conflict adaptation effects and smaller ERP manifestations of conflict adaptation. These correl ations included the congruencyrelated adjustment scores (inc ongruent minus congruent trials) for RTs as well as N450 and conflict SP amplitude. Similar to Experiment 1, we recomputed the correl ations including only those participants with only positive, rather than absolute value, FrSBe concordance scores (i.e., higher significant other than TBI survivor scor es) to account for participants who may be hypervigilent to their deficits. Results Behavioral Performance Overall RTs and error rates for the Stroop task were not significantly correlated in control participants, r (20)=-0.17, p >.47, but were significantly positively correlated in participants with TBI, r (18)=.47, p <.04. Results suggest speed/accuracy tradeoff did not influence control or TBI participants, as a positive correlation indicates longer RTs were associated with increased error rates, opposite the direction sugges tive of a speed/accuracy trade-off.

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59 Response times Data for correct-trial RTs as a function of group, previous trial congruency, and current trial congruency are pres ented in Table 3-1 and depicted in Figure 3-1. Analyses on correct-trial RTs revealed the expe cted generalized slowing in participants with severe TBI, as reflected in a significant main effect of group, F (1,38)=11.75, p <.001, 2 =.24. A main effect of current trial congruency re flected the anticipated RT interference, F (1,38)=73.19, p <.001, 2 =.66, with both groups showing longer RTs to the incongruent than congruent condition (i.e., the standard Stroop effect [TBI: t (18)=4.97, p <.001, d = .97; controls: t (20)=9.43, p <.001, d =1.04]). The Group x Congruency interacti on was not statistically reliable, F (1,38)=.84, p >.37, 2 =.02, indicating the two groups showed similar levels of current trial congruencyrelated RT interference. Of greater interest to the pres ent study were the potential conflict adaptation effects (Figure 3-1; Table 3-3). The Group x Congruency-Re lated Adjustment Score ANOVA yielded a main effect of adjustment score, F (1,38)=12.59, p <.001, 2 =.25, indicated an overall conflict adaptation effect; however, the Group x Adjust ment Score interacti on was not significant, F (1,38)=.74, p >.40, 2 =.02, indicating the magnitude of th e conflict adaptation effect was similar between groups. Supporting this observati on, planned contrasts indicated incongruent minus congruent trial RTs were greater following congruent than following incongruent trials for both TBI, t (18)=2.53, p <.02, d =.45, and control participants, t (20)=2.54, p <.02, d =.44. Survivors of severe TBI showed a 205.42ms (SD = .54) Stroop effect (inc ongruent minus congruent RTs) when preceded by a congruent trial and a 149.4ms (.3) Stroop effect when preceded by an incongruent trial (incongruent minus congrue nt preceding trial difference = 56.0ms). Control participants showed a 157.9ms (.0) Stroop eff ect when preceded by congruent trials and a

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60 123.7ms (.9) effect when preceded by incongr uent trials (incongruent minus congruent preceding trial difference = 34.19ms). Error rates. Data for mean error rates as a func tion of group, previous trial congruency, and current trial congruency are presented in Table 3-2 and depicted in Figure 3-2. The Group x Congruency ANOVA on arcsine-corr ected error rates i ndicated comparable error rates between groups, as the main effect of group wa s not statistically significant, F (1,38)=2.21, p >.14, 2 =.06. A significant main effect of current trial congruency, F (1,38)=83.68, p <.001, 2 =.69, reflected error rate interference, with both groups co mmitting more errors to the incongruent than congruent condition (TBI: t (18)=6.37, p <.001, d =.58; controls: t (20)=6.57, p <.001, d =1.34). A non-significant Group x C ongruency interaction, F (1,38)=1.47, p >.23, 2 =.04, indicated similar error rate profiles between groups as a function of congruency. Similar to the data for RTs, the Group x Congruency-Related Ad justment Score ANOVA on arcsine-corrected error rates yielded a main effect of adjustment score, F (1,38)=4.00, p =.05, 2 =.10, indicating the presence of a conflict adaptation effect when collapsed across groups (Table 3-3). The Group x Adjustment Sc ore interaction was not significant, F (1,38)=.03, p >.86, 2 =.001, nor were planned comparisons of the in congruent minus congruent difference scores for TBI, t (18)=1.53, p >.18, d =.34, or healthy control participants, t (20)=1.30, p >.20, d =.32. ERP Data Healthy control participants and survivors of severe TBI did not differ on number of trials retained for averaging on congruent, t (38)=1.16, p >.25, d =.37, or incongruent conditions, t (38)=1.40, p >.17, d =.44. Congruent trial waveforms contained an average ( SD) of 326.1 70.5 trials for participants with TBI and 346.3 35.0 trials for controls, while incongruent waveforms contained an average of 132.2 36.6 trials for participants with TBI and 144.6 16.7 trials for

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61 controls. When broken down to examine sequential trial effects, groups di d not differ on number of trials retained for congruent-congruent, t (38)=1.21, p >.23, d =.38 (TBI = 216.5 53.8 trials; controls = 232.1 23.6 trials), congruent-incongruent, t (38)=1.26, p >.22, d =.40 (TBI = 91.1 27.5 trials; controls = 99.5 12.9 trials), or incongruent-congruent conditions, t (38)=1.27, p >.21, d =.40 (TBI = 90.1 27.8 trials; cont rols = 98.8 13.2 trials). Groups did signi ficantly differ on number of trials retained for the in congruent-incongruent condition, t (38)=2.15, p <.04, d =.68 (TBI = 34.3 11.3 trials; controls = 40.2 5.4 trials) due to more artifact trials rejected for participants with TBI, rather than increased error rates, as noted above. P1 amplitude and latency. A Group x Congruency ANOVA on stimulus-locked grand average ERP waveforms averaged across the two channels of greatest P1 amplitude (channels 32 and 45; one from each hemisphere at posterior scalp locationssee Figure 2-1) was conducted to examine the possibility of generalized amplit ude decrements or latency shifts for TBI participants. Results of the anal ysis of P1 amplitude indicate no main effect of congruency, F (1,38)=.03, p >.86, 2 =.001, no Group x Congruency interaction, F (1,38)=1.52, p >.22, 2 =.04, and no main effect of group, F (1,38)=.70, p >.41, 2 =.02. Latency data for the P1 component were similar, with no significant main effect of congruency, F (1,38)=.07, p >.79, 2 =.002, no Group x Congruency interaction, F (1,38)=.70, p >.41, 2 =.02, and no main effect of group, F (1,38)=1.73, p >.20, 2 =.04. Thus, data suggest that there is not a signifi cant generalized amplitude decrement or latency shift in the ERPs of the TBI participants relative to healthy controls. Stimulus-locked grand average ERP waveform s and spline interpolat ed current source density maps for the fronto-medial N450 as a f unction of group and congruency are presented in Figure 3-3, those for the conflic t SP are presented in Figure 3-4. Grand average ERPs for both

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62 groups and each repetition category (i.e., Previous x Current Trial averages) are presented in Figure 3-5. Mean ( SD) component amplitude data are pres ented in Table 3-4 and depicted in Figure 3-6 for the N450 and Figure 3-7 for the conflict SP. N450 amplitude Examination of stimulus-locked ERP waveforms (Figure 3-3) revealed a negative-going deflection that is more negative to incongruent than congrue nt trials in control participants, but does differentiate congruencie s for participants with TBI. Contrary to predictions, the Group x Congrue ncy ANOVA on N450 amplitude did not yield a significant main effect of current trial congruency, F (1,38)=2.57, p >.12, 2 =.06; neither group showed reliable N450 amplitude differentiation of th e incongruent and congr uent conditions (TBI: t (18)=.88, p >.39, d=.09; controls: t (20)=1.38, p >.18, d =.11). The main effect of group on N450 component amplitude was not significant, F (1,38)=.01, p >.99, 2 =.00. Consistent with the absence of congruency differentiation on N450 component amplitude, the Group x Congruency-Related Adjustment Score ANOVA on incongruent minus congruent difference scores did not demonstrate a conf lict adaptation effect as evidenced by a nonsignificant main effect of congruency, F (1,38)=.03, p >.87, 2 =.001. Similarly, there was not a significant Group x Congr uency interaction, F (1,38)=1.60, p >.21, 2 =.04, nor a main effect of group, F (1,38)=.88, p >.35, 2 =.02 (see Table 3-4; Figures 3-5 and 3-6). Planned comparisons on incongruent minus congruent di fference scores confirmed the absence of conflict adaptation changes in N450 amplitude for both TBI, t (18)=.87, p >.39, d =.28, and control participants, t (20)=.93, p >.36, d =21. N450 latency. A Group x Congruency ANOVA indicate d N450 peak latencies were similar for both congruencies, as reflected by a non-significant main effect of current trial congruency, F (1,38)=.60, p >.45, 2 =.02. There were no group differe nces in N450 latency, with

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63 no significant Group x C ongruency interaction, F (1,38)=.01, p >.90, 2 =.001, or main effect of group, F (1,38)=1.50, p >.23, 2 =.04. Similarly, there were no ma in effects or interactions involving group or congruency-related adjust ment scores for N450 latency data, F s < 1.66, p s>.20. Conflict SP amplitude. In contrast to results of N450 amplitude, examination of conflict SP amplitudes (Figure 3-4) revealed a significa nt main effect of current trial congruency, F (1,38)=21.15, p <.001, 2 =.36, as well as a significant Group x Congruency interaction, F (1,38)=5.12, p <.03, 2 =.12. The current trial congruency eff ect reflected greater positivity to the incongruent than congruent condition; pl anned contrasts revealed the conflict SP was significantly more positive to the incongruent than congrue nt condition in controls, t (20)=4.44, p <.001, d =.79, and at trend level for su rvivors of severe TBI, t (18)=1.90, p =.07, d =.34. The Group x Congruency interaction was found in the ab sence of an overall main effect of group on conflict SP component amplitude, F (1,38)=.88, p >.35, 2 =.02. For conflict adaptation effects on the conf lict SP (Figures 3-5 and 3-7), the Group x Congruency-Related Adjustment Score ANOVA on in congruent minus congrue nt trials yielded a non-significant main effect of adjustment score, F (1,38)=.02, p >.89, 2 =.001, as well as a nonsignificant Group x Adjustme nt Score interaction, F (1,38)=1.40, p >.24, 2 =.04. Planned contrasts, however, indicated the conflict SP for the incongruent minus congruent difference was greater following congruent than in congruent trials for control, t (20)=2.10, p <.05, d =.41, but not TBI participants, t (18)=.53, p >.61, d =.20. Impact of Repetition Priming As pointed out above, recent research challe nges the interpretation of sequential trial effects as reflecting top-down conflict adaptation, suggesting instead that such effects are due to bottom-up repetition priming mechanisms (Mayr et al., 2003; di Pellegrino et al., 2007). Given

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64 this, we re-analyzed both beha vioral (RT and error rate) and ERP (N450 and conflict SP) data excluding sequential trials of the same color. Excluding trials based on stimulus color was chosen because responses on the version of th e Stroop task employed were color-naming only and exclusion of color repeats en sures possible direct stimulus repetitions are excluded from the congruent-congruent and incongr uent-incongruent conditions. Behavioral data. The pattern of results for the Gr oup x Congruency-Related Adjustment Score ANOVA on RTs and error rates was largely c onsistent with previous analyses following removal of color repetitions (see th e right side of Tables 3-1 and 3-2). For RTs, a main effect of adjustment score remained, F (1,38)=52.50, p <.001, 2 =.15, while the Group x Adjustment Score interaction was not significant, F (1,38)=2.40, p >.13, 2 =.06. For arcsine-corrected error rates, the main effect of difference score was not maintained, F (1,38)=1.44, p >.24, 2 =.04, indicating the modest sequential trial effect on error rate s reported above may be influenced by repetition priming. The Group x Adjustment Scor e ANOVA remained non-significant, F (1,38)=.25, p >.62, 2 =.006. ERP data. When color repetitions were remove d, the pattern of N450 and conflict SP results remained consistent with data presented previously (see right side of Table 3-2). For the N450, neither the main effect of adjustment score, F (1,38)=.70, p >.41, 2 =.02, nor the Group x Adjustment Score interaction, F (1,38)=.57, p >.46, 2 =.02, were statistically significant. Similarly for the conflict SP, the main eff ect of adjustment score was not significant, F (1,38)=1.52, p >.23, 2 =.04, nor was the Group x Adjust ment Score interaction, F (1,38)=.30, p >.59, 2 =.008. Correlational Analyses Due to the relatively small influence of repeti tion priming in the variables of interest for the correlations (RT and N450/conflict SP amp litude), Pearsons correlation analyses (one-

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65 tailed) were conducted on all tria ls. Initial correlations indicated that the c onflict SP incongruent minus congruent difference score signifi cantly correlated with both the SADI, r (18)=-.42, p <.04 (Figure 3-8), and the FrSBe concordance score, r (17)=.49, p <.024 (Figure 3-9); no significant correlations were noted with N450 amplitude, r s<.11, p s>.25. Subsequent examination of the conflict SP correlation with deficit awareness meas ures revealed an outlier that, when removed from analyses, rendered the corr elations with both the SADI, r (18)=-.12, p>.31, and the FrSBe concordance score, r (17)=-.006, p>.49, non-significant. Corr elations (excluding the single outlier) of RT and ERP congruency-related adjustme nt scores with measures of deficit awareness yielded no statistically si gnificant associations, r s< .36 p s> .07. Similarly, when FrSBe concordance score analyses were re-computed with only participants who endorsed fewer symptoms than their caregivers no signi ficant correlations were present, r s< .52 p s>.07. Discussion In this experiment, we examined the behavi oral and electrophysio logical correlates of conflict processing and adaptation effects in su rvivors of severe TB I and healthy control participants. Behavioral data revealed the an ticipated increases in RTs and error rates on incongruent relative to congruent trials (i.e., Stroop interfer ence) for both TBI and control participants. Contrary to predic tions, TBI and control participants did not differ on the magnitude of RT or error rate interference. Likewise, both groups showed a conf lict adaptation effect wherein the incongruent minus c ongruent Stroop RT effect disp roportionately decreased when preceded by incongruent relative to congruent stimu li. Error rates on incongruent trials similarly decreased when preceded by incongruent relative to congruent trials, but only when pooled across control and TBI groups.

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66 In contrast to predictions, participants with TBI showed RT and error rate conflict adaptation effects of sim ilar magnitude to those of healthy co ntrol participants. These results are consistent with a recent study indicating patients with focal lesions to the rostral ACC following anterior communicating artery (AcoA) aneurysm demonstrated abolished conflict adaptation effects, while neurologic ally-injured control participants w ith more diffuse neural damage or aneurysm not specifically affecting the ACC sh owed conflict adaptation effects the same in magnitude to those of neurologically-healthy controls (di Pellegrino et al., 2007). As noted above, several studies suggest inte rplay between medial and lateral frontal cortices (including the ACC and dlPFC, respectively) in monitoring for conflict and utilizing conflict information to dynamically allocate cognitive control resources and improve task performance (Kerns et al., 2004; Egner & Hirsch, 2005). The presence of behavi oral conflict adaptation effects that did not differ from those of healthy control participan ts in the current heterogeneous TBI samplenone of whom, to the best of our knowledge, experien ced focal ACC lesions--indi cates direct insult to the ACC (or potentially the dlPFC) may be n ecessary for disruption of conflict adaptation mechanisms. Supporting this view, West & Moor e (2005) found conflict adaptation effects of similar magnitude between young and old adults despite previous findings that cognitive control mechanisms are impaired in older adults (West, 2004). Event-related potentials were used to tem porally dissociate neural activity reflecting conflict monitoring and conflict ad aptation (Perlstein et al., 20 06; West, 2004; West, 2003; West & Moore, 2005). Consistent with predictions, a distinct slow poten tial, the conflict SP, differentiated congruent and incongr uent trials. The conflict SP is thought to reflect regulative aspects of cognitive control, perhaps involving pr ocesses devoted to the resolution of response conflict or signaling for increased implementatio n of attentional contro l (Liotti et al., 2001;

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67 Perlstein et al., 2006; West, 2003; West & Alain, 2000). While both healthy controls and participants with TBI demonstrat ed a clear conflict SP, control participants showed significantly greater differentiation between incongruent and c ongruent trials than participants with TBI. Considered in the context of pr evious studies indicating impair ed conflict resolution processes following severe TBI (Perlstein et al., 2006), this finding may indica te participants with TBI did not implement regulative control to the same extent as control participants in order to adaptively resolve the conflict inherent in the incongr uent Stroop color-naming condition. Behavioral findings (i.e., similar levels of Stroop RT and erro r rate interference) and the relative similarity in conflict SP pattern between control and TB I participants cast some doubt upon this interpretation. If, as suggested by cognitive control theory, th e detection of response conflict signals for the recruitment of cont rolled regulative strategies toward adaptive resolution of this conflict (Botvinick et al., 1999; Kerns et al., 2004; Miller & Cohen, 2001), the conflict SP should be smaller on trials preceded by incongruent stimuli where increased attentional control has been implemented. In contrast to this prediction, no ma in effect of conflict SP adjustment score was found, nor was there a significant Group x Adjust ment Score interactio n. When only control participants were considered in a planned contrast, trials preceded by incongruent stimuli demonstrated decreased amplitude conflict SP relati ve to trials preceded by congruent stimuli. Given that there was not a signifi cant main effect or interaction of the omnibus ANOVA, these results are tentative and shoul d be interpreted with caution. Moreover, the finding that TBI participants showed similar le vels of RT-related conflict adap tation argues against differential group-related conflict re solution processes.

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68 Event-related potential findings w ith regard to the conflict-det ection N450 were contrary to predictions and previous findings from our laborato ry (Perlstein et al., 2 006). Indeed, the lack of N450 differentiation between incongruent and congruent color-naming stimuli regardless of preceding trial is unexpected. The reasons for th e lack of differentiation are unclear, and are unlikely to be due to the EEG acquisition parame ters, since we have successfully obtained the N450 in previous studies using similar recording parameters (Perlstein et al., 2006), or to the modality of response (i.e., vocal, manual), as N450 has been obtained using both response modalities (e.g., Liotti et al., 2000), or to la tency differences between groups, as the N450 latency did not differ between groups. Thus, th e absence of a clear N450 that differentiates congruencies limits our ability to make firm c onclusions regarding the integrity of stimulusrelated conflict detection processes, as this co mponent has most reliably been thought to reflect conflict detection (see West et al ., 2005 for review), as well as th e function of conflict-detection processes in the conflict adaptation effect. As noted previously, recent research suggests conflict adap tation effects may be due to repetition priming rather than compensatory adjustments of cognitive control processes (Mayr et al., 2003). Current findings suggest automatic pr iming effects do not solely account for RTrelated conflict adaptation effects, as such effects persisted in bot h control and participants with TBI when repetition of color-naming trials were removed. The conflict ad aptation effect present for error rates when pooled acro ss control and participants w ith TBI was diminished when repetition trials were removed. Th is may suggest errors are more sensitive to repetition priming effects than RTs; however, the ini tial findings of conflict adaptation effects in the error rate data were tenuous and not significant for either the co ntrol or participants with TBI alone. Thus, the

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69 reduction in the number of trials contributing to the conflict adaptation effects may have been sufficient to reduce the previously significant effect. Largely consistent with Experiment 1, corre lations between two different measures of deficit awareness and behavioral (RT) and electrophysiological (N450, conflict SP) manifestations of cognitive cont rol (specifically conflict proce ssing) were not significant. As noted above, the lack of association may be due to the difficulties in measurement of deficit awareness (i.e., using absolute values with the Fr SBe concordance score). In addition, the lack of differentiation between participan ts with TBI and their control counterparts for both RT and ERP measurements suggests the current sample of pa rticipants with TBI may not be exhibiting the cognitive control deficits that might be associat ed with deficit awarene ss. The absence of strong associations between deficit aw areness and error-related ERP co mponents in the previous study and behavioral and ERP indices of conflict pr ocessing in the current study suggests that the hypothesis of deficit awareness corresponding with declines in evaluativ e control mechanisms may not be correct. Future resear ch utilizing improved measures of deficit awareness is clearly required to adjudicate among these possibilities. Limitations specific to the current study should be considered. First, while we were able to examine sequential trial conflict adaptation effects, the task employed limited our ability to examine post-error strategic adjustments (as note d in Experiment 1). As post-error strategic adjustments have, similar to the conflict adaptation effect, been ta ken to reflect participants topdown adjustments in performance strategy, perh aps reflecting the dynamic interplay between ACC-mediated evaluative and dlPFC-mediated re gulative processes (Bot vinick et al., 2004; Kerns et al., 2004), the convergence of inform ation from the two measurements would strengthen current findings. Next, due to th e complications associated with examining

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70 individual-trial ERPs (i.e., low si gnal-to-noise ratio in the absence of signal averaging), ERP data examining conflict adaptation effects were reduced by binning individual tria ls into epochs based on previous and current trial congruency. Epochs were then averaged for each participant and statistical values obtained on these averages. For be havioral data, in contra st, RT and error rate data for previous and current trial congruencies we re calculated on an individual trial level. Thus, it is possible that the averaging of the sequent ial trial data may have obscured potentially meaningful findings. In addition, we were unable to examine potenti ally meaningful associations between components of cognitive control. For example, Kerns et al., (2004) in their fMRI examination of conflict adaptation effects, used ACC activity on previous trials to predict dlPFC activity levels on subsequent tria ls and vice-versa. Our inability to examine single-trial data reliably due to the limitations inherent in the ERP methodology prevented such examination between, for example, N450 and conflict SP amplitude across sequential trials. In summary, the present findings indicate be havioral conflict adaptation effects are similar for participants with heterogeneous TBI and their cont rol counterparts. Findings, in concert with previous studies that showed inta ct conflict adaptation effects in groups with known cognitive control deficits but no direct lesions to the ACC (d i Pellegrino et al., 2007; West & Moore, 2005), may suggest direct insult to AC Cor other dlPFC-media ted cognitive control mechanisms are necessary for impaired conf lict adaptation processes. A tonic conflict SP differentiated incongruent from congruent trials, but failed to show consiste nt conflict adaptation effects. The N450 component did not differentiate congruent from incongruent trials. Thus, in the current study, ERPs were not a sensitive measure of the conflic t adaptation effect.

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71 Table 3-1. Mean RT ( Standard Deviation) for congruent (C) and incongr uent (I) trials as a function of previous trial c ongruency. Left columns reflect all trials, including color repetitions. Right columns reflect mean RT s with color-naming re petitions excluded. Previous C Previous I Previous C Previous I Group Current C Current I Current C Current I Current C Current I Current C Current I TBI 719.1 (184.3) 924.5 (236.0) 723.7 (175.7) 873.1 (218.7) 656.3 (196.1) 843.8 (230.3) 666.5 (159.5) 711.63 (162.2) Control 583.7 (70.1) 741.6 (139.2) 601.5 (74.2) 725.2 (136.7) 524.4 (66.0) 695.9 (154.7) 552.6 (76.0) 631.7 (125.9) Table 3-2. Mean percent errors ( Standard Deviation) for congruent (C) and incongruent (I) trials as a function of previous trial c ongruency. Left columns reflect all trials, including color repetitions. Right columns reflect percent errors with color repetitions excluded. Previous C Previous I Previous C Previous I Group Current C Current I Current C Current I Current C Current I Current C Current I TBI .04 (.08) .11 (.14) .04 (.05).10 (.18).05 (.09).11 (.15).05 (.05) .11 (.17) Control .02 (.01) .05 (.02) .02 (.02).05 (.04).02 (.02).06 (.03).02 (.02) .05 (.06) Table 3-3. Mean difference scores ( Standard Deviation) for RTs and error rates of the incongruent (I) minus congruent (C) differe nce. Left columns reflect all trials, including color repetitions. Right columns reflect trials with color repetitions excluded. All trials including repetitionsColor repetitions excluded Controls TBI Controls TBI Response time (RT) I C difference Previous trial congruent Previous trial incongruent 157.9 (76.0) 123.7 (80.9) 205.4 (146.5) 149.4 (99.3) 149.6 (64.7) 137.7 (83.3) 203.9 (.130.0) 173.8 (129.0) Error rate I C difference Previous trial congruent Previous trial incongruent .04 (.03) .03 (.04) .07 (.07) .07 (.13) .04 (.03) .03 (.06) .06 (.07) .07 (.13)

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72 Table 3-4. Mean ( Standard Deviation) ERP amplitude ( V) data for the N450 and conflict SP components. Left columns reflect all tr ials, including colo r repetitions. Color repetitions are not included in right column data. Differences represent the incongruent (I) minus congruent (C) difference. Controls TBI Controls TBI Amplitude ( V) Amplitude ( V) N450 Congruent Incongruent .51 (2.5) .24 (2.6) .44 (1.7) .30 (1.6) .40 (2.3) .12 (2.7) .59 (1.8) .40 (2.0) Conflict SP Congruent Incongruent .40 (1.7) 1.8 (1.8) .36 (1.5) .84 (1.4) .06 (1.5) 1.6 (1.9) .52 (1.4) 1.2 (1.9) N450 I C difference Previous trial congruent Previous trial incongruent -.23 (1.0) -.45 (1.1) -.25 (.86) .04 (1.2) -.07 (.80) -.09 (1.3) -.11 (.75) -.46 (1.2) Conflict SP I C difference Previous trial congruent Previous trial incongruent 1.6 (1.7) 1.0 (1.2) .64 (1.4) 1.1 (3.3) 1.4 (1.4) .86 (1.2) .71 (1.6) .48 (2.2)

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73 Mean RTs for Control & TBI500 600 700 800 900 1000Control Congruent Control Incongruent TBI Congruent TBI Incongruent Previous Trial by GroupMean RT (ms) Congruent Incongruent Figure 3-1. Mean reaction times (RTs) as a func tion of group, congruency, and current/previous trial type. Error bars reflect st andard errors of the mean. Mean Error Rates for Control & TBI0.01 0.03 0.05 0.07 0.09 0.11 0.13Control Congruent Control Incongruent TBI Congruent TBI Incongruent Previous Trial by GroupPercent Errors Congruent Incongruent Figure 3-2. Mean error rates as a function of gr oup, congruency, and curren t/previous trial type. Error bars reflect standard errors of the mean.Current Trial Current Trial

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74 Figure 3-3. Grand average ERP waveforms of stim ulus-locked congruent a nd incongruent trials averaged across fronto-medial electrode locations for the N 450 (left) and top view of the spline-interpolated current sour ce density maps at 477ms (right). Figure 3-4. Grand average ERP waveforms of stim ulus-locked congruent a nd incongruent trials averaged across posterior electrode locations for the conf lict SP (left) and top view of the spline-interpolated current sour ce density maps at 711ms (right).

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75 Figure 3-5. Grand average ERP waveforms of stim ulus-locked waveforms for congruent (C) and incongruent (I) waveforms as a function of previous trial congruency. Thus, C-C indicates a congruent previous trial and a congruent curr ent trial, C-I indicates a congruent previous trial and an in congruent current trial, etc.

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76 N450 Mean Amplitude for Control & TBI-0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4Control Congruent Control Incongruent TBI CongruentTBI Incongruent Previous Trial by GroupMicrovolts ( V) Congruent Incongruent Figure 3-6. Mean N450 amplitude as a function of group, congruency, and current/previous trial type. Error bars reflect standard errors of the mean. Conflict SP Mean Amplitude for Control & TBI0 0.5 1 1.5 2 2.5Control Congruent Control Incongruent TBI Congruent TBI Incongruent Previous Trial by GroupMicrovolts ( V) Congruent Incongruent Figure 3-7. Mean conflict SP amplitude as a func tion of group, congruency, and current/previous trial type. Error bars reflect standard errors of the mean. Current Trial Current Trial

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77 Figure 3-8. Scatter plot reflecting the relationship between SADI total score for TBI participants and the parietal conf lict SP incongruent minus congruent difference. Point in square reflects the outlier participant. Figure 3-9. Scatter plot reflecti ng the relationship between FrSB e otherminus self-rated total score for TBI participants and the parietal conflict SP incongruent minus congruent difference. Point in square reflects outlier participant.

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78 CHAPTER 4 FEEDBACK UTILIZATION AND REWARD CONTEXT SENSITIVITY IMPAIRMENT FOLLOWING SEVERE TRAUMATIC BRAIN INJURY Feedback processing is an important aspect of evaluative control and is critical for appropriate decision-making. Ind eed, many rehabilitation protocol s following traumatic brain injury (TBI) utilize feedback vi a reinforcement and reward to in fluence behavior and facilitate recovery; however, previous studi es suggest survivors of severe TBI demonstrate impairments in feedback contingency utilization and sensitiv ity. The precise neurobiological mechanisms underlying these deficits have not been thorough ly explored, but can be examined using the feedback-related negativity (FRN)an even t-related potential (ERP) component evoked following performance or response feedback (e.g., whether a moneta ry reward is obtained) with a larger FRN following unfavorable than favorab le outcomesparticularly when unfavorable feedback occurs in the context of high rewa rd probability. We examined ERPs elicited by favorable (monetary gain: reward) and unfavorab le (no monetary gain: non-reward) feedback during a guessing task where probability of rewa rd outcome was manipulated in a subset of survivors of severe TBI and demographically-mat ched healthy participan ts. Consistent with previous findings, healthy cont rol participants showed larger amplitude FRN to non-reward feedback and the largest amplitude FRN follo wing a non-reward when reward probability context was greatest. In contrast FRN in severe TBI survivors di d not significantly differentiate non-reward from reward trials and their FRN was largest to reward trials in the low reward probability context. Findings indicate an impa ired evaluative control mechanism of feedback processing and implicate an elec trophysiological marker of impai red reward context sensitivity following severe TBI.

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79 Introduction The previous studies indicate survivors of severe traumatic brain injury (TBI) show deficits in the evaluative processes of monito ring and comparing performance with internal goals. Feedback processing, a critic al component of evaluative cont rol utilized in the assessment of actions and the adjustment of performance to these outcomes, may also be impaired following severe TBI. Indeed, TBI survivors frequently exhibit a constellation of characteristics that include failure to evaluate and adjust behavior to feedback/p erformance (Larson et al., 2006a), and decrements in their ability to respond adaptively to the consequences of their actions or responses (Bechara et al., 2000; Bechara et al., 1996; Schl und, 2002a, 2002b; Schlund et al., 2001; Schlund & Pace, 2000) leading to risky deci sion-making (Grafman et al., 1996; Oddy et al., 1985; Tateno et al., 2003) and impaired go al-directed action (Sha llice & Burgess, 1991). Such sequelae of injury lead not only to deficits in essential cognitive activities, but also poor learning/re-learning of socially appropriate behaviors, deteriorat ion of interpersonal relationships, and ultimately poor rehabilitation outcomes and decreased rates of return to employment (Weddell et al., 1980). Many of the aforementioned difficulties result from decreased sensitivity to stimulusresponse contingencies (Bechara et al., 2000; Bechara et al., 1996; Salmond et al., 2005; Schlund et al., 2001; Schlund & Pace, 2000). While brain in jured individuals may remain sensitive to certain consequences, they fail to adaptivel y discriminate among the relevant responseconsequence relations (i.e., contingencies), wh ich likely accounts for some increases in risky behaviors, as well as problems in skill acqui sition and adaptive choice (Schlund, 2002a). For example, Salmond et al., (2005) found impaired decision-making and increased impulsive responding when head injury survivors performe d a computerized gambling task. These results were consistent with other accounts of increas ed levels of impulsivi ty associated with

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80 dysfunction of the frontal lobe (Fuster, 1997; Miller, 1992). Although there is substantial heterogeneity among TBI survivors, there is typica lly widespread damage to white matter tracts (Meythaler et al., 2001) and cort ical regions involving the orb itofrontal cortex and temporal lobes (Levin et al., 1987). Impulsi ve or disinhibited be havior has been link ed to orbitofrontal (Bechara, 2004; Rolls, 2000) and ventromedial prefrontal (Bechara et al., 1994) lesions in humans. More specifically, the actio ns of individuals with injuries to the prefrontal cortex show reduced sensitivity to the consequences of thei r response and tend to respond preferentially to stimuli that are associated with the possibility of an immediat e reward, without regard to the context of previous feedback or future contingencies, resulti ng in a form of myopia for the future (Bechara et al., 2000, p. 2198). There remains a paucity of data on the neural correlates of impaired feedback contingency sensitivity following TBI, despite the fact f eedback-based treatments (e.g., reward) are frequently employed in the rehabilitation setting. Our understanding of the neurocognitive processes related to f eedback evaluation and monitoring has been enhanced through examination of the scalp-recorded event-re lated potential (ERP) known as f eedback-related negativity (FRN). The FRN is a negative-deflecti ng component with medio-frontal scalp distributi on that peaks approximately 250ms following presentation of pe rformance or reward feedback and shows greater amplitude following unfavorable than favorable outcomes (Gehring & Willoughby, 2002; Ruchsow et al., 2002). The FRN has been interpre ted as an electrophysio logical reflection of whether a desired reward has been achieved, as evidenced by Hajcak and colleagues (2006) study of healthy adults that identified a dichot omous FRN response to multiple, graded forms of feedback, with the smallest negativity following positive outcomes and largest negativity following negative or neutral outcomes. Ho lroyd and colleagues (2006) study similarly

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81 demonstrated neutral feedback elicits FRN am plitudes similar to cost/punishment, suggesting non-reward stimuli are processed as feedback that is inconsistent with the prevailing reward context. Holroyd and Coles (2002) propose the FRN is produced when an error processing system detects events that are worse than e xpected. More specifically, their reinforcement learning theory of the error-related negativity (RL-ERN) proposes the FRN, like its response error-related analogue known as the error-related negativity (ERN), is a reflection of a dopaminergic negative feedback reinforcem ent-learning signal produced when response outcomes are worse than expected. Studies of the FRN assumed participant expectation through manipulation of reward probability, rather than dire ct assessment via questi onnaire or otherwise. Thus, these studies of the FRN and the RL-ERN theory assume knowl edge of participant expectation and, therefore, may be better conceptualized as studies of reward context rather than reward prediction/expectation, with larger FR N occurring when a high reward probability context is violated by the presentation of a non-reward stimulus. Consistent with the RL-ERN theory, sour ce localization studies of the FRN broadly implicate areas of the mesial-frontal cortex, sp ecifically the anterior cingulate cortex, as the primary neural generator of the FRN (G ehring & Willoughby, 2002; Holroyd & Coles, 2002; Ruchsow et al., 2002). One paradigm that has been employed to examine the FRN is a type of guessing task (Holroyd et al., 2003; Ruchsow et al., 2002; van Meel et al., 2005). In these tasks, participants are presented with several response options and told there is a reward associated with one of the options. Following participan t response, feedback indicating whether the response was correct (reward obtai ned) or incorrect (no reward ) is presented. Unknown to the participants, feedback is presented in a pseudorandom fashion. In the high reward probability condition, participants received positive feedback on 75% of trials, while in the low reward

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82 probability condition particip ants received negative feedback on 75% of trials. This manipulation of feedback establishes distin ct forms of reward context, which are dependent on whether a reward is likely or unlikely to be achieved. According to the RL -ERN theory (Holroyd & Coles, 2002; Holroyd et al., 2003), non-reward feedback in a low reward probability condition would be associated with a small FRN because feedback is consistent with the reward context, while nonreward feedback in a high reward probability condition would lead to a larger FRN because a probability context violation has been register ed by the reward monitoring system. Such guessing paradigms also allow for study of fee dback-related neural processing independent of participant performance (van Meel et al., 2005) which would likely be impaired relative to healthy controls following a severe head inju ry, and ensures that response-reinforcement contingencies do not confound the FRN response to feedback. The present study utilized the FRN to examine reward context sensitivity in a subset of severe TBI survivors and healthy controls. We pr edicted that findings in control participants would replicate those of previous studies us ing the same guessing para digm described above (Holroyd et al., 2003), with increased amplitude FRN following non-reward feedback when averaged across conditions and largest FRN following non-reward feedback when reward probability is high. In participants with severe TBI, we predicted FRN amplitude would not differ as a function of feedback condition due to deficits in reward context sensitivity. Methods Participants Study enrollment consisted of a subset of the pa rticipants who participated in the previous studies. Initial enrollment included 11 TBI and 11 healthy control participants. Data from one TBI participant were excluded due to too few artif act-free trials to compute reliable average ERP epochs (< 25 trials per condition). Thus, the final sample included ten right-handed severe TBI

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83 participants between the ages of 18 and 42 years (3 female; M =26.40 years, SD =8.21) and 11 right-handed, ageand education-matched h ealthy control participants (4 female; M =27.18 years, SD =11.10; range=18 years). Demographic characteri stics of TBI and cont rol participants are provided in Table 4-1. Similar to the previous studies, TBI participants were recruited from two Northern Florida trauma and rehabilitation hospitals ; control participants we re recruited via flyer and advertisement from the local community. All participants provided written informed consent according to procedures established by the Univ ersity of Florida Health Science Center Institutional Review Board and were compensated for their participation. As in the previous studies, TBI severity wa s determined from medi cal record review of lowest post-resuscitation Glasgow Coma Scale (GCS) score (Teasdale & Jennett, 1974), with severe TBI defined as a GCS score <9. Neurol ogical indices, includ ing neuroradiological findings taken from acute computerized to mography (CT) scans, duration of loss of consciousness (LOC), and duration of post-traumatic amnesia (PTA), were also acquired from medical record review or, when LOC and PTA information were not available in medical records, from structured partic ipant and significant other interv iew (King et al., 1997; McMillan et al., 1996). LOC and PTA data confirmed a ll patients met criteria for severe TBI as traditionally defined by LOC>6 hours and/or PTA>7 days (Bigler, 1990; Bond, 1986; Gerstenbrand & Stepan, 2001; Lezak et al., 2004). All participants were screened for major ps ychiatric disorder usi ng the Mental Health Screening Form-III (MHSF-III; Carroll & McGinl ey, 2000, 2001). Potential participants were excluded from the study for the following reasons: history of psychotic or bipolar disorder, learning disability, alcohol or s ubstance abuse within six months prior to testing, other acquired brain disorders (e.g., epilepsy, st roke), inpatient psychiatric tr eatment predating brain injury,

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84 clinically-significant depression or anxiety within two years prior to injury, or color-blindness as measured by the Ishihara pseudo-isochromatic color plates (Clark, 1924). Participants with language comprehension deficits or uncorrected visual impairments were also excluded. Injury characteristics and neuror adiological findings fo r this subset of TBI participants are presented in Table 4-2. TBI participants were at least six months post-inju ry, with the exception of one who was functioning well and desired to complete the study before returning to employment. No participants were engaged in legal action at the time of the study. Participant groups were well matched for age, t (19)=.18, p >.85, and education, t (19)=.79, p >.43. TBI participants endorsed significantly more depr essive symptoms, as measured by the Beck Depression Inventory-2nd Edition (BDI-II; Beck, 1996), t (19)=3.15, p <.01; however, no individual scores met common clinical cut-offs for depression (BDI-II>21) and mean scores for both groups were well within normal limitsnot m eeting criteria for ev en mild levels of depressive symptomatology (BDI-II>13; see Be ck, 1996). Groups did differ on their report of apathy symptoms on a modified vers ion of the Apathy Evaluation Scale (Marin, 1991; Marin et al., 1991; Starkstein et al., 1992), t (20)=2.22, p <.04, with TBI participan ts endorsing significant more symptoms. TBI participants en dorsed higher levels of state, t (19)=2.15, p <.05, but not trait anxiety symptoms, t (19)=1.10, p >.29, as measured by the State-Tr ait Anxiety Inventory (STAI; Speilberger et al., 1983). Experimental Task We utilized the experimental task employed by Holroyd et al., in their 2003 investigation of reward context and the FRN. In this task, pa rticipants viewed four circles in a row (OOOO) and were told that one of the circles containe d a reward of five cents that would be summed throughout the task and provided in addition to their hourly compensation. Circles remained on the screen until the participant responded by pres sing one of four keys placed directly below

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85 each circle on a response pad. A black screen was then presented for 500ms, followed by the feedback stimulus that remained on the screen for 2000ms. Reward feedback consisted of four dollar signs in a row ($$$$), wh ile non-reward feedback consisted of four Xs (XXXX). The interstimulus interval between the feedback stimulus and the subsequent trial was 500ms. All stimuli during the task were printed in yellow font on black background, visually centered, 0.6 high and 5.0 wide, and app eared on a 15 inch computer monitor ~40cm from the participants head. Participants were instructed that presentation of a reward feedback st imulus indicated they had received five cents, while presentation of a non-reward feedback stimulus indicated they received no money for that trial and that the goal of the task wa s to respond in a manner that would maximize their earnings. Unknown to the pa rticipants, feedback s timuli were presented randomly according to two separate reward probab ility conditions. In th e high reward probability condition, participants received positive feedback on 75% of trials, while in the low reward probability condition participants received positive feedback on only 25% of trials. Each condition consisted of one block of 200 trials. For example, participants presented with 200 trials during the high reward probability block received reward ($$$$) feedback on 150 trials (75%), while 50 trials (25%) showed non-reward f eedback (XXXX) for a sum of $7.50 earned. The probability of reward feedback was reversed in the low reward probability block. Order of block presentation was counterbalanced across partic ipants. Following completion of the first block, participants were told to take as much time as they desired to relax, and the amount of money they had achieved was displayed on the co mputer monitor (either $2.50 or $7.50). After completing the task, participants were debrie fed, and all were provided with $10 additional

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86 compensation. All participants re sponded to all trials and were awarded the same amount of compensation. Electrophysiological Data Recording and Reduction Electroencephalographic activity was recorded from 64 scalp sites using a geodesic sensor net and Electrical Geodesics, Inc., (EGI; E ugene, Oregon) amplifier system (20,000 gain, nominal bandpass=.10-100 Hz). Elec troencephalogram data were referenced to Cz and digitized continuously at 250Hz with a 16-bit analog-to-dig ital converter. A righ t posterior electrode served as common ground. Electrode im pedance was maintained below 50 k Eye movement and blink artifacts were corrected using a spatia l filtering method (Berg & Scherg, 1994; Ille et al., 1997, 2002). Data were segmented off-line a nd single trial epochs with voltages that exceeded 100V or transitional (sample-to-sample) thresholds of 75V were discarded. Electroencephalogram data were re-referenced to an average reference (Bertrand et al., 1985), and digitally low-pass filtered at 15 Hz. Individual-subject feedback-l ocked ERPs were derived separately for reward and nonreward trials for the two different feedback bl ocks (high and low reward probability) from 200ms beforeand 600ms following-feedback and we re baseline corrected using the 200ms prefeedback stimulus window. The FRN was quantified at electrode FCz. This electrode location was chosen because the FRN was largest there upon examination of grand-averaged waveforms and based on previous studies showing the FRN is maximal at this medio-frontal site (Hajcak et al., 2006; Holroyd et al., 2006; Holroyd et al., 2004; Holroyd et al., 2003). In light of previous findings that measur ement of the FRN can be confounded by potential overlap with other components (e.g., P300; Holr oyd et al., 2004; Holroyd et al., 2003), initial analyses of the FRN were completed by calcu lating difference waves subtracting the ERP

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87 associated with reward feedback from the ER P associated with non-reward feedback. The nonreward minus reward difference waves were al so calculated for fre quent and infrequent stimulus presentation contexts. The FRN was qu antified as the maximum negative amplitude of the difference wave between 125ms and 325ms post-feedback presentation. We next employed the peak-to-peak scoring approach used by Holroyd et al., (2003) and others (Hajcak et al., 2006; Ho lroyd et al., 2006; Yasuda et al ., 2004). Specifically, FRN peak-topeak amplitude was defined as the difference of the maximum value between 125ms and 325ms following feedback onset and the most negativ e point between this maximum and 325ms postfeedback presentation. One contro l participant had no measurable negative deflection, thus the FRN amplitude for this participant was scored as zero. To assess the potential for generalized ERP amplitude decrements or latency shifts in TBI participant ERP waveforms, N1 amplitude and la tency data was extracted as the amplitude and latency of the first peak nega tive deflection in the ERP between 50 and 200ms for both reward and non-reward trials at posterior electrode si te 38 (location of maximum N1 amplitude). Data Analysis Median RTs as well as ERP (N1, FRN) amplitude and latency data were analyzed separately using repeated-measures analyses of variance (ANOVAs). The Huynh-Feldt epsilon adjustment was applied for ANOVAs with more th an two levels of a w ithin-subject factor and partial-eta2 ( 2 ) reported as a measure of effect si ze. Initial ANOVAs for RT and feedbackrelated ERP activity included group (TBI, control) as the between-subjects factor and feedback probability condition (high, low reward probabil ity) as the within-subject factor. Planned comparisons were used to decompose main effect s and interactions and to examine the feedback

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88 factor separately within the high and low reward probability blocks. Cohens-d effect sizes (Cohen, 1988) were calculated for condition-related effects. Results Behavioral Data Median RTs for each feedback type in the high and low reward probability conditions are presented in Table 4-3. A Group x Feedback ANOVA showed no significant main effect of reward condition, F(1,19)=2.46, p>.14, 2=.11, no Group x Feedback interaction, F(1,19)=.38, p>.38, 2=.04, and no significant main effect of group, F(1,19)=1.71, p>.21, 2=.08. ERP Data A total of 12% of trials were rejected from averaging due to artifact in the EEG. Control and TBI participants did not differ on number of tr ials retained for averaging under either high or low reward probability conditions, t s(19) .96, p s>.35. Per participant, reward waveforms contained an average of 180 (SD =; range=166 to 193) trials for controls and 174 (SD =; 133 to 193) trials for TBI participants, while non -reward waveforms contained an average of 179 (SD =; 151 to 198) trials for controls and 170 (SD =; 108 to 197) trials for TBI participants. N1 amplitude and latency. A Group x Feedback ANOVA on feedback-locked grand average ERP waveforms was conducted to examin e the possibility of generalized amplitude decrements or latency shifts for TBI participan ts. Results of the analysis of N1 amplitude indicate no main effect of reward condition, F (1,19)=1.13, p >.30, 2 =.06, no Group x Feedback interaction, F (1,19)=.23, p >.63, 2 =.01, and no main effect of group, F (1,19)=1.84, p >.19, 2 =.09. Latency data were similar, with no significant Group x Feedback interaction, F (1,19)=2.12, p >.16, 2 =.21, and no main effect of group, F (1,19)=1.39, p >.25, 2 =.07. Thus,

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89 data suggest that there is not a significant generalized amplitude d ecrement or latency shift in the ERPs of the TBI participants relative to heal thy controls. FRN difference wave analysis. Feedback-locked grand average ERP waveforms for reward and non-reward conditions and accomp anying non-reward minus reward difference waves are presented collapsed ac ross reward context conditions in Figure 4-1 and as a function of feedback frequency (high or low reward proba bility) in Figure 4-2. Spline-interpolated scalp voltage maps of the difference waves are pres ented in Figure 4-3, with FRN difference wave amplitude data shown in Table 4-4. As anticip ated, feedback-locked ERPs showed an FRN occurring at a mean latency of 261ms in c ontrol and 233ms in TBI participants. Planned comparisons of non-reward minus reward difference waves showed no differences between groups, t (19)=.72, p >.47, d =.32. Subsequent between-groups an alyses on FRN difference waves as a function of frequent and infrequent feedb ack presentation also yi elded no group differences on either frequent, t (19)=.93, p >.37,d =.41 or infrequent, t (19)=-.71, p >.48, d =.30, stimulus presentation. As evident in Figures 4-1 and 4-2, difference waves are insensitive to equivalent changes across feedback conditions. For example, the positiv ity following reward trials in the low reward probability block for TBI participan ts is increased in direct pr oportion to the slight negativity following non-reward trials (FRN)--leading to the appearance of a large negative difference. In contrast, the amplitude of the negativity (FRN) at approximately the same latency for control participants in the low reward probability bloc k is much greater than the positivity. Thus, the finding of equivalent FRN difference waves between TBI and control participants is spurious and confounded by the variations in waveform morphology between-groups. Consequently, although unable to make direct conclusions a bout the FRN without taking into account the

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90 possibility of component overlap, we conducted p eak-to-peak analyses to directly examine the negative deflection of the FRN. FRN peak-to-peak analysis. FRN component amplitude and latency data are presented in Table 4-4. A Group x Feedback ANOVA yielded a nonsignificant main effect of feedback condition, F (1,19)=1.84, p >.19, 2 =.09. More importantly, ther e was a significant Group x Feedback interaction, F (1,19)=9.76, p <.006, 2 =.34. Planned contrasts revealed that the FRN was significantly larger following non-reward than reward feedback in controls, t (10)=2.64, p <.025, d =.67, but not TBI participants, t (9)=-1.85, p >.10, d =.25. The interaction was found in the absence of an overall main effect of group on FRN amplitude, F (1,19)=0.19, p >.66, 2=.01, further suggesting the effect is not due to an overall attenuation of ERP component amplitudes in TBI participants. After verifying the two groups exhibited diffe rent neural responses to feedback, we conducted a series of planned contra sts to test the specific hypothese s that: 1) control participants would show the largest FRN in response to non-re ward feedback when a reward was expected (i.e., non-reward feedback in the high reward probability block); 2) FRN amplitude would not differ as a function of feedback condition when n on-reward stimuli were predicted (i.e., during the low reward probability block); and, 3) FR N amplitude would not differ as a function of condition during the high and low reward probab ility blocks in TBI participants due to impairments in reward context sensitivity. Paired-samples t -tests conducted separately for each group confirmed these hypotheses, w ith control participants show ing significantly larger FRN amplitude to non-reward stimuli during the high reward probability block, t (10)=2.40, p <.03, d =.80; control participants not differentiating between reward and non-reward feedback during the low reward probability block, t (10)=.03, p >.90, d =.01; and, TBI participants showing no

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91 differences between feedback conditions in the high reward probability block, t (9)=.52, p >.60, d =.12. Interestingly, TBI participants showed si gnificantly larger FRN amplitude to reward stimuli during the low reward probability block, t (9)=2.54, p <.03, d =.47. Figure 4-2 presents the grand average waveforms as a function of feedb ack type and reward probability condition for TBI and control groups. FRN latency. A Group x Feedback ANOVA yielded no significant main effects or interactions on FRN latency (p s>.18). Discussion Results of the current stu dy largely supported our primary hypotheses regarding impaired neural processing of reward and non-reward stimuli following severe TBI. First, TBI participants demonstrated generally reduced feedback-relat ed ERP differentiation between reward and nonreward conditions relative to he althy control participants. That is, TBI participants showed feedback-related ERP activity, but the amplitude of this activity did not differentiate between reward and non-reward feedback. In contrast, co ntrol participants showed significantly larger FRN amplitude following non-reward relative to rewa rd trials. The results in control participants replicate previous studies of reward feedback on guessing task s (Holroyd et al., 2003; Ruchsow et al., 2002), while results in TB I participants suggest that thes e survivors are largely responsive to feedback, but do not generally differentiate reward and non-reward contingencies at the electrophysiological level. Moreover, the finding that the control and TB I groups did not differ on N1 amplitude or latency, or in the overall amplitude of f eedback-related ERPs, provides evidence that the feedback-related differences do not simply reflect a more generalized ERP decrement in the TBI survivors. Second, TBI and control partic ipants differed in their sens itivity to reward context. Consistent with the hypothesis that the FRN is largest when reward-probability context is high

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92 but a non-reward is obtained (Holroyd & Coles, 2002; Holroyd et al., 2003), control participants showed the largest FRN to non-reward stimuli in the high reward-probability context, but did not differentiate between reward condi tions in the low-reward probabil ity context. TBI participants showed the opposite pattern of findings, with no differentiation between reward and non-reward trials in the high reward-probability context, but significantly larger FRN following reward stimulus presentation in the low reward-probabil ity context. This finding was unanticipated, as FRN amplitude in TBI participants did not ge nerally differentiate reward and non-reward feedback and previous studies show FRN amp litude is largest when rewards/goals are not obtained, rather then when feedb ack indicates reward attainment (Hajcak et al., 2006; Holroyd et al., 2004). This reversal in the direction of the reward-context effect on FR N in TBI participants could reflect the possibility that obtaining a monetary reward is more meaningful and less expected in TBI participants. That is, it may be that monetary incentives had a stronger motivating effect on TBI participants as they we re largely unemployed or on disability at the time of the study. More likely is the possibility that survivors of severe TBI show generally altered reactivity to feedback and change in rewa rd context. As a whole, the current findings that TBI participants did not respond di fferentially to non-reward trials in the high reward-probability context and that FRN amplitude increased when a reward was presented during low reward probability blocks provides support for the hypothe sis that reward feedback processing is impaired relative to control participants. Nota bly, between-groups FRN differences were found in the absence of significant effects of RT or fr equency of feedback presentation (i.e., frequent vs. infrequent feedback within reward or non-reward blocks), suggesting speed of response/reward presentation and frequent/infre quent feedback presen tation are not underlying reasons for the current findings.

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93 To the authors knowledge, this is the first study to expose deficienci es in reward-context sensitivity in participants with TBI. That is, ne ural reflections of reward processing in both high and low reward probability conditions were not differentiated in TBI participants and did not follow the pattern of results in control particip ants. Findings fit well into a burgeoning literature that implicates performance-monitoring defici ts likely associated with medial-frontal cortex/ACC dysfunction following se vere TBI (see General Discussion below). Results are also consistent with studies of individuals who have sustained damage to neuroanatomical structures strongly implicated in reward-pro cessing, such as the ventral stri atum, ventromedial/orbitofrontal cortex, and limbic system (Bechara et al., 2000 ; Bechara et al., 1996) that show impaired sensitivity to reward contingencies. Furthermore, recent studies suggest altered striatal dopamine activity following head injury contributes to de ficits in cognitive performance (Wagner et al., 2005) and dopamine agonists have been show n to improve some aspects of cognitive performance following TBI (Kaelin et al., 1996; McAllister et al., 2004; Napolitano et al., 2005; Plenger et al., 1996). Thus, future research should examine the role of the dopaminergic system in reward context sensitivity deficits following TBI, as well as the possible pharmaco-therapeutic role of dopamine agonists (c.f ., McAllister et al., 2004). Results of this study suggest several implications for clin ical application and future research. First, this study adds to the literature by suggesting participants with TBI show reduced sensitivity to reward contexta key component to learning (and re-learn ing) of appropriate behaviors in the rehabilitation sett ing. Thus, clinicians should be vigilant to these decrements and realize learning of appropriate and non-risky behaviors and deci sion-making strategies may be difficult and time-consuming. Second, results pr ovide insight into the neural mechanisms underlying previous findings of impaired stimul us-response contingencies in behavioral studies

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94 by demonstrated alterations in the neurobiological reflections of reward context sensitivity following TBI. Thus, a potential future line of research might examine the neurobiological instantiation of reward context processing with response-based contingencies as well as reward context utilization changes following rehabilita tion targeting feedback processing, contingencyutilization skills, and risk-taking behaviors. Finally, results suggest a continued need for emphasis on decision-making skills in rehabili tation. Few empirically supported treatments currently target such deficits, though studies have begun to examin e this domain (Levine et al., 2000; Park et al., 2003). Utilization of cognitiv e neuroscience methods (e.g., ERPs, functional magnetic resonance imaging) may aid in eluc idating the mechanisms and corroborating the efficacy of potential re habilitation strategies. Findings of the current study must be considered within the context of potential limitations and alternative explanations. First, the small sample size limits the extent findings can be generalized to a larger popul ation of TBI survivors. Second, the current study employed a guessing paradigm where feedback stimuli were presented in a pseudorandom fashion, rather than according to participant perf ormance; that is, feedback wa s not response contingent. Thus, the task paradigm precludes our ability to exam ine behavioral data and strategic adjustments critical to evaluative control following feedback presentation. In addition, the ambiguous results of the difference-wave analyses and utiliza tion of peak-to-peak measurement leave open questions regarding the possibili ty of component overlap and a lternative contributions to FRN differences between groups (e.g., potential overlap of the P300 or N2 components). Third, it is possible that individuals with a bnormal reward processing are more likely to suffer a TBI. Thus, group differentiation of the FRN could be due to pre-existing differences, rather than a direct

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95 consequence of TBI. Finally, gr oups differed on levels of depr ession, anxiety, and apathy. Each of these factors may have contributed to reduc e FRN amplitude in participants with TBI. Present findings implicate impaired evaluative control mechanisms in survivors of severe TBI. The finding of an electrophysiological marker of impaired reward context sensitivity adds to the growing body of literature suggesting that, compared to c ontrol participants, severe TBI survivors have difficulty monito ring their performance and envir onment. This study also places further emphasis on the need for continued use of cognitive neuroscience methods to increase understanding of the neurobiological bases of TBI-related dysfunction and provide a strong foundation for the potential development and validation of rehabilitation treatments.

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96 Table 4-1. Mean ( Standard Deviation) demographic da ta for control and TBI participants Definition of abbreviations: BDI-II = Beck Depre ssion Inventory-II; STAI = State-Trait Anxiety Inventory Control (n = 11) TBI (n = 10) # males/# females 7/47/3 Age (years) 27.2 (11.1)26.4 (8.2) Education (years) 14.1 (1.6)13.5 (1.8) BDI-II 2.8 (2.8)9.6 (6.5) Apathy evaluation scale 11.0 (5.2)7.0 (3.0) STAI-state 26.1 (4.8)30.9 (5.5) STAI-trait 29.5 (6.4)32.7 (7.3)

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97 Table 4-2. Injury characteristics and neurorad iological information for TBI participants. Age (yrs) Sex Etiology GCS LOC (days) PTA (days) Months Post Injury Neuroradiological Findings 21 M MVA 3 429020Right frontal subdural hematoma; multiple skull fractures 20 F MVA 3 141619Right frontal contusions; shear injury to left frontoparietal lobe; subarachnoid hemorrhage with interpeduncular cistern 25 F MVA 3 302117Left occipital condoyle fracture; subdural hematoma 22 F Rollover MVA 3 72119Left supraorbital hematoma; right frontal hematoma; bifrontal contusionsleft greater than right 21 M MVA 3 41506Unavailable 35 M Collision with wall 8 7N/A15Nondepressed right temporal bone fracture leading to subdural hematoma; blood on right thalamus and left internal capsule; small uncal herniation 36 M Motorcycle accident 3 30364Small bilateral intraventricular hemorrhages; no additional findings 18 M MVA 7 43112Bilateral frontal contusions-more prominent right frontal; effacement of cortical sulci and basal cisterns 42 M MVA 3 101206Intraventricular hemorrhage, basilar skull fracture 21 M Motorcycle accident 3 123318Right temporal contusions; right frontal subarachnoid hemorrhage; microhemorrhages along graywhite junction of left hemisphere and right parietal lobe 26.4 (8.2) --3.9 (1.9) 19.7 (14.6) 46.4 (35.4) 13.6 (6.1) -Note: Last row is Mean ( Standard Deviation) values. LOC and PTA are shown in days unless otherwise specified. Neuroradio logical findings taken from medical record review of neuroradiological reports from CT scans taken acutely af ter injury. MVA = Motor Vehicle Accident; GCS = Glascow Coma Scale; LOC = Loss of consciousness; PTA = Post-traumatic amnesia

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98 Table 4-3. Mean ( Standard Deviation) reaction times for control and TBI participants Control (n = 11) TBI (n = 10) Reaction Times (ms) Non-Reward Reward 474.7 (231.4) 454.9 (252.3) 731.3 (577.5) 659.4 (445.8) Table 4-4. Mean ( Standard Deviation) non-reward minus reward difference wave ( V) Table 4-5. Mean ( Standard Deviation) peak-to-peak component amplitude ( V) and latency (ms) as a function of feedback condition for the FRN. Control TBI Control TBI Amplitude ( V) Latency (ms) FRN Reward Non-reward -2.4 (1.7) -3.6 (1.9) -2.89 (1.9) -2.42 (1.7) 239.6 (35.5) 261.5 (26.1) 229.6 (34.8) 232.8 (41.6) Frequent presentation Reward Non-reward -2.4 (1.6) -3.6 (1.9) -2.89 (1.9) -2.46 (1.7) 238.4 (37.1) 259.3 (28.2) 230.8 (33.5) 217.6 (41.2) Infrequent presentation Reward Non-reward -3.6 (2.6) -4.0 (2.4) -3.22 (1.6) -3.09 (1.5) 251.6 (30.8) 266.9 (25.0) 239.6 (39.4) 249.6 (41.2) Control (n= 11) TBI (n = 10) Amplitude ( V) FRN difference -2.7 (1.5)-2.2 (1.2) Frequent difference -2.9 (1.8)-2.2 (1.7) Infrequent difference -2.1 (2.6)-2.8 (1.6)

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99 Figure 4-1. Grand average ERP waveforms depic ting feedback-locked reward and non-reward activity as well as the non-reward minus rewa rd difference wave at recording site FCz for control (top) and TBI (bottom) partic ipants. denotes approximate location of FRN. Figure 4-2. Grand average feedback-locked ER P waveforms showing reward and non-reward activity as well as non-reward minus reward difference waves at recording site FCz for the high frequency trials (e.g., reward tr ial in a high reward probability condition) and low frequency trials (e.g., reward trial in low reward probab ility condition) in control (top) and TBI bottom) participants denotes approximate location of the FRN.

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100 Figure 4-3. Spline-interpolated vo ltage maps of the non-reward minus reward difference wave at 280ms for control (top) and TBI (bottom) participants.

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101 CHAPTER 5 GENERAL DISCUSSION The previous chapters examined evaluative control processes following severe TBI. Specific aims of these studies were to: 1) test the prediction that survi vors of severe TBI show impairments in their ability to detect errors a nd response conflict (i.e., when representations of more than one response are simultaneously activated ) and subsequently show decrements in their ability to reactively adjust performance to adapt to changing task demands; 2) test the prediction that survivors of severe TBI exhi bit deficits in the evaluative c ontrol process of reward context monitoring and, subsequently, show decrements in th eir ability to evaluate feedback and reward; 3) compare behavioral and neur obiological indices of evaluative control to measurements of deficit awareness in TBI participants, with th e prediction that larger magnitude evaluative control deficits would be associated with poorer deficit awareness. Findings indicate impaired elec trophysiological manifestati ons of evaluative control (including feedback processing) fo llowing severe TBI. The ERN, an ERP reflection of errorand performance-monitoring, was attenu ated in participants with TBI as was the conflict SP, an ERP deflection thought to reflect regul ative aspects of conflict proc essing. Similarly, the FRN, an index of feedback context and monitoring, dem onstrated generally reduced feedback-related ERP differentiation between reward and non-rewa rd contexts in participants with TBI. Importantly, group-wise differences in these reflections of evaluative control were found in the absence of differences in early sensory components of the ERP (i.e., P1 or N1 amplitude or latency) and the absence of group main effect s on ERP amplitudes--suggesting differences do not simply reflect more generalized attenuations in ERP signatures following TBI. Given this, the ERN, FRN, and potentially the conflict SP re present possible neurob iological markers of impaired evaluative control following severe TBI.

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102 While supporting our hypothesis th at survivors of TBI exhibit impaired evaluative control processes, the ERP results do not directly addre ss critical questions regarding the source or mechanism underlying the ERP manifestation of evaluative contro l dysfunction. Reducedamplitude ERP components may be due to a number of factors not directly reflective of an underlying impairment in the process of interest. For example, signal averaging for creation of ERPs is based on the assumption of across-trial time (and amplitude) invariance. It is conceivable that participants with TBI exhibit greater variability in the latency of peak response (i.e., latency jitter), violating this invarian ce assumption, and resulting in spuriously reducedamplitude ERP components. While methods exis t for evaluating single-trial ERP data and adjusting for latency jitter (e.g., Mcks et al., 1988; Picton et al ., 1995; Woody, 1967), their effectiveness is limited to large-amplitude ERP components (e.g., P 300) and may not yield reliable or valid effects for the smaller component s examined in the present research. In addition, the possibility of alterations in cortical geomet ry, volume, and electrical conductivity in the TBI patient group (e.g., lesions, pooling blood, etc) may gi ve rise to spurious amplitude reductions in ERP component amplitudes. Specifically, the propag ation or volume conduction of potentials to the scalp surface, and therefore their scalp distri bution, can be altered by the presence of injuryrelated factors. These can result in altered amplitude or scalp dist ribution of the ERP, consequently challenging the assumption that us ing identical measurement electrode sites across the different groups will yield similar measur ement sensitivity to the ERP components of interest. Another alternative explan ation is that the current sample of participants w ith TBI is quite heterogeneous, as are the majority indivi duals in the severe TBI population. Thus, the heterogeneity of mechanism of injury, lesion lo cation, and level of recovery post-TBI preclude

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103 specific conclusions regarding lesi on location or pathology and eval uative control de ficits in the current sample. Finally, many studies comparing neurologically-impaired participants with healthy controls have difficulty with the interp retation of ERP results due to differences in behavioral performance. For example, TBI partic ipants had a higher number of errors included in analyses of the ERN than control participants. Th is may lead to differences in signal-to-noise ratio, potentially reducing or amp lifying ERP components of interest. Control and TBI participants did not differ on several behavi oral (i.e., RT, error rate) indices of evaluative control. On the Stroop ta sk, participants with TB I did not commit more errors than control participan ts nor did they commit dispr oportionately more errors on incongruent trials. Thes e findings were not completely une xpected. Seignourel et al., (2005) utilized a cued version of the single-trial Stroop task to dem onstrate error rate differences between severe TBI participants and healthy controls were due to deficits in the ability to maintain context information (i.e., whether th e task was color-naming or word-reading) as opposed to a more general deficit in inhibition of pre-potent response te ndencies. Due to task context being maintained throughou t the current color-naming paradi gm for the participants (i.e., the appropriate response was to name the color fo r all trials), the lack of differences between groups provides further support for deficits in context-maintenance, rather than response inhibition, following severe TBI. More unexpected was the finding th at, other than generalized sl owing in participants with TBI, groups did not differ on reactive conflict ad aptation adjustments. While consistent with other findings of non-ACC specific head trauma and older adult patient groups, the findings can lead to questions regarding the heterogeneity of injury in the current sample and the specificity of ACC-mediated cognitive control mechanisms (d i Pellegrino et al., 2007). For example, some

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104 TBI participants may have specific deficits in re gulative function, but inta ct evaluative functions. Others, in contrast, may have intact regula tive control processes a nd impaired evaluative processes. Examination of the data in group form at, therefore, obscures our ability to look at individual-specific deficits in cognitive control component pro cesses. Future research that capitalizes on the heterogeneity present in TBI samples by identifying clinically-meaningful subtypes would be beneficial in elucidating the cognitive control deficits, but even more helpful in the context of rehabilitation where rehabilita tion techniques can be empirically tested and tailored to improve specific de ficits in cognitive control func tion. As the current paradigm does not temporally dissociate regula tive and evaluative aspe cts of cognitive cont rol without potential component overlap, future research is needed to address this possibility. Results of the current studies do not support an association between evaluative control functioning and awareness of TBI-related deficits. Behavioral and ERP indi ces of conflict/error processing were not related to tw o measures of deficit awareness. Deficit awareness represents a challenging measurement construct as caregiver bias and hypervigil ance to deficits can prejudice self-/other concordance scores and a strong knowledge of partic ipant functioning is required for clinical rated measures. Thus, the two measures employed in the current studies may not have been sensitive to the potential relationships between deficit awar eness and evaluative control. In addition, deficit awareness is a different constr uct than the on-line ev aluation of performance and errors associated with evaluative control. Thus, future research directly examining a participants knowledge of performance while the task is completed may be more sensitive to potential relationships w ith deficit awareness. As a whole, this dissertation represents an im portant step in the application of cognitive neuroscience principles and tool s to elucidate evaluative control mechanisms following severe

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105 TBI. Future research and longer-term goals th at build upon this research examining cognitive control adjustments in TBI as a function of TB I severity (as in Larson et al., 2006a), subtyping TBI survivors based on primary deficits in regula tive or evaluative control processes, testing the neurobiological manifestations of recovery preand post-rehab ilitation with techniques designed to remediate difficulties in regulative control or evaluative control, elucidating the relationship between evaluative control manifestations and o n-line awareness of errors (rather than general awareness of deficits), and examining the role of performance feedback (rather than randomly presented monetary feedback) to predict corrective behavior following severe TBI.

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106 LIST OF REFERENCES Adams, J.H. (1984). Head Injury. In J. H. Ad ams, J.A.N. Corsellis & C.W. Duchen (Eds.), Greenfield's Neuropathology (4th Edition ed., pp. 85124). London: Edward Arnold. Adams, J. H., Graham, D. I., Murray, L. S., & Sc ott, G. (1982). Diffuse axonal injury due to nonmissile head injury in huma ns: An analysis of 45 cases. Annals of Neurology, 12 557-563. Adams, J. H., Scott, G., Parker, L. S., Graham, D. I., & Doyle, D. (1980). The contusion index: A quantitative approach to cerebra l contusions in head injury. Neuropathology and Applied Neurobiology, 6 319-324. Allen, C. C., & Ruff, R. M. (1990). Self-rating versus neurop sychological performance of moderate versus severe head-injured patients. Brain Injury, 4 7-17. Anderson, V., Levin, H. S., & Jacobs, R. (2002). Ex ecutive functions after fr ontal lobe injury: A developmental perspective. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function New York: Oxford University Press. Bate, A. J., Mathias, J. L., & Crawford, J. R. (2001). Performance on the Test of Everyday Attention and standard test s of attention following seve re traumatic brain injury. Clinical Neuropsychology, 15 405-422. Beck, A. T. (1996). Beck Depression Inventory Second Edition (BDI-II) USA: The Psychological Corporation. Bechara, A. (2004). The role of emotion in decision-making: Evid ence from neurological patients with orbitofrontal damage. Brain Cognition, 55 30-40. Bechara, A., Damasio, A. R., Damasio, H., & A nderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50 7-15. Bechara, A., Tranel, D., & Damasio, H. (2000). Ch aracterization of the d ecision-making deficit of patients with ventromedial prefrontal cortext lesions. Brain, 123 2189-2202. Bechara, A., Tranel, D., Damasio, H., & Damasio, A. R. (1996). Failure to respond autonomically to anticipated future outcomes following damage to the prefrontal cortex. Cerebral Cortex, 6 215-225. Benton, A., & Hamsher, K. (1976). Multilingual aphasia examination. Iowa City: University of Iowa. Berg, P., & Scherg, M. (1994). A multiple source approach to the correction of eye artifacts. Electroencephalography and Clinical Neurophysiology, 90 229-241.

PAGE 107

107 Bergquist, T. F., & Jacket, M. P. (1993). Awarene ss and goal setting with the traumatically brain injured. Brain Injury, 7 275-282. Bertrand, O., Perrin, F., & Pernier, J. (1985). A theo retical justification of the average-reference in topographic evoked potential studies. Electroencephalography and Clinical Neurophysiology, 62 462-464. Bigler, E. D. (1990). Neuropath ology of traumatic brain injury In E. D. Bigler (Ed.), Traumatic Brain Injury Austin, TX: Pro-ed. Bigler, E.D. (1999). Neuroimagi ng in mild TBI. In N.R. Varney & R.J. Roberts (Eds.), The evaluation and treatment of m ild traumatic brain injury (pp. 63-80). Mahwah, New Jersey: Lawrence Erlbaum Associates. Bogod, N. M., Mateer, C. A., & Macdonald, S. W. S. (2003). Self-awareness after traumatic brain injury: A comparison of measures a nd their relationship to executive functions. Journal of the International Neuropsychological Society, 9 450-458. Bond, M. R. (1986). Neurobehavioral sequelae of closed head injur y. In I. Grant & K. M. Adams (Eds.), Neuropsychological assessment of neuropsychological disorders (pp. 347-373). New York: Oxford University Press. Botvinick, M., Carter, C. S., Braver, T. S., Barch, D. M., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108 624-652. Botvinick, M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. Trends in Cognitive Sciences, 8 539-546. Botvinick, M., Nystrom, L. E., Fissell, K., Ca rter, C. S., & Cohen, J. D. (1999). Conflict monitoring versus selection-for-ac tion in anterior cingulate cortex. Nature, 402 179-181. Botwinick, J., Storandt, M., Berg, L., & Boland, S. (1988). Senile dementia of the Alzheimer's type: Subject attrition and testability in research. Archives of Neurology, 45 493-496. Buchanan, R. W., Strauss, M. E., Kirkpatrick, C. H., Breier, A., & Ca rpenter, J. (1994). Neuropsychological impairments in deficit and non-deficit forms of schizophrenia. Archives of General Psychiatry, 51 801-811. Butters, M. A., Kaszniak, A. W., Glisky, E. L., Eslinger, P. J., & Schachter, D. L. (1994). Recency discrimination deficits in frontal lobe patients. Neuropsychology, 8 343-353. Brandt, J., & Benedi ct, R.H.B. (2001). Hopkins Verbal Learning Te st--Revised. Professional Manual. Lutz, Fl: Psychological Assessment Resources.

PAGE 108

108 Braver, T. S., Barch, D. M., & Cohen, J. D. (1999). Cognition and control in schizophrenia: A computational model of dopamine and prefrontal function. Biological Psychiatry, 46 312-328. Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M., Noll, D., & Cohen, J.D. (1998). Anterior cingulate cortex, e rror detection, and the online monitoring of performance. Science, 280 747-749. Carroll, J. F. X., & McGinley, J. J. (2000). Mental Health Screening Form-III (MHSF-III) New York, N.Y.: Project Return Foundation, Inc. Carroll, J. F. X., & McGinley, J. J. (2001). A screening form for iden tifying mental health problems in alcohol/other drug dependent persons. Alcoholism Treatment Quarterly, 19 33-47. Cazalis, F., Feydy, A., Valabregue, R., Pelegrini-Issac, M., Pierot L., & Azouvi, P. (2006). fMRI study of problem-solving after se vere traumatic brain injury. Brain Injury, 20, 10191028. Centers for Disease Control (1999). Traumatic brain injury in the United States: A report to congress Atlanta, GA: Centers for Disease Control and Prevention. Christodoulou, C., DeLuca, J., Ricker, J. H., Ma digan, N. K., Bly, B. M., Lange, G., Kalnin, A.J., Liu, W.C., Steffener, J., Diamond, B.J., & Ni, A.C. (2001). Functional magnetic resonance imaging of working memory impa irment following traumatic brain injury. Journal of Neurology, Neurosurgery, and Psychiatry, 71 161-168. Clark, J. H. (1924). The Ishiha ra test for color blindness. American Journal of Physiological Optics, 5 269-276. Cohen, J. (1988). Statistical power analysis for the behavioral sciences Hillsdale, NJ: Erlbaum Associates. Cohen, J. D., Botvinick, M., & Carter, C. S. ( 2000). Anterior cingulate an d prefrontal cortex: Who's in control? Nature Neuroscience, 3 421-423. Cohen, J.D., Servan-Schreiber, D., & McClelland, J.L. (1992). A parallel distributed processing approach to automaticity. American Journal of Psychology, 105, 239-269. Damasio, A. R., & Anderson, S. W. (1993). The frontal lobes. In K. M. Heilman & E. Valenstein (Eds.), Clinical Neuropsychology (pp. 409-460). New York: Oxford University Press. Dias, R., & Aggleton, J. P. (2000). Effects of selective excitotoxic pr efrontal lesions on acquisition of non-matching and matching-to-pl ace in the T-maze in the rat: Differential involvement of the prelimbic-infralimbic a nd anterior cingulate cortices in providing behavioral flexibility. European Journal of Neuroscience, 12 4457-4466.

PAGE 109

109 Dirette, D. (2002). The developm ent of awareness and the use of compensatory strategies for cognitive deficits. Brain Injury, 16 861-871. Di Russo, F., Martinez, A., Sereno, M.I., Pitzalis, S., & Hillyard, S. A. (2002). Cortical sources of the early component of th e visual evoked potential. Human Brain Mapping, 15, 95-111. Di Pellegrino, G., Ciaramelli, E., & Ladavas, E. (2007). The regulation of cognitive control following rostral anterior cingulate cortex lesion in humans. Journal of Cognitive Neuroscience, 19, 275-286. Egner, T., & Hirsch, J. The neural correlates of functional integration of cognitive control in a Stroop task. Neuroimage, 15, 539-547. Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon th e identification of a target letter in a nonsearch task. Perception & Psychophysics, 16 143-149. Falkenstein, M., Hohnsbein, J., Hoormann, J., & Ba nke, L. (1991). Effects of crossmodal divided attention on late ERP compone nts. II. Error processing in choice reaction tasks. Electroencephalography and Clinical Neurophysiology, 78 447-455. Falkenstein, M., Hoormann, J., Christ, S., & H ohnsbein, J. (2000). ERP components on reaction errors and their functional significance: A tutorial. Biological Psychology, 51 87-107. Finkelstein, E.A., Corso, P.S., & Miller, T.R. (2006). Incidence and economic burden of injuries in the United States New York, NY: Oxford University Press. Flashman, L.A., & McAllister, T.W. (2002). Lack of awareness and its impact in traumatic brain injury. Neurorehabilitation, 17, 285-296. Fleming, J., & Strong, J. (1995). Self-awareness of deficits fo llowing acquired brain injury: Considerations for rehabilitation. British Journal of O ccupational Therapy, 58 55-60. Fleming, J. M., Strong, J., & Ashton, R. (1996). Self-awareness of deficits in adults with traumatic brain injury: How best to measure? Brain Injury, 10 1-15. Fontaine, A., Azouvi, P., Bussel, B., & Samson, Y. (1996). Prefrontal and cingulate dysfunction at the subacute stage following severe cl osed head injury: A high resolution PET study. Proceedings of the Australian Brain Injury Society, 1 98-104. Fuster, J. M. (1997). The prefrontal cortex. Anatomy, phy siology, and neuropsychology of the frontal lobe. (3rd ed. ed.). Philadelphia: Lippincott-Raven. Gehring, W. J., & Fencsik, D. E. (2001). Functions of the medial frontal co rtex in the processing of conflict and errors. The Journal of Neuroscience, 21 9430-9437.

PAGE 110

110 Gehring, W. J., Goss, B., Coles, M. G. H., Meye r, D. E., & Donchin, E. (1993). A neural system for error detection and compensation. Psychological Science, 4 385-390. Gehring, W. J., & Knight, R. T. (2000). Prefront al-cingulate interactions in action monitoring. Nature Neuroscience, 3 516-520. Gehring, W. J., & Willoughby, A. R. (2002). The medi al frontal cortex and the rapid processing of monetary gains and losses. Science, 295 2279-2282. Gemba, H., Sasaki, K., & Brooks, V. B. (1986). 'Error' potentials in lim bic cortex (anterior cingulate area 24) of monkeys during motor learning. Neuroscience Letters, 70 223-227. Gerstenbrand, F., & Stepan, C. H. ( 2001). Mild traumatic brain injury. Brain Injury, 15 95-97. Grace, J., & Malloy, P. F. (2001). Frontal Systems Behavior Scale Professional Manual Lutz, FL: Psychological Assessment Resources, Inc. Grafman, J., Schwab, K., Warden, D., Pridgen, A., Brown, H. R., & Salazar, A. M. (1996). Frontal lobe injuries, violen ce, and aggression: A report of the Vietnam Head Injury Study. Neurology, 46 1231-1238. Grapperon, J., Vidal, F., & Leni, P. (1988). Th e contribution of cognitiv e evoked potentials to knowledge mechanisms of the Stroop color-word interference effect. Neuropsychologia, 38 701-711. Gratton, G., Coles, M.G., & Donchin, E. (1992). Optimizing the use of information: Strategic control of activation of responses. Journal of Experimental Psychology: General, 121, 480-506. Gronwall, D., & Wrightson, P. (1981). Memory and information processing capacity after closed head injury. Journal of Neurology, Neurosurgery, and Psychiatry, 44 889-895. Hajcak, G., McDonald, N., & Simons, R. F. (2003a ). To err is autonomic: Error-related brain potentials, ANS activity, and posterror compensatory behavior. Psychophysiology, 40 895-903. Hajcak, G., McDonald, N., & Simons, R. F. ( 2003b). Anxiety and error-r elated brain activity. Biological Psychology, 64 77-90. Hajcak, G., Moser, J. S., Holroyd, C. B., & Simons, R. F. (2006). The feedback-related negativity reflects the bi nary evaluation of good versus bad outcomes. Biological Psychology, 71 148-154. Hart, T., Giovannetti, M. S., Montgomery, M. W ., & Schwartz, M. F. C. (1998). Awareness of errors in naturalistic action after traumatic brain injury. Journal of Head Trauma, 13 1628.

PAGE 111

111 Hart, T., Whyte, J., Junghoon, K ., & Vaccaro, M. (2005). Executive function and self-awareness of "real-world" behavior a nd attention deficits following traumatic brain injury. Journal of Head Trauma Rehabilitation, 20 333-347. Hart, T., Whyte, J., Polansky, M., Millis, S., Hammond, F. M., Sherer, M., Bushnik, T., Hanks, R., & Kreutzer, J. (2003). Concordance of pa tient and family report of neurobehavioral symptoms at 1 year after traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 84 221-230. Henry, J.D., & Crawford, J.R. (2004). A meta-analy tic review of verbal fluency performance in patients with traumatic brain injury. Neuropsychology, 18, 621-628. Holroyd, C.B. (2004). A note on the Oddball N200 and the feedback ERN. In M. Ullsperger & M. Falkenstein (Eds.), Errors, Conflicts, a nd the Brain. Current Opinions in Performance Monitoring, (pp. 211-218). Leipzig: MPI of Cognitive Neuroscience. Holroyd, C. B., & Coles, M. G. H. (2002). Th e neural basis of hu man error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109 679-709. Holroyd, C. B., Hajcak, G., & Larsen, J. T. (2006). The good, the bad, and the neutral: Electrophysiological responses to feedback stimuli. Brain Research, 1105, 93-101. Holroyd, C. B., Larsen, J. T., & Cohen, J. D. (2004). Context dependence of the event-related potential associated with reward and punishment. Psychophysiology, 41 245-253. Holroyd, C. B., Nieuwenhuis, S., Yeung, N., & Cohen, J. D. (2003). Errors in reward predication are reflected in the event-related potential. Neuroreport, 14 2481-2484. Hommel, B., Proctor, R.W., & Vu, K.P. (2004). A feature-inte rgration account of sequential effects in the Simon task. Psychological Research, 68 1-17. Ille, N., Berg, P., & Scherg, M. (1997). A sp atial components method for continuous artifact correction in EEG and MEG. Biomedical Technology, 42 80-83. Ille, N., Berg, P., & Scherg, M. (2002). Artif act correction of the ongoing EEG using spatial filters based on artifact and brain signal topographies. Journal of Clinical Neurophysiology, 19 113-124. Kaelin, D. L., Cifu, D. X., & Matthies, B. (1996) Methylphenidate effect on attention deficit in the acutely brain-injured adult. Archives of Physical Medicine and Rehabilitation, 77 6-9. Kerns, J.G. (2006). Anterior cingul ate and prefrontal activity in an fMRI study of trial-to-trial adjustments on the Simon task. Neuroimage, 15, 399-405.

PAGE 112

112 Kerns, J. G., Cohen, J. D., MacDonald, A. W., Cho, R. Y., Stenger, V. A., & Carter, C. S. (2004). Anterior cingulate conflict mon itoring and adjustments in control. Science, 303 1023-1026. King, N. S., Crawford, S., Wenden, F. J., Moss, N. E., & Wade, D. T. (1997). Interventions and service need following mild and moderate head injury: The Oxford Head Injury Service. Clinical Rehabilitation, 11 13-27. Larson, M. J., Jones, V., Kelly, K. G., & Perlstein, W. M. (2004, February). Dissociating components of cognitive control with highdensity ERPs: Implemen tation of control, conflict processing, and error monitoring. Paper presented at the 32nd Annual Meeting of the International Neuropsychological Society, Baltimore, MD. Larson, M. J., Perlstein, W. M., Demery, J. A., & Stigge-Kaufman, D. (2006a). Cognitive control impairments in traumatic brain injury. Journal of Clinical and Experimental Neuropsychology 28, 968-986. Larson, M. J., Perlstein, W. M., Stigge-Kaufma n, D. A., Kelly, K. G., & Dotson, V. M. (2006b). Affective context-induced modulatio n of the error-related negativity. Neuroreport, 17 329-333. Leclercq, M., Couillet, J., Azouvi, P., Marlier, N., Martin, Y., Strypstein, E., & Rousseaux, M. (2000). Dual task performance after severe di ffuse traumatic brain injury or vascular prefrontal damage. Journal of Experimental and Clinical Neuropsychology, 22 339-350. Leon-Carrion, J., Alarcon, J.C., Revuelta, M., Murillo-Cabezas, F., Dominguez-Roldan, J.M., Dominguez-Morales, M.R., Machuca-Murga, F., & Forastero, P. (1998). Executive functioning as outcome in patient s after traumatic brain injury. International Journal of Neuroscience, 94 75-83. Levander, M. B., & Sonesson, B. G. (1998). Are there any mild interhemispheric effects after moderately severe closed head injury. Brain Injury, 12 165-173. Levin, H. S., Amparo, E., Eisenberg, H. M., Willi ams, D. H., High, W. M. Jr., McArdle, C. B., & Weiner, R.L. (1987). Magnetic resonance imaging and computerized tomography in relation to the neurobehavior al sequelae of mild and moderate head injuries. Journal of Neurosurgery, 66 706-713. Levin, H. S., Gary, H., Eisenberg, H. M., Ruff, R. M., Barth, J. T., Kr eutzer, J., High, W.M., Portman, S., Foulkes, M.A., Jane, J.A., Mamarou, A., & Marshall, L.F. (1990). Neurobehavioral outcome one year after severe head injury: Experience of the Traumatic Coma Data Bank. Journal of Neurosurgery, 73 699-709.

PAGE 113

113 Levine, B., Katz, D. I., Dade, L., & Black, S. E. (2002). Novel approaches to the assessment of frontal damage and executive deficits in trau matic brain injury. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (pp. 448-465). New York: Oxford University Press. Levine, B., Robertson, I. H., Clare, L., Carter G., Hong, J., Wilson, B. A., Duncan, J., & Stuss D.T. (2000). Rehabilitation of executive func tioning: An experimental-clinical validation of goal management training. Journal of the International Neuropsychological Society, 6 299-312. Lezak, M. D., Howieson, D., & Loring, D. (2004). Neuropsychological assessment (4th Edition ed.). New York: Oxford Press. Liotti, M., Woldorff, M. G., Perez, R., & Maybe rg, H. S. (2000). An ERP study of the temporal course of the Stroop colo r-word interference effect. Neuropsychologia, 38 701-711. MacDonald, A. W., Cohen, J. D., Stenger, V. A., & Carter, C. S. (2000). Dissociating the role of the dorsolateral prefrontal co rtex in cognitive control. Science, 288 1835-1838. Marin, R. S. (1991). Apathy: A neuropsychiatric syndrome. Journal of Neuropsychiatry and Clinical Neuroscience, 3 243-254. Marin, R. S., Biedrzycki, R. C., & Firinciogulla ri, S. (1991). Reliability and validity of the Apathy Evaluation Scale. Psychiatry Research, 38 143-162. Mathalon, D. H., Fedor, M., Faustman, W. O., Gr ay, M., Askari, N., & Ford, J. M. (2002). Response-monitoring dysfunction in schizophr enia: An event-related brain potential study. Journal of Abnormal Psychology, 111 22-41. Mayr, U., Awh, E., Laurey, P. (2003). Conflict ad aptation effects in th e absence of executive control. Nature Neuroscience, 6 450-452. McAllister, T. W., Flashman, L. A., Sparling, M. B., & Saykin, A. J. (2004). Working memory deficits in traumatic brain injury: Catec holaminergic mechanisms and prospects for treatment--A review. Brain Injury, 18 331-350. McAllister, T.W., Saykin, A.J., Flashman, L.A ., Sparling, M.B., Johnson, S.C., Guerin, S. J., Mamourian, A.C., Weaver, J.B., & Yanofsky, N. (1999). Brain activation during working memory one month after mild traumatic brain injury: A functional MRI study. Neurology, 12 1300-1308. McAllister, T. W., Sparling, M. B., Flashman, L. A., Guerin, S. J., Mamourian, A. C., & Saykin, A. J. (2001). Differential working memory load effects after mild tr aumatic brain injury. NeuroImage, 14 1004-1012.

PAGE 114

114 McDowell, S., Whyte, J., & D'Esposito, M. (1997 ). Working memory impairments in traumatic brain injury: Evidence from a dual-task paradigm. Neuropsychologia, 35 1341-1353. McMillan, T. M., Jongen, E. L., & Greenwood, R. J. (1996). Assessment of post-traumatic amnesia after severe closed head in jury: Retrospective or prospective? Journal of Neurology, Neurosurgery, and Psychiatry, 60 422-427. Meythaler, J. M., Peduzzi, J. D., Eleftheriou, E., & Novack, T. A. (2001). Current concepts: Diffuse axonal injury-associated traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 82 1461-1471. Miller, E. K. (2000). The prefront al cortex and cognitive control. Nature Reviews: Neuroscience, 1 59-66. Miller, E. K., & Cohen, J. D. (2001). An in tegrative theory of prefrontal cortex. Annual Review of Neuroscience, 24 167-202. Miller, L. A. (1992). Impulsivi ty, risk-taking, and the abilit y to synthesize fragmented information after frontal lobectomy. Neuropsychologia, 30 69-79. Miltner, W. H. R., Lemke, U., Weiss, T., Holroyd, C. B., Scheffers, M. K., & Coles, M. G. H. (2003). Implementation of erro r-processing in the human anterior cingulate cortex: A source analysis of the magnetic equiva lent of the error-related negativity. Biological Psychology, 64 157-166. Mcks, J., Kohler, W., Gasser, T., & Pham, D.T. (1988). Novel approaches to the problem of latency jitter. Psychophysiology 25 217-226. Napolitano, E., Elovic, E. P., & Qureshi, A. I. (2005). Pharmacological stimulant treatment of neurocognitive and functional deficits after traumatic and non-traumatic brain injury. Medical Science Monitor, 11 RA212-220. National Institute of Health. (1998). NIH Consensus Statement on Rehabilitation of Persons with TBI Bethesda, MD. Neter, J., Wasserman, W., & Kutner, M. H. (1985). Applied linear statistical models: Regression, analysis of variance, and experimental designs (2nd ed.). Homewood, Ill.: R.D. Irwin. Newsome, M.R., Scheibel, R.S., Steinberg, J.L. Troyanskaya, M., Sharma, R.G., Rauch, R.A., Li, X., & Levin, H.S. (2007). Working memo ry brain activation following severe traumatic brain injury. Cortex, 43, 95-111. Nieuwenhuis, S., Ridderinkhof, K. R., Blom, J., Band, G. P., & Kok, A. (2001). Error-related brain potentials are differentially related to awareness of response errors: Evidence from an antisaccade task. Psychophysiology, 38 752-760.

PAGE 115

115 Nieuwenhuis, S., Stins, J.F., Posthuma, D., Pold erman, T.J., Boomsma, D.I., & de Geus, E.J. (2006). Accounting for sequential trial effects n the flanker task: Conflict adaptation or associative priming. Memory & Cognition, 34, 1260-1272. Niki, H., & Watanabe, M. (1979). Prefrontal a nd cingulate unit activity during timing behaviour in the macaque. Brain Research, 171 213-224. Noe, E., Ferri, J., Caballero, M. C., Villodre, R., Sanchez, A., & Chirivella, J. (2005). Selfawareness after acquired brain inju ry: Predictors and rehabilitation. Journal of Neurology, 252 168-175. Notebaert, W., Gevers, W., Verbruggen, F., & Liefooghe, B. (2006). Top-down and bottom-up sequential modulations of congruency effects. Psychonomic Bulletin & Review, 13, 112117. Oddy, M., Coughlan, T., Tyerman, A., & Jenkins, D. (1985). Social ad justment after closed head injury: A further follow-up seven years after injury. Journal of Neurology, Neurosurgery, and Psychiatry, 48 564-568. O'Keeffe, F. M., Dockree, P. M., & Robertson, I. H. (2004). Poor insight in traumatic brain injury mediated by impaired error proce ssing? Evidence from el ectrodermal activity. Cognitive Brain Research, 22 101-112. Overbeek, T.J.M., Nieuwenhuis, S., Ridderinkhof, K.R. (2005). Dissociable components of error processing: On the functional signfican ce of the Pe vis--vis the ERN/Ne. Journal of Psychophysiology, 19, 319-329. Ownsworth, T. L., Fleming, J., Desbois, J., Stro ng, J., & Kuipers, P. (2006). A metacognitive contextual intervention to enhance error awareness and functional outcome following traumatic brain injury: A si ngle-case experimental design. Journal of the International Neuropsychological Society, 12 54-63. Ownsworth, T. L., McFarland, K., & Young, R. M. (2000). Development and standardization of the Self-regulation Skills Interview (SRSI): A new clinical assessment tool for acquired brain injury. Clinical Neuropsychology, 14 76-92. Ownsworth, T. L., McFarland, K., & Young, R. M. (2002). The inves tigation of factors underlying deficits in self-a wareness and self-regulation. Brain Injury, 16 291-309. Ownsworth, T. L., & Oei, T. P. S. (1998) Depression after trau matic brain injury: Conceptualization and treatment considerations. Brain Injury, 12 735-751. Park, N. W., Conrod, B., Hussain, Z., Murphy, K. J., Rewilak, D., & Black, S. E. (2003). A treatment program for individuals with defi cient evaluative processing and consequent impaired social and risk judgement. Neurocase, 9 51-62.

PAGE 116

116 Perlstein, W. M., Cole, M. A., Demery, J., Seig nourel, P. J., Dixit, N. K., Larson, M. J., & Briggs, R.W. (2004). Parametric manipulati on of working memory load in traumatic brain injury: Behavioral and neural correlates. Journal of the International Neuropsychological Society, 10 724-741. Perlstein, W. M., Larson, M. J., Dotson, V. M., & Kelly, K. G. (2006). Te mporal dissociation of components of cognitive control dysfunction in severe TBI: ERPs and the cued-Stroop task. Neuropsychologia, 44 260-274. Picton, T.W., Lins, O., & Scherg, M. (1995). Th e recording and analys is of event-related potentials. In F. Boller & J. Grafman (Ser ies Eds.), & R. Johnson, Jr. (Section Ed.), Handbook of neuropsychology: Vol. 10, secti on 14. Event-related brain potentials and cognition (pp. 3-73). Amsterdam: Elsevier. Plenger, P. M., Dixon, C. E., Castillo, R. M., Fr ankowski, R. F., Yablon, S. A., & Levin, H. S. (1996). Subacute methylphenidate treatment for moderate to moderately severe traumatic brain injury: A preliminary doubl e-blind placebo-controlled study. Archives of Physical Medicine and Rehabilitation, 77 536-540. Ponsford, J., & Kinsella, G. (1992). Attenti onal deficits followi ng closed-head injury. Journal of Clinical and Experimental Neuropsychology, 14 822-838. Potter, D. D., Jory, S. H., Basset, M. R., Barre t, K., & Mychalkiw, W. (2002). Effect of mild head injury on event-related potential co rrelates of Stroop task performance. Journal of the International Neuropsychological Society, 8 828-837. Prigatano, G. P., Bruna, O., Mataro, M., Munoz J. M., Fernandez, S., & Junque, C. (1998). Initial disturbances of consciousness and resu ltant impaired awareness in Spanish patients with traumatic brain injury. Journal of Head Trauma Rehabilitation, 13 29-38. Rabbitt, P.M.A. (1966). Errors and error correction in choice reaction tasks. Journal of Experimental Psychology, 71, 264-272. Rabbitt, P.M.A. (1968). Three kinds of error-si gnaling responses in a serial choice task. Quarterly Journal of Ex perimental Psychology, 20, 179-188. Ratcliff, R. (1993). Methods for dealing with reaction time outliers. Psychological Bulletin, 114 510-532. Rebai, M., Bernard, C., & Lannou, J. (1997). The Stroop test evokes a ne gative brain potential, the N400. International Journal of Neuroscience, 91 85-94. Reitan, R.M. (1958). Validity of th e Trail Making Test as an indi cator of organic brain damage. Perceptual and Motor Skills, 8 271-276.

PAGE 117

117 Ridderinkhof, K.R. (2002). Activation and suppressi on in conflict tasks: Em pirical clarification through distributional analyses. In W. Prinz & B. Hommel (Eds.), Attention and Performance XIX (pp. 494-519). Oxford University Press: Oxeford. Rios, M., Perianez, J. A., & Munoz-Cespedes, J. M. (2004). Attentional control and slowness of information processing after severe traumatic brain injury. Brain Injury, 18 257-272. Rolls, E. T. (2000). The orbito frontal cortex and reward. Cerebral Cortex, 10 (3), 284-294. Ruchsow, M., Grothe, J., Spitzer, M., & Kiefer, M. (2002). Human anterior cingulate cortex is activated by negative feedback: Evidence from event-related potentials in a guessing task. Neuroscience Letters, 14 203-206. Ruchsow, M., Herrnberger, B., Wiesend, C., Gr on, G., Spitzer, M., & Kiefer, M. (2004). The effect of erroneous responses on response mon itoring in patients with major depressive disorder: A study with event-related potentials. Psychophysiology, 41 833-840. Ruchsow, M., Spitzer, M., Gron, G., Grothe, J ., & Kiefer, M. (2005). Error processing and impulsiveness in normals: Evidence from event-related potentials. Cognitive Brain Research, 24 317-325. Ruchsow, M., Hernberger, B., Beschoner, P., Gr on, G., Spitzer, M. & Kiefer, M. (2006). Error processing in major depressive disorder: Evidence from event-related potentials. Journal of Psychiatry Research, 40, 37-46. Rushworth, M. F. S., Hadland, K. A., Gaffan, D. & Passingham, R. E. (2003). The effect of cingulate cortex lesions on task switching and working memory. Journal of Cognitive Neuroscience, 15 338-353. Rushworth, M. F. S., Walton, M. E., Kennerley, S. W., & Bannerman, D. M. (2004). Action sets and decisions in the medial frontal cortex. Trends in Cognitive Sciences, 9 410-417. Salmond, C. H., Menon, D. K., Chatfield, D. A., Pickard, J. D., & Sahakian, B. J. (2005). Deficits in decision-making in head injury survivors. Journal of Neurotrauma, 22 (6), 613-622. Scheibel, R.S., Newsome, M.R., Steinberg, J.L., Pearson, D.A., Rauch, R.A., Mao, H., Troyanskaya, M., Sharma, R.G., & Levin, H. S. (2007). Altered brain activation during cognitive control in patients with mode rate to severe traumatic brain injury. Neurorehabilitation and Neural Repair, 21 36-45. Scheibel, R.S., Pearson, D.A., Faria, L.P., Kotr la, K.J., Aylward, E., Bachevalier, J., & Levin H.S. (2003). An fMRI study of executive f unctioning after severe diffuse TBI. Brain Injury, 17, 919-930.

PAGE 118

118 Scherg, M. (1990). Fundamentals of dipole source potential analysis. In F. Grandori & M. Hoke (Eds.), Auditory evoked magnetic fields and elect ric potentials. Advances in audiology (Vol. 6, pp. 65-78). Basel: Karger. Schlund, M. W. (2002a). Effects of acquired brai n injury on adaptive choice and the role of reduced sensitivity to contingencies. Brain Injury, 16 527-535. Schlund, M. W. (2002b). The effects of brain in jury on choice and sensitivity to remote consequences: Deficits in discrimi nating response-consequence relations. Brain Injury, 16 347-357. Schlund, M. W., & Pace, G. M. (2000). The effect s of traumatic brain injury on reporting and responding to causal relations: An investig ation of sensitivity to reinforcement contingencies. Brain Injury, 14 573-583. Schlund, M. W., Pace, G. M., & McGready, J. (2001). Relations between decision-making deficits and discriminating con tingencies following brain injury. Brain Injury, 15 347357. Seignourel, P.J., Robins, D.L., Larson, M.J., Deme ry, J.A., Cole, M., & Perlstein, W.M. (2005). Cognitive control in closed head injury: C ontext maintenance dysfunction or prepotent response inhibition deficit? Neuropsychology, 19 578-590. Shallice, T., & Burgess, P. W. (1991). Deficits in strategy app lication following frontal lobe damage in man. Brain, 114 727-741. Sherer, M., Bergloff, P., Boake, C., High, W., & Levin, E. (1998). The Awareness Questionnaire: Factor structur e and internal consistency. Brain Injury, 12 63-68. Sherer, M., Hart, T., Whyte, J., Nick, T. G., & Yablon, S. A. (2005). Neuroanatomic basis of impaired self-awareness after traumatic br ain injury: Findings from early computed tomography. Journal of Head Trauma Rehabilitation, 20 287-300. Simmond, M., & Fleming, J. (2003). Reliability of the self-awareness of deficits interview for adults with traumatic brain injury. Brain Injury, 17 325-337. Soeda, A., Nakashima, T., Okumura, A., Kuwata K., Shinoda, J., & Iwama, T. (2005). Cognitive impairment after traumatic brain injury: A functional magnetic resonance imaging study using the Stroop task. Neuroradiology, 47 501-507. Speilberger, C. D., Gorusch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory Palo Alto, CA: Consulting Psychologists Press. Spreen, O., & Strauss, E. (1991). A compendium of neuropsychol ogical tests: Administration, norms, and commentary New York: Oxford University Press.

PAGE 119

119 Starkstein, S.E., Mayberg, H.S., Preziosi, T.J ., Andrezejewski, P., Leiguarda, R., & Robinson, R.G. (1992). Reliability, validity, and clinical correlates of ap athy in Parkinson's disease. Journal of Neuropsychiatry and Clinical Neuroscience, 4, 134-139. Stemmer, B., Segalowitz, S. J., Witzke, W., & Sc honle, P. W. (2004). Error detection in patients with lesions to the medial pr efrontal cortex: An ERP study. Neuropsychologia, 42 118130. Stroop, J. R. (1935). Studies of interf erence in serial verbal reactions. Journal of Experimental Psychology, 18 643-662. Stuss, D. T. (1991). Self, awareness, and the fron tal lobes: A neuropsychol ogical persp ective. In J. Strauss & G. R. Goethals (Eds.), The self: Interdisciplinary approaches (pp. 255-278). New York: Springer-Verlag. Stuss, D. T., & Gow, C. A. (1992). "Frontal dysfunction" after traumatic brain injury. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 5 272-282. Swick, D., & Turken, A. U. (2002). Dissociation between conflict detecti on and error-monitoring in the human anterior cingulate cortex. Proceedings of the National Academy of Sciences, 99 16354-16359. Tateno, A., Jorge, R. E., & Robinson, R. G. (2003) Clinical correlates of aggressive behavior after traumatic brain injury. The Journal of Neuropsychiatry and Clinical Neurosciences, 15 155-160. Teasdale, G., & Jennett, B. (1974). Assessment of coma and impaired consciousness: A practical scale. Lancet, ii 81-84. Toglia, J., & Kirk, U. (2000). Understanding awareness defi cits following brain injury. Neurorehabilitation, 15 57-70. Trudel, T. M., Tyron, W., & Purdum, C. (1998). Awareness of disability and long-term outcome after traumatic brain injury. Rehabilitation Psychology, 43 276-281. Ullsperger, M., Bylsma, L.M., & Botvinick, M.M. (2005). The conflict adapta tion effect: It's not just priming. Cognitive, Affective, and Behavioral Neuroscience, 5, 467-472. van Meel, C. S., Oosterlaan, J., Heslenfeld, D. J., & Sergeant, J. A. (2005). Telling good from bad news: ADHD differentially affects proces sing of positive and negative feedback during guessing. Neuropsychologia, 43 1946-1954. van Veen, V., & Carter, C. S. (2002a). The anteri or cingulate as a conf lict monitor: fMRI and ERP studies. Physiology and Behavior, 77 477-482.

PAGE 120

120 van Veen, V., & Carter, C. S. (2002b). The timing of action-monitoring pro cesses in the anterior cingulate cortex. Journal of Cognitive Neuroscience, 14 593-602. Verbruggen, F., Notebaert, W., Liefooghe, B ., & Vandierendonck, A. (2006). Stimulusand response-conflict-induced cognitive control on the flanker task. Psychonomic Bulletin & Review, 13, 328-333. Vidal, F., Hasbroucq, T., Grapperon, J., & Bonnet, M. (2000). Is the 'error negativity' specific to errors. Biological Psychology, 51 109-128. Wagner, A. K., Sokoloski, J. E., Ren, D., Chen, X ., Khan, A. S., Zafonte, R. D., Michael, A.C., & Dixon, C.E. (2005). Controlled cortical impact injury affects dopaminergic transmission in the rat striatum. Journal of Neurochemistry, 95 457-465. Walton, M. E., Bannerman, D. M., Alterescu, K ., & Rushworth, M. F. S. (2003). Functional specialization within medial fr ontal cortex of the anterior cingulate for evaluating effortrelated decisions. Journal of Neuroscience, 23 6475-6479. Wechsler, D. (1987). Wechsler Memory Scale--Revised. San Antonio, TX: The Psychological Corporation. Wechsler, D. (1997). Wechsler Adult Intelligence Scale--Third Edition San Antonio, TX: The Psychological Corporation. Weddell, R., Oddy, M., & Jenkins, D. (1980). Social adjustment after rehabilitation: A two year follow-up of patients with severe head injury. Psychological Medicine, 10 257-263. West, R. (2003). Neural correlate s of cognitive control and conf lict detection in the Stroop and digit-location tasks. Neuropsychologia, 41, 1122-1135. West, R. (2004). The effects of aging on contro lled attention and conf lict processing in the Stroop task. Journal of Cognitive Neuroscience, 16, 103-113. West, R., & Alain, C. (1999). Event-related neur al activity associated with the Stroop task. Cognitive Brain Research, 8 102-111. West, R., & Alain, C. (2000). Effect of task c ontext and fluctuations of attention on neural activity supporting performa nce of the Stroop task. Brain Research, 873 102-111. West, R., Jakubek, K., Wymbs, N., Perry, M., & Moor e, K. (2005). neural correlates of conflict processing. Experimental Brain Research, 167, 38-48. West, R., & Moore, K. (2005). Adjustments of cognitive control in yo unger and older adults. Cortex, 41, 570-581.

PAGE 121

121 Woody, C.D. (1967). Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals. Medical and Biological Engineering 5 539-553. Woods, S.P., Scott, J.C., Conover, E., Marcotte, T.D., Heaton, R.K., Grant, I. (2005). Test-retest reliability of component process variables within the Hopkins Verbal Learning TestRevised. Assessment, 12, 96-100. Yasuda, A., Sato, A., Miyawaki, K., Kumano, H. & Kuboki, T. (2004). E rror-related negativity refelcts detection of negativ e reward prediction error. Neuroreport, 15 2561-2565. Yeung, N., & Cohen, J. D. (2006). The imp act of cognitive deficits on conflict monitoring. Predictable di ssociations between the error-related negativity and N2. Psychological Science, 17 164-171 Yeung, N., Cohen, J. D., & Botvinick, M. (2004). The neural basis of error detection: Conflict monitoring and the error-related negativity. Psychological Review, 111 931-954.

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122 BIOGRAPHICAL SKETCH Michael James Larson obtained a bachelor of science degree in psychology from Brigham Young University in Provo, Utah in 2002. He subs equently began his doctoral training in the Department of Clinical and Hea lth Psychology at the University of Florida, where he earned his master of science degree in 2004. Michael earned his Ph.D. in ps ychology, with a specialization in clinical neuropsychology, in August 2008 followi ng a one-year clinical internship at Emory University in Atlanta, Georgia.