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A TALE OF TWO TROOPS IN TRAUMATIC BRAIN INJURY
A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
UNIVERSITY OF FLORIDA
Paul J. Seignourel
I thank my advisor, William M. Perlstein; and my collaborators on this project,
Michael A. Cole, Jason A. Demery, and Diana L. Robins.
TABLE OF CONTENTS
A C K N O W L E D G M E N T S .................................................................... ......... .............. iii
LIST OF TABLES ......... ........................ ..............................vi
L IST O F FIG U R E S .... ...... ................................................ .. .. ..... .............. vii
A B S T R A C T .......................................... .................................................. v iii
1 IN TR OD U CTION ............................................... .. ......................... ..
Performance of Brain-Injured Patients on the Stroop Task .........................................6
P reduction s ............................................................................ 10
2 M E T H O D S .......................................................................................................14
P a rtic ip a n ts ........................................................................................................... 1 4
M a te ria ls ........................................................................................................1 5
C a rd S tro o p .....................................................................................1 5
Single-Trial Stroop ............................................... .......... 16
Neurobehavioral Rating Scale (NRS) ........................................ .....17
WAIS-III subtests .................................................... .... ........19
North American Adult Reading Test (NAART) ..................................... 19
P ro c e d u re s ........................................................................................1 9
S statistical A n aly se s ............................................................................................... 19
3 R E S U L T S .............................................................................2 2
N europ sy chological T ests..................................................................................... 22
C ard Stroop ...................................... .... ....................................22
Single-Trial Stroop: Speed-Accuracy Tradeoff Analyses .......................................23
Single-T rial Stroop : R T s....................................................................................... 24
Single-Trial Stroop: Error R ates .......................................................... .. .....25
Neurobehavioral Rating Scales............................ ...............27
4 D ISC U S SIO N ............................................................................... 32
L IST O F R E F E R E N C E S ........................................................................ ..................... 44
BIOGRAPH ICAL SKETCH .............................................................. ...................51
LIST OF TABLES
1-1 Studies of performance of TBI patients on the Stroop task................... ..............
2-1 Demographics and injury variables by group.......................................................16
3-1 Performance on neuropsychological tests by group .............................................22
3-2 Means and standard deviations of median RT (ms) in the single-trial Stroop ........24
3-3 Means and standard deviations of error rates (%) in the single-trial Stroop ..........26
3-4 ANOVA for error rates in the single-trial Stroop..................................................26
3-5 Internal consistency (alpha-cronbach) estimates for the NRS for self and
significant other's ratings by group ......................... ......... ...............28
3-6 Means and standard deviations of NRS surrogate factor scores and total score
b y g ro u p .......................................................................... 2 8
3-7 Correlations between self and significant-others' ratings on the NRS....................29
3-8 Correlations between ratings on the NRS and Stroop performance (TBI group)....30
3-9 Multiple regressions with self and significant-others' ratings as independent
variables and error rates (color naming) as the dependent variables (TBI group) ..30
3-10 Correlations between self-ratings on the NRS and color-naming error rates at the
long and short delays separately (TBI group).................................. ... ..................31
3-11 Multiple regressions with color-naming error rates at the long and short delays as
independent variables and NRS self-ratings as dependent variables (TBI group) ..31
LIST OF FIGURES
2-1 Schema of the single-trial Stroop. Participants are first presented with an
instructional cue ("Color" or "Word"), followed by a delay (1 or 5 seconds) and
an imperative stimulus (congruent, neutral or incongruent). ...................................17
3-1 Number of items completed on the card Stroop by group and condition. Error bars
represent standard errors. ............................................... ............................... 23
3-2 Error rates in the incongruent color-naming condition of the single-trial Stroop by
group and delay. Error bars represent standard errors. ...........................................27
Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science
A TALE OF TWO TROOPS IN TRAUMATIC BRAIN INJURY
Paul J. Seignourel
Chair: William M. Perlstein
Major Department: Clinical and Health Psychology
The Stroop Color-Word task has frequently been used to examine attentional
deficits in Traumatic Brain Injury (TBI). However, critical review of the literature
suggests that TBI patients do not consistently show disproportionate reaction time (RT)
interference on the Stroop task, inconsistent with a frequent assertion of increased
interference. We hypothesized that combining inhibition and working memory (WM)
requirements in a new, computerized version of the Stroop would increase sensitivity to
TBI. We examined the performance of healthy subjects and TBI patients on card and
single-trial versions of the Stroop paradigm. The TBI patients did not show
disproportionately increased RT interference compared to controls on either version, but
instead greater error-rate interference on the single-trial version, especially at the long
delay. Error rates, but not reaction times, were related to reports of symptomatology in
TBI patients. Results suggest that errors (rather than RTs) are more sensitive to cognitive
deficits in TBI; and that such deficits, and everyday life difficulties experienced by TBI
survivors, may be related to a difficulty in the preparation to override prepotent response
Traumatic brain injury (TBI), with an incidence of 500,000 to 1.9 million cases
each year (Lezak, 1995), is a significant problem in the United States. It is also a unique
problem, in that it affects large numbers of young individuals: the highest incidence of
brain injury occurs in the 15 to 24 year range, with high incidence rates also in the 0 to 5
year range and for the elderly. Among individuals who sustain TBI, some experience
only transient symptoms, such as brief loss of consciousness (LOC) and post-traumatic
amnesia (PTA). Others, however, continue to experience significant problems long after
injury. These symptoms include frequent headaches, irritability and restlessness, sleep
disturbances, and various cognitive difficulties (such as poor concentration and attention,
reduced processing speed, and impaired memory) (Levin, Eisenberg, & Benton, 1991;
Levine, 1988; van Zomeren & van den Burg, 1985): a constellation of symptoms
sometimes referred to as postconcussional syndrome (Lishman, 1988). In a study of 103
patients with moderate-to-severe brain injuries, Olver, Ponsford and Curran (1996) found
that at a 2-year follow-up, 61% of the patients reported word-finding problems, 60% had
difficulties concentrating and 56% reported feeling more depressed than before the
injury. Moreover, only 40% were able to drive and only 41% were employed full-time.
Percentages were similar at 5-year follow-up, with the exception of ability to drive,
which increased to 48%; and full-time employment, which decreased to 34%. Such
findings suggest that TBI, at least in the moderate-to-severe range, results in disabling
and long-lasting difficulties for a great number of individuals.
Closed head injuries, in which the skull is intact and the brain is not exposed,
account for about 90% of all brain injuries (Lezak, 1995). Anatomically, brain damage
after closed head injury is generally diffuse, resulting from several distinct damaging
mechanical forces to many different areas of the brain. Some evidence exists, however,
that because of the shape of bone's protuberances in the brain, bruising due to coup (the
blow at the point of impact) and contrecoup (bruising in the area opposite to the blow) is
often more pronounced in the frontal and temporal lobes (Levin & Kraus, 1994). Axonal
shearing or diffuse axonal injury (DAI), which is an excessive stretching of nerve fibers
and blood vessels due to violent acceleration and deceleration (Adams, Graham, Murray,
& Scott, 1982), might be more concentrated in these areas as well (Groswasser,
Reider-Groswasser, Soroker, & Machtey, 1987). Consistent with evidence of frontal
damage, studies of individuals with TBI often show difficulties on complex tasks, despite
normal or quasi-normal functioning in basic cognitive domains such as arousal, language
and perception. For example McDowell, Whyte and D'Esposito (1997) compared
brain-injured patients with control participants on a simple visual reaction time (RT) task
and on a dual task, consistent with patient reports of difficulties negotiating multiple
simultaneous real-world tasks (van Zomeren & van den Burg, 1985). They found that, in
addition to generalized slowing, TBI patients showed greater decrements in performance
compared to control participants during dual-task conditions. Similarly, Levine, Dawson,
Boutet, Schwartz and Stuss (2000) found that TBI patients were impaired on the Revised
Strategy Application Test (R-SAT), a complex and unstructured task in which
participants, in order to perform satisfactorily, must select items on the basis of their
length while refraining from the tendency to complete all items sequentially.
Despite major differences, the two previously mentioned tasks share at least one
essential characteristic: in both cases, participants tend to perform poorly if they complete
all items automatically (that is, by simply responding to each item presented to them and
without any overall strategy toward optimal performance-bottom-up processing).
Conversely, good performance depends on participants' strategy being guided by the
overall goal and structure of the task (top-down processing). In other words, both tasks
require that participants actively maintain goal representations to guide their behavior and
the order in which they perform the task. Using a more general framework, Braver and
Barch (2002-page 1) defined context representations as "any task-relevant information
that is generally represented in such a form that it can bias processing in the pathways
responsible for task performance." Through extensive behavioral studies and
connectionist computational models, Cohen, Barch, Carter and Servan-Schreiber (1999)
showed that schizophrenic patients' cognitive difficulties on a range of seemingly
dissimilar tasks could be explained by a single deficit in context maintenance. According
to their model, context representations are maintained on-line by the prefrontal cortex
(PFC), through a mechanism where dopamine (DA) plays a prominent role; the putative
disruptions in the dopaminergic circuitry in schizophrenic patients are thought to be
primarily responsible for their context maintenance deficits. More recently, Braver et al.
(2001) showed that performance decrements and, counterintuitively, performance
improvements in older adults could also be explained by a deficit in context maintenance.
Importantly, the term context maintenance, in this framework, refers to a concept more
general than goal representations: goals represent only one type of representation, among
others, that can bias processing of subsequent information. In the AX-Continuous
Performance Task (AX-CPT), for instance, the cue provides the context essential for
proper processing of the probe, without representing per se the goal of the task (Cohen et
al., 1999). Context maintenance, on the other hand, is a much more specific concept than
executive functioning, which has been used to describe a number of abilities including
planning, problem-solving, shifting mental set, and inhibition of prepotent responses. In
fact, Cohen, Braver and O'Reilly (1996) noted that the term dysexecutive syndrome
(often used to describe the set of symptoms exhibited by patients with frontal lobe
lesions) is essentially descriptive, and does not specify which mechanisms are responsible
for executive control.1 They added that their framework, by specifying the mechanisms
responsible for cognitive control at a computational and neurobiological level, leads to
specific predictions regarding the performance of individuals with context maintenance
For the purpose of our study, two of these predictions are especially relevant. First,
representations of context are especially important when the response required by the task
at hand is competing with a more frequent and automatic response. This characteristic of
context maintenance is similar to what has been called inhibition of the prepotent
response. It is required in the Stroop task, used in this study, but also in the antisaccade
task (Crevits, Hanse, Tummers, & Van Maele, 2000) and in the R-SAT (Levine et al.,
2000), previously mentioned. Second, deficits in context maintenance should be more
1 Context maintenance may not account for all mechanisms involved in executive control.
In the framework described by Cohen and Servan-Schreiber (1992), the maintenance of
context representations is carried out by the prefrontal cortex (PFC) and mediated by DA.
Carter et al. (2000), however, showed that the role of the anterior cingulate (AC) in
cognitive control is evaluative rather than strategic. In other words, the AC might be
another area of the brain responsible for cognitive control, complementary to the
maintenance of context carried out by the PFC.
pronounced when the task requires participants to hold context representations in mind
for a prolonged period of time. This second characteristic of context maintenance shows
its similarity with working memory; in fact, Braver et al. (2001) recently described the
maintenance of context representations as a subset of representations within working
memory. In support of this hypothesis, Cohen et al. (1996) compared the performance of
schizophrenics and control participants on the AX-CPT; they found that the sensitivity of
schizophrenics to the cue decreased after a long delay compared to a short delay between
the cue and the probe; whereas the performance of control participants was not affected
by delay. Moreover, the same pattern of results was observed when comparing two neural
network simulations designed to model normal performance and performance associated
with a reduced gain in the context layer. Cohen et al. (1999), on the other hand, failed to
find significant delay effects for both schizophrenics and healthy participants on a
single-trial version of the Stroop paradigm we used.
The primary goal of our study was to examine the hypothesis that patients with
moderate-to-severe TBI exhibit difficulties maintaining context representations, as
evidenced by poor performance when they must maintain representations over a delay in
order to inhibit prepotent response tendencies. This hypothesis stems from the relation
among context maintenance, PFC, and dopaminergic neuromodulation, on the one hand;
and from the aforementioned finding that closed head injuries often result in damage to
the frontal lobes, on the other hand. It is also consistent with the various symptoms
experienced by such patients (some of which, including lack of behavioral control,
disorganization, attention difficulties, and memory deficits, suggest dysfunction of the
frontal lobes) (Kraus & Maki, 1997; Levin & Kraus, 1994; Rieger & Gauggel, 2002).
More specifically, our study used a single-trial version of the Stroop task, which places
greater demands on working memory than the card Stroop often used in clinical settings.
Before we describe the tasks in detail and state our specific predictions, we review the
evidence that TBI critically affects performance on the Stroop task.
Performance of Brain-Injured Patients on the Stroop Task
The Stroop task has been considered by several researchers to be a prototypical
instrument for measuring prepotent response inhibition2 (Miyake, Emerson, & Friedman,
2000; Miyake, Friedman et al., 2000), a function often attributed, in part, to the frontal
lobes (Jahanshahi et al., 1998; Kiefer, Marzinzik, Weisbrod, Scherg, & Spitzer, 1998).
Although there are many different versions of the original task (MacLeod, 1991), the
basic paradigm consists of naming the color of the ink of an incongruent color word. For
example, one would be presented with the word BLUE printed in red ink. In order to
provide the correct answer, red, the participant must overcome the natural, more
automatic or prepotent tendency to simply read the word and respond blue. A version of
the Stroop task most widely used in clinical settings (Golden, 1978) comprises three
* Word reading, in which participants must read aloud columns of color words.
* Color naming, in which participants are required to name the color of the ink of
rows of Xs.
2 Although some researchers refer to the Stroop task as a measure of selective or focused
attention (see e.g., Batchelor, Harvey, & Bryant, 1995; Kingma, La Heij, Fasotti, &
Eling, 1996; Salo, Avishai, & Lynn, 2001), we find the term "inhibition of a prepotent
response" more specific. Selective attention is the ability to focus one's attention on a
specific stimulus or a specific dimension of a stimulus among an array of distractors. Not
included in this definition is a key component of the Stroop, which is the fact that in this
task the distractor (i.e., the color word) tends to elicit an automatic (and in this case
incorrect) response; whereas the correct response (naming the color of the ink) is much
less natural and automatic.
* Color-word naming (or interference), in which participants must name the color of
the ink of incongruent color words.
Studies examining TBI patients' performance on the Stroop paradigm have relied
on a variety of task versions and scoring methods (Table 1-1). In some studies,
researchers have used a single measure (generally performance on the color-word-naming
condition) to compare brain-injured patients and control participants. These researchers
have generally found that TBI patients were slower than control participants
(Guskiewicz, Riemann, Perrin, & Nashner, 1997; Rojas & Bennett, 1995; Stuss et al.,
1985; Trennery, Crosson, DeBoe, & Leber, 1989), although not always significantly so
(Guskiewicz et al., 1997; Potter, Jory, Bassett, Barrett, & Mychalkiw, 2002).
Interpretation of these results, however, is uncertain. Although researchers often consider
slower performance in the interference condition of the Stroop task as a sign of deficits in
inhibiting a prepotent response (or selective attention), it may simply result from
generalized slowing, a very common cognitive sequela of TBI (Lezak, 1995).
Researchers using the difference score between the color-word naming and the
color-naming conditions have obtained mixed results. In three studies, TBI patients had a
significantly greater mean interference score than control participants (Bohnen,
Twijnstra, & Jolles, 1992; McDowell et al., 1997). In three other studies, however, there
was no significant difference between the two groups (Batchelor et al., 1995; Bate,
Mathias, & Crawford, 2001; Bohnen, Jolles, & Twijnstra, 1992), and in one study,
Table 1-1. Studies of performance of TBI patients on the Stroop task
Asikainen et al.
Batchelor et al.
Bate et al.
Bohnen et al.
Bohnen et al.
Potter et al.
Stuss et al.
Trennery et al.
Vakil et al.
92 severe TBI,
35 mild TBI,
35 severe TBI, 35
44 mild TBI, 44
10 mild TBI with
PCS, 10 mild
11 athlete mild
TBI, 11 athlete
severe TBI, 24
47 severe TBI, 30
24 mild TBI, 24
25 mild TBI, 25
20 CHI, 20
65 TBI, 106
25 TBI (all
No significant diff.
No significant diff.
No significant diff.
No significant diff.
in TBI patients
No significant diff.
No significant diff.
No significant diff.
No significant diff.
No significant diff.
TBI slower than
TBI slower than
No significant diff.
TBI slower than
CWN-CN Greater interference
aWR = word reading; CN = color naming (naming the color of a row of Xs); CWN = color-word
naming (naming the color of incongruent color words); mod. CWN = modified color-word
naming, in which a few word-reading items are interspersed among incongruent color-word
naming items; WCN = word-color reading (reading color words printed in incongruent colors);
PC cong. and PC incong. = computer version where congruency varies with each trial but task
control participants actually had a greater interference score than brain-injured patients
(Ponsford & Kinsella, 1992).3 Finally, researchers examined error rates in only two
studies. Ponsford and Kinsella (1992) failed to find any difference between control
participants and TBI patients on a card version of the Stroop. Potter et al. (2002) found no
significant difference between the two groups on either a card version or a computer
version of the Stroop.
Three main possible explanations may account for these mixed findings.
* First, it may be that TBI patients do not actually have deficits in inhibiting
prepotent response tendencies, but rather difficulties on many tasks due to
nonspecific, generalized slowing. Although this explanation may account for the
results obtained with the Stroop task in brain-injured patients, the findings by
McDowell, Whyte and D'Esposito (1997) and Levine et al. (2000) suggest that
these patients do have more difficulties with tasks requiring some form of cognitive
control, of which inhibition of prepotent response tendencies is a prominent
* Secondly, even though TBI patients may have difficulties with inhibitory
processes, the Stroop paradigm may not be sensitive to these deficits.
* Finally, the Stroop paradigm may have the potential to detect deficits in TBI
patients, but the versions of the task used in previous studies may not be sensitive
to these deficits. In support of this explanation, all the tasks used in previous
research on TBI were card versions of the Stroop paradigm. As pointed out by
Perlstein, Carter, Barch and Baird (1998), these versions require participants to
correct mistakes during task performance. As a result, errors and speed are
confounded in the RT data, leading to a possible decrease in sensitivity. Possibly
even more crucial is the fact that conditions are blocked in the card version of the
Stroop. In other words, the task requires participants to read words on a first page,
and name colors on a different page. As a result, it may become easier, over time,
to overcome the influence of the words of incongruent stimuli and to focus instead
3 Bohnen and his collaborators (Bohnen, Jolles et al., 1992; Bohnen, Twijnstra et al.,
1992) have also developed a new condition, in which a few word-reading items are
interspersed among incongruent color-word naming items. For this new condition, they
found an increased interference score in brain-injured patients in at least two independent
studies. Interestingly, their modification is not without commonalities with our computer
version, as in both cases participants have to switch rapidly between reading words and
naming colors, thereby increasing dramatically the context maintenance requirements of
on the color of the ink. As noted previously, deficits in context maintenance are
more likely to become apparent in tasks with greater working memory demands. In
a task with mixed conditions, such as the computer version used in our study, color
naming and word reading vary randomly with each new trial, and participants must
constantly update, maintain and manipulate task instructions to perform
appropriately. If the difficulties of brain-injured patients are indeed due to
impairments in maintaining context representations, then such a task, combining
working memory and inhibition of prepotent response tendency requirements, may
be better suited than card versions of the Stroop paradigm to detect deficits in
context maintenance due to TBI.
In our study, we examined the performance of TBI patients on two versions of the
Stroop paradigm: the "classic" three-card version of Golden (1978), often used in the
clinical context, and a single-trial computerized version developed by Cohen et al.
(1999). In the single-trial version, the conditions varied with each trial, and participants
were first given an instructional cue (reading the word or naming the color), and then
shown an imperative stimulus varying in congruency. Previous single-trial computer
versions of the Stroop typically consisted of three color-naming conditions of the present
design (Perlstein et al., 1998; Salo et al., 2001). Our addition of the three word-reading
conditions requires participants to maintain the instruction on-line and use it to bias the
processing of the imperative stimulus. In other words, this modification introduces a
working-memory component to the basic Stroop paradigm, which we believe will
increase its sensitivity to context maintenance deficits induced by TBI. To examine even
more closely the influence of working memory on task performance, we also manipulated
the delay between the instruction and the imperative stimulus, with a short, 1-second
delay and a long, 5-second delay (Figure 2.1 shows the variables in the single-trial Stroop
Our main hypothesis stems from our review of the literature and the characteristics
of these two tasks: we predicted that the computer-based, single-trial Stroop (but not the
card Stroop) would be sensitive to context maintenance deficits in TBI patients. More
specifically, we predicted that TBI patients would be slower than control participants in
each of the three conditions of the card Stroop (i.e., generalized slowing), but that they
would not be disproportionately slower in the incongruent condition (no increased
difference score). Conversely, for the single-trial Stroop, we predicted that, in addition to
generalized slowing, TBI patients would show disproportionately longer RTs than control
participants in the incongruent, color-naming condition, resulting in an increased
difference score between incongruent and neutral conditions. In terms of error rates, we
expected TBI patients to make more errors than control participants only in the
incongruent color-naming condition. We also predicted that, due to a degradation of
context representations, brain-injured patients would make more errors at the long than
short delay, whereas the performance of control participants would not be influenced by
delay (resulting in an interaction between group and delay in the incongruent,
An additional goal of our study was to examine the relation between performance
of TBI patients on the Stroop task and subjective reports of symptomatology. As imaging
techniques proliferate and become a standard tool for evaluating brain trauma, the role of
neuropsychologists in clinical practice tends to move away from lesion localization to a
4 Unlike for RT data, we did not compute an interference score incongruentt neutral) for
error rates, because we expected very low error rates in the neutral condition. Instead, our
prediction regarding a differential deficit of TBI patients at the long delay represented our
attempt to disentangle overall performance impairment from specific deficits in
maintenance of context representations.
more refined description of patients' functional impairments and potential for
rehabilitation (Groth-Marnat, 2000). In the future, patient's needs and pressure from
insurance companies will most likely result in a demand for neuropsychological tests to
become better predictors of symptomatology in brain-injured patients. To our knowledge,
until now, only one study (Levine et al., 2000) has examined the relationship between
Stroop performance and reports of impairment after TBI. Levine et al. have found a small
correlation (R2 = 0.14) between Stroop RT interference score and total score on the
Sickness Impact Profile, a multi-dimensional measure of health status for individuals
with general medical conditions (Bergner, Bobbitt, Pollard, Martin, & Gilson, 1976;
Pollard, Bobbitt, Bergner, Martin, & Gilson, 1976).
In our study, we used self-reports and significant-other reports of symptomatology
obtained on a modified version of the Neurobehavioral Rating Scale (NRS), a 27-item
measure designed specifically to assess impairments after brain injury. We predicted that
performance on the single-trial Stroop, being more sensitive to impairments in TBI,
would be more strongly correlated than performance on the card Stroop with reports of
symptomatology. In addition, we were interested in the following questions:
* In the single-trial Stroop, would RTs and errors contribute independently to
predicting reports of impairments, or would one of them account for most of the
predicted variance in the NRS?
* Would errors be a better predictor of NRS scores at the long than at the short delay,
suggesting that performance after a delay (i.e., with increased working memory
requirements) is more strongly related to reports of impairment in TBI?
* Would self-reports or significant-other reports be most strongly correlated with
Stroop performance? In relation to this last question, Sunderland, Harris and
Baddeley (1983) found that significant-others' ratings of TBI patients' memory
difficulties correlated more strongly than self-reports with their performance on
standard memory tests. If such results were replicated in our study, it would suggest
that significant others, when present, may be better informants of impairment after
brain injury than the patients themselves, a finding that may have important
implications for the assessment and management of TBI.
Participants were 23 individuals with moderate-to-severe closed-head injury and 21
demographically-matched, healthy participants recruited through advertising in the local
community. Consistent with the definition of Alexander (1995), we defined injuries of
the moderate-to-severe range as any injury resulting in loss of consciousness (LOC)
longer than 30 minutes, post-traumatic amnesia (PTA) longer than 24 hours or presence
of lasting focal signs and positive neuroimaging findings.1 We did not distinguish
between moderate and severe brain injury. Data were collected from interviews with TBI
patients at the time of the experiment. Because most patients did not remember their
score on the Glasgow Coma Scale (GCS) at the time of injury, this variable was not used
in our classification of severity. Excluded from the study were all individuals below 18 or
above 55 years of age, and all participants reporting a history of schizophrenia or bipolar
disorder, a history of formally diagnosed attention-deficit/hyperactivity disorder, a
history of learning disability, a history of chronic alcohol or drug abuse extending within
a 6-months period before testing, a history of other acquired brain damage (e.g., stroke,
epilepsy), a history of inpatient psychiatric hospitalization predating brain injury, or a
history of significant depression or anxiety predating brain injury and extending within a
1 In our sample, all of the participants classified as moderate-to-severe TBI, but one
reported an LOC greater than 30 minutes or a PTA greater than 24 hours. This participant
reported an LOC and PTA of 1 minute, but presented with linear skull fracture, subdural
hematoma and significantly impaired senses of smell and taste.
2-year period before testing. In addition, brain-injured participants had to be at least 1
month after injury. Exclusion based on current medication use was determined on a
case-by-case basis, depending on whether the medication had documented effects on
concentration and attention.
Demographic variables of brain-injured patients and control participants are shown
in Table 2-1. The two groups did not differ significantly in terms of gender, &(1, 42), 1 >
0.5, age, t(42) = -1.8, p > 0.08, education, t(42) = 0.2, p > 0.8, mother's education, t(42) =
1.5, 2 > 0.1, and father's education, t(42) = -0.6, 2 > 0.5. Median scores (ranges) for time
since injury, LOC, and PTA in the TBI group were 65 months (1.5 to 444 months), 72
hours (1 minute to 2160 hours) and 692 hours (1 minute to 4320 hours), respectively.
We used the three-card version of the Stroop test most frequently used in clinical
settings (Golden, 1978). This version includes three cards, administered in fixed order,
that consist of five columns of 20 items each. The first card contains lists of color words
(BLUE, GREEN and RED) printed in black ink, which participants were instructed to
read aloud as quickly and as accurately as possible (word-reading condition). The second
card contains rows of four colored Xs and participants were instructed to name the color
of the printed Xs (color-naming condition). The third card contains lists of words printed
in incongruent colors (e.g., BLUE printed in red ink), and participants were required to
name the printed color of the ink (color-word-naming or conflict condition). For each
card, participants were given 45 seconds to complete as many items as possible, without
skipping any. Whenever participants made a reading or naming error, they were briefly
instructed to correct their response.
Table 2-1. Demographics and injury variables by group
Controls participants TBI patients
(n = 21) (n = 23)
Males/females 12/9 15/8
M SD M SD
Age (years) 36.3 10.1 42.0 11.2
Education (years) 14.0 1.6 13.9 2.0
Mother's education (years) 13.9 3.0 12.7 2.3
Father's education (years) 13.6 3.4 14.1 2.6
For the different subtests of the card Stroop, Golden (1975) found test-retest
reliabilities ranging from 0.73 to 0.89 in a normal sample. Golden (1976) also found the
card Stroop to be fairly accurate in distinguishing brain-injured individuals from normal
participants and psychiatric patients.
Participants also performed a computer-based, single-trial version of the Stroop
task, originally developed by Cohen et al. (1999). Stimuli were presented on an Apple
Macintosh computer using PsyScope software (Cohen, MacWhinney, Flatt, & Provost,
1993). At the beginning of each trial, they were presented with an auditory cue ("Word"
or "Color"), followed by a visual stimulus. They were instructed to respond verbally to
the stimulus, and their RTs were determined by a voice-activated relay connected to the
computer. The examiner recorded responses manually for coding of accuracy. The same
basic three colors and color words (blue, red, and green) as in the card Stroop were used.
There were two task conditions (color naming and word reading), two delay conditions
(corresponding to a delay of Is and 5s, respectively, between the cue and the probe); and
three congruency conditions (congruent, neutral, and incongruent); for a total of 12 trial
types (Figure 2-1). In the congruent condition, stimuli were color words presented in their
own color ink. Incongruent stimuli consisted of color words printed in one of the two
remaining colors, and neutral stimuli were four colored Xs for color-naming trials and
color words displayed in white for word-reading trials.2 A total of 180 experimental trials
were distributed randomly across trial types, resulting in an average number of 15 trials
of each type. Because of random effects, this number was not always equal to 15, but fell
between 8 and 24. Because of its novelty, reliability and validity estimates were not
available for this computer-based task.
Figure 2-1. Schema of the single-trial Stroop. Participants were first presented with an
instructional cue ("Color" or "Word"), followed by a delay (1 or 5 seconds)
and an imperative stimulus (congruent, neutral or incongruent).
Neurobehavioral Rating Scale (NRS)
A modified version of the NRS was used to estimate current functioning in TBI
patients and control participants. This 27-item instrument was originally based on
clinician ratings, and was specifically designed to estimate cognitive, behavioral, and
emotional changes after brain injury (Levin et al., 1987). We used the modified version,
2 Although one could argue that white is also a color, and that neutral stimuli in the
word-reading condition were not really "neutral", the important point here is that "White"
was not part of the response set in any of the trial types. A further indication that the
white color did not substantially interfere with the reading of the color words is that none
of our participants ever answered "White" to any of the stimuli.
developed by Mathias and Coats (1999), to enable self-report. Each of the 27 items was
rated using a 5-point scale (from "never" to "very often"). In addition to self-report
ratings, each participant was given a copy of the scale to be completed by a significant
other. Previous versions of the NRS (Levin et al., 1987) showed high inter-rater
reliability (0.88 and 0.90 for two different samples of brain-injured patients) and internal
consistency for self and significant-other's ratings ranged from 0.92 to 0.96 (Mathias &
Coats, 1999). One brain-injured patient had a missing item on self-report. Four
significant others of normal participants and one significant other of a brain-injured
patient failed to return their questionnaires. Finally, one significant-other report of a
brain-injured patient had a missing item. NRS data for these participants were excluded
from relevant analyses.
In addition to the total score, previous factor-analytic studies of the NRS and the
NRS-Revised (NRS-R), a revised version of the NRS developed by Vanier, Mazaux,
Lambert, Dassa and Levin (2000), suggested that at least three factors (relatively stable
across studies) could be extracted from this instrument: a cognition/attention factor, a
hyperactivity factor, and a mood/affect factor (Levin et al., 1987; McCauley et al., 2001;
Vanier et al., 2000). Based on these previous studies, we calculated three surrogate factor
scores by summing ratings across selected items (Hair, Anderson, & Black, 1995),
separately for each of the two rating forms (self and significant-other's ratings). The
cognition/attention factor included Items 3 (Disorientation), 7 (Confusion), 10 (Memory),
and 23 (Planning). The hyperactivity factor included Items 8 (Disinhibition), 11
(Restlessness), 22 (Excitement), and 25 (Tenseness). The mood/affect factor included
Items 6 (Emotional (Guilt), 13 (Depressed Mood), 14 (Irritability), and 15 (Motivation).
The Digit Span forward and backward and Digit Symbol-Coding subtests of the
Weschler Adult Intelligence Test-Third Edition (WAIS-III) were administered as
estimates of working memory and processing speed, respectively. Reliability estimates of
the Digit Span ranged 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 (WAIS-III and
WMS-III Technical Manual, 1997). Test-retest reliability estimates of the Digit
Symbol-Coding ranged from 0.81 to 0.87 and its correlation with the processing speed
index of the WAIS-III was estimated at 0.91 (WAIS-III and WMS-III Technical Manual,
North American Adult Reading Test (NAART)
The NAART is often used in neuropsychological evaluations as a measure of
premorbid intelligence after brain injury or the onset of a dementia (Spreen & Strauss,
1991). It has been shown to be a good estimate of WAIS-R and WAIS-III scores,
especially in the average range of intellectual abilities (Johnstone, Callahan, Kapila, &
Bouman, 1996). However, it may tend to overestimate low IQ scores and underestimate
high IQ scores (Johnstone et al., 1996).
Participants were administered all of the tasks described above as part of a larger
battery. The total duration of testing fell between 4 and 5 hours, and order was
counterbalanced across tasks.
Analyses of the Stroop data were conducted separately for the word-reading and
color-naming tasks. For the card Stroop, the primary dependent variables were the
number of items completed on each card within the 45-second time-limit. We conducted
a 2 x 2 analysis of variance (ANOVA) with group as the between-subjects factor and
condition (color naming and color-word naming) as the within-subject factor. We
conducted a separate t-test for the word-reading condition.
For the single-trial Stroop task, RTs and error rates were analyzed separately. For
each trial type and each participant, we calculated the median RT for correct responses3
and conducted separate 2-Group x 2-Delay x 3-Congruency ANOVAs for the
word-reading and color-naming tasks. Between-group planned comparisons evaluated
interference effects incongruentt RT vs neutral RT) in the color-naming task. The raw
data for error rates were normalized using the arcsin transformation (Neter, Wasserman,
& Kutner, 1985) before all analyses. We conducted separate 2 x 2 x 3 ANOVAs for
word-reading and color-naming tasks. To statistically evaluate the primary prediction of
interest, we also conducted a focused Group x Delay ANOVA on the incongruent
color-naming condition to test our prediction of increased error rates in TBI patients at
the long delay.
Given the expected restricted range of NRS scores in healthy controls, we restricted
our analyses of correlations between ratings on the NRS and performance on the Stroop
task to the TBI group. To limit the number of correlations computed, we used five simple
performance indices from the Stroop tasks:
* For the card Stroop, total number of items computed in the color-word naming
3 In situations where subjects' variability is expected to be important, and in which the
probability of outliers may be different across conditions, Median RTs are fairly robust to
outliers and have good power compared to other measures of central tendency (Ratcliff,
For the single-trial Stroop, median RT in the incongruent word-reading task,
median RT in the incongruent condition of the color-naming task, error rates in the
word-reading task, and error rates in the color-naming task (for the four indices of
the single-trial Stroop, we used the average of scores at the short and at the long
Means and standard deviations of the performance of TBI patients and control
participants on various neuropsychological tests are presented in Table 3-1.
Table 3-1. Performance on neuropsychological tests by group
Control participants TBI patients
(n = 21) (n = 23)
M SD M SD
NAART (errors) 26.2 9.2 33.7 14.1
Digit span forward (raw scores) 10.4 1.9 9.7 2.5
Digit span backward (raw scores) 6.7 2.1 5.7 2.2
Digit symbol (# items completed)a 89.1 15.7 65.3 16.4
aBecause the Digit Symbol was included only later in our protocol, the data for this task include
only 19 control participants and 15 TBI patients out of our total sample.
The two groups did not differ in terms of their performance on the Digit Span
Forward, t(43) = 0.6, p > 0.3, or Backward, t(43) = 1.6, p > 0.11. Brain-injured patients,
however, committed significantly more errors on the NAART than control participants,
t(43) = -2.1, p = 0.046, suggesting slightly lower verbal IQ in TBI patients. TBI patients
also completed significantly fewer items on the Digit Symbol task than control
participants, t(32) = 4.3, p < 0.001, suggesting lower processing speed in TBI patients.
Means and standard errors of the number of items completed on each card for each
group are presented in Figure 3-1. Control participants completed significantly more
items than TBI patients in the word-reading condition, t(42) = 6.2, P < 0.001. The 2 x 2
ANOVA including group as a between-factor and color-naming and color-word-naming
conditions as repeated measures yielded main effects of group, F(1, 42) = 45.3, p < 0.001,
and condition, F(1, 42) = 440.1, p < 0.001. The Group x Condition interaction was also
significant, F(1, 42) = 8.2, p < 0.01, reflecting a smaller interference score (number of
items completed in the color-naming condition minus number of items completed in the
color-word-naming condition) for brain-injured patients (M = 25.4, SD = 8.5) than for
control participants (M = 33.4, SD = 10.0). These results suggest that Stroop interference
was less strong in TBI patients than in control participants, a finding inconsistent with the
hypothesis of a deficit in inhibition of a prepotent response in brain-injured individuals.
WR CN CWN
Figure 3-1. Number of items completed on the card Stroop by group and condition. Error
bars represent standard errors.
Single-Trial Stroop: Speed-Accuracy Tradeoff Analyses
In order to ensure that there were no speed-accuracy tradeoffs in either group, we
calculated the correlations between median RT and error rates in the incongruent
condition for both groups, separately for color-naming and word-reading tasks. All
estimates were positive except for the control group in the color-naming task, where the
correlation was negative, r(20) = -0.25, although not significantly, 1(20) = -1.1, p > 0.2.
These results suggest that speed-accuracy tradeoffs did not play a significant role in the
performance of TBI patients or control participants.
Single-Trial Stroop: RTs
Means and standard deviations of median RT for each group and each condition are
presented in Table 3-2. In the word-reading task, control participants were faster than
brain-injured patients, F(1, 42) = 16.7, p < 0.001, and RTs were longer at the short than
long delay, F(1, 42) = 5.6, p < 0.03. There was also a significant effect of congruency,
F(2, 42) = 24.5, p < 0.001. Fisher's post-hoc comparisons revealed that RTs were longer
in the incongruent than in the congruent (p < 0.001) and neutral (p < 0.001) conditions,
whereas the difference between the neutral and congruent conditions was not significant
(p > 0.5). None of the interaction effects reached significance (all P > 0.1). These findings
suggest generalized slowing in TBI patients.
Table 3-2. Means and standard deviations of median RT (ms) in the single-trial Stroop
Control participants TBI patients
(n = 21) (n = 23)
M SD M SD
Congruent 820 174 951 139
Neutral 786 174 992 158
Incongruent 894 204 1082 286
Congruent 767 149 936 152
Neutral 732 200 957 154
Incongruent 839 136 1015 172
Congruent 838 199 1027 179
Neutral 770 138 967 155
Incongruent 1035 192 1310 249
Congruent 775 159 1014 215
Neutral 726 97 940 144
Incongruent 987 193 1265 258
In the color-naming task, control participants were faster than brain-injured
patients, F(1, 42) = 24.9, p < 0.001, and RTs were longer at the short delay than long
delay, F(1, 42) = 10.7, p < 0.003. There was also a significant effect of congruency, F(2,
42) = 89.8, p < 0.001. Fisher's post-hoc comparisons revealed that RTs were longer in the
incongruent than in the congruent (p < 0.001) and neutral (1 < 0.001) conditions. RTs
were also significantly longer in the congruent than in the neutral condition, p < 0.01.
None of the interaction effects reached significance, all p > 0.1.
More importantly, the two groups were compared with respect to the interference
score (difference between the incongruent and neutral conditions), at the short and long
delays separately. Control participants (M = 265, SD = 132) did not differ significantly
from TBI patients (M = 343, SD = 215) at the short delay, t(42) = -1.4, 2 > 0.1, nor at the
long delay (control participants: M = 262, SD = 130; TBI patients: M = 326, SD = 170),
t(42) = -1.4, p > 0.1. These results suggest generalized slowing but no disproportionate
Stroop interference in TBI patient.
Single-Trial Stroop: Error Rates
Means and standard deviations for the error rates are displayed in Table 3-3, and
the ANOVA results are presented in Table 3-4. In order to decompose the significant
interaction between group and congruency in the word-naming task, we conducted
separate analyses for each of the congruency condition, with delay as a within-subjects
factor and group as a between-subjects factor. In the incongruent, but not in the congruent
and neutral conditions, brain-injured patients committed significantly more errors than
control participants, F(1, 42) = 6.8, p < 0.03. None of the other effects were statistically
Table 3-3. Means and standard deviations of error rates (%) in the single-trial Stroop
Control participants TBI patients
(n = 21) (n = 23)
M SD M SD
Congruent 0 0 0 0
Neutral 0 0 .4 1.7
Incongruent 0 0 2.0 4.6
Congruent 0 0 0 0
Neutral 0 0 .7 2.3
Incongruent .3 1.3 3.1 6.0
Congruent 0 0 0 0
Neutral 0 0 0 0
Incongruent 7.3 8.6 14.5 18.3
Congruent .7 2.2 0 0
Neutral .4 1.8 .2 1.0
Incongruent 2.8 6.0 16.5 23.1
Table 3-4. ANOVA for error rates in the single-trial Stroop
Word reading Color naming
Source df F df F P
Between subjects Between subjects
Group 3 6.8 0.013 3 5.0 0.03
Within subjects Within Subjects
Delay 1 1.3 > 0.2 1 .1 > 0.5
Congruency 2 6.7 0.002 2 20.9 < 0.01
Group x delay 3 .6 > 0.4 3 2.2 > 0.1
Group x congruency 6 5.3 0.007 6 5.9 0.004
Delay x congruency 2 .7 > 0.5 2 .7 > 0.4
Group x delay x congruency 6 .2 > 0.5 6 3.3 0.04
We followed the same procedure to decompose the significant three-way
interaction in the color-naming task. In the congruent and neutral conditions, none of the
effects reached significance (all es > 0.1). In the incongruent condition, there was a main
effect of group, F(1, 42) = 7.2, p < 0.02, and, more importantly, a near-significant
interaction between group and delay, F(1, 42) = 4.0, p = 0.052. Consistent with our
primary prediction, the difference between the two groups was significant at the long
delay, 1(42) = 3.2, p < 0.003, but not at the short delay, t(42) = 1.5, p > 0.1 (Figure 3-2).
In terms of effect sizes, the difference between the two groups was moderate at the short
delay, d = 0.49, and large at the long delay, d = 0.97. In addition, complementary
analyses revealed that control participants committed significantly fewer errors at the
long than short delay, t(42) = 2.7, p < 0.02, whereas error rates for TBI patients did not
differ as a function of delay, t(42) = -0.3, p > 0.5. Consistent with our primary prediction,
these results suggest a disruption over time of context representations in TBI patients
compared to healthy participants.
20 :n tr,:,
Figure 3-2. Error rates in the incongruent color-naming condition of the single-trial
Stroop by Group and Delay. Error bars represent standard errors.
Neurobehavioral Rating Scales
Cronbach-alpha internal consistency estimates for self and significant-others'
ratings are presented in Table 3-5. Internal consistency estimates were satisfactory (above
0.80) for self-ratings in the TBI group, but tended to be lower (below 0.80) in the control
group. They also tended to be low in certain subscales of significant-others' ratings, for
both the TBI and the control group. The lower estimates for the control group are not
surprising, given that the NRS was developed specifically for assessing impairment after
brain injury. In addition, they should not constitute a significant threat to the validity of
our study, since our analyses of the relations between reports of impairment and
performance on the Stroop tasks were restricted to the TBI group. The lower internal
consistency estimates for the significant-others' ratings of brain-injured patients, on the
other hand, suggest that the relationship between these ratings and the performance of
TBI patients should be interpreted with caution.
Table 3-5. Internal consistency (alpha-cronbach) estimates for the NRS for self and
significant-other's ratings by group
Control participants TBI patients
Self-rating Sign. Other Self-rating Sign. Other
Total 0.93 (21)a 0.93 (17) 0.93 (22) 0.88 (21)
Cognition 0.69 (21) 0.60 (17) 0.82 (23) 0.85 (22)
Hyperactivity 0.65 (21) 0.74 (17) 0.86 (23) 0.66 (21)
Mood 0.80 (21) 0.82 (17) 0.82 (23) 0.45 (22)
aThe number of participants used for this particular estimate is in parentheses. Because of missing
questionnaires and missing items, this number varies slightly for each subscale.
Means and standard deviations for each of the surrogate factor scores and for the
total NRS score are reported in Table 3-6.
Table 3-6. Means and standard deviations of NRS surrogate factor scores and total score
Control participants TBI patients
(n = 17) (n = 20)
M SD M SD t
Cognition 0.82 0.53 2.06 1.02 4.8 < 0.001
Hyperactivity 1.02 0.58 1.79 1.04 2.8 < 0.01
Affect 0.92 0.65 1.84 1.02 3.6 < 0.001
Total 0.82 0.46 1.81 0.79 5.2 < 0.001
Cognition 0.62 0.57 2.09 1.00 5.0 < 0.001
Hyperactivity 1.16 0.70 1.55 0.68 1.4 0.17
Affect 1.11 0.71 1.50 0.64 1.8 0.08
Total 0.88 0.54 1.57 0.54 3.5 < 0.002
Data from four control participants and three TBI patients were not included due to
missing items or because the significant other failed to mail or bring back the
questionnaire. NRS scores show that brain-injured patients viewed themselves as having
significantly more cognitive and emotional difficulties and as being more hyperactive
than control participants. Significant others also rated TBI patients as more cognitively
impaired than control participants. There was, however, no significant difference between
the two groups in the significant-other ratings of hyperactivity or emotional functioning.
Table 3-7. Correlations between self and significant-others' ratings on the NRS
C/S H/S M/S T/S C/O H/O M/O T/O
Cognition -self 0.61* 0.55* 0.82* 0.19 0.16 0.25 0.20
Hyperactivity self 0.33 0.59** 0.82** 0.10 0.08 0.27 0.13
Mood- self 0.52** 0.61* 0.87** 0.01 0.25 0.14 0.19
Total- self 0.79** 0.72** 0.82* 0.10 0.19 0.25 0.21
Cognition- other 0.27 0.18 -0.18 0.04 0.78** 0.79** 0.88*
Hyperactivity other 0.21 0.64** 0.44* 0.41 0.07 0.82** 0.93**
Mood- other 0.28 0.62** 0.47* 0.55** 0.29 0.65 0.93**
Total other 0.33 0.59** 0.23 0.44 0.61** 0.72** 0.80** -
Note. Upper right = control participants; Lower left = TBI patients. In the upper row, C stands for
cognition, H for hyperactivity, M for mood and T for total; S stands for self-ratings and O for
*p < 0.05. **p < 0.01.
Correlations between the surrogate factor scores of the NRS and between self and
significant-other ratings are presented in Table 3-7. Correlations between the scores on
the various factor scores of the NRS were generally moderate to high within raters, but
low between self and significant-other ratings, with the notable exception of significant
and moderate correlations between self-ratings of hyperactivity and significant-other's
ratings of hyperactivity, mood and total NRS score in the TBI group.
Correlations between ratings on the NRS and performance indices on the Stroop
tasks are presented in Table 3.8. As predicted, performance on the card Stroop was not
significantly correlated with self and significant-others' ratings of reports of
symptomatology. RTs in the single-trial task were also unrelated to reports of
impairment, as were error rates in the word-reading task, with the exception of a
significant correlation with self-ratings of mood. Error rates in the color-naming task,
however, were significantly correlated with all three surrogate factor scores of the NRS
for self-ratings, and with significant-others' ratings of hyperactivity.
Table 3-8. Correlations between ratings on the NRS and Stroop performance (TBI group)
Card RT word RT color Errors Errors
Stroopa word color
Cognition -self 0.34 0.15 0.21 0.33 0.45
Hyperactivity self 0.06 0.25 0.38 0.35 0.48*
Mood self 0.05 0.22 0.27 0.46* 0.68*
Total self 0.26 0.24 0.31 0.49 0.61*
Cognition other 0.15 0.17 0.22 -0.09 -0.01
Hyperactivity other -0.13 0.12 0.27 0.33 0.49*
Mood other 0.07 0.01 0.11 0.22 0.41
Total other 0.10 0.18 0.38 0.19 0.34
aFor the card Stroop, we reversed the sign of the correlation, as a larger number of items
completed means better performance, whereas larger RTs and error rates in the single-trial Stroop
mean worse performance.
*p < 0.05. **p < 0.01.
We conducted multiple regression analyses to examine the extent to which self and
significant-others' ratings independently predicted color-naming error rates (Table 3-9).
Table 3-9. Multiple regressions with self and significant-others' ratings as independent
variables and error rates (color naming) as the dependent variables (TBI
Total R Self-ratingsa Significant other
Cognition 0.21 0.47 -0.13
Hyperactivity 0.28 0.25 0.33
Mood 0.47 0.62* 0.12
Total 0.34 0.55* 0.08
aNormalized beta weights.
*p < 0.05.
For the cognition and mood subscales, and for the total NRS score, self-ratings
remained significant predictors of error rates whereas significant-others' ratings did not
reliably contribute to the predicted variance. These results suggest that self-reports of
impairment in TBI may be more related than significant-other reports to performance on
We also computed the correlations between self-ratings on the NRS and
color-naming error rates at the long and short delays separately (Table 3-10). As
correlations tended to be qualitatively higher with errors at the long delay, we conducted
multiple regressions with error rates at the short and long delays as independent variables,
and cognition, hyperactivity, mood and total score as dependent variables. As seen in
Table 3-11, normalized beta weights were generally not significant, except for mood,
where error rates at the long, but not at the short delay, were uniquely predictive of
Table 3-10. Correlations between self-ratings on the NRS and color-naming error rates at
the long and short delays separately (TBI group)
Errors short delay Errors long delay
Cognition 0.38 0.45
Hyperactivity 0.44* 0.45*
Mood 0.56** 0.70**
Total 0.54** 0.59**
*p < 0.05. **p < 0.01.
Table 3-11. Multiple regressions with color-naming error rates at the long and short
delays as independent variables and NRS self-ratings as dependent variables
Total R Errors short delaya Errors long delaya
Cognition 0.21 0.10 0.38
Hyperactivity 0.23 0.24 0.27
Mood 0.49 0.07 0.65*
Total 0.37 0.21 0.43
aNormalized beta weights.
*p < 0.05.
The results of our study suggest that the performance of brain-injured patients on
two versions of the Stroop paradigm is consistent with the presence of a deficit in the
preparation to override prepotent response tendencies. On the card Stroop, TBI patients
did not show deficits in inhibition of prepotent response tendencies beyond generalized
slowing: they were slower than control participants on every condition of the task, but not
disproportionately slower in the color-word naming (or interference) condition.1 This
finding is consistent with previous literature showing generalized slowing of TBI patients
(Guskiewicz et al., 1997; Rojas & Bennett, 1995; Stuss et al., 1985; Trennery et al., 1989)
but mixed results across studies regarding disproportionate slowing in the interference
condition of the Stroop task (Batchelor et al., 1995; Bate et al., 2001; Bohnen, Jolles et
al., 1992; Bohnen, Twijnstra et al., 1992; McDowell et al., 1997; Ponsford & Kinsella,
1992). The same result was observed when analyzing the RT data from the single-trial,
computer-based version of the task. Again, TBI patients were slower on every condition
(for both the color-naming and the word-reading tasks), but not disproportionately slower
1 In fact, as shown in the results section, the difference score between the color-word
naming and the color-naming conditions was larger in control participants than in TBI
patients. If considered too literally, these results may suggest that individuals having
sustained brain injury show better inhibition of prepotent response tendencies than
healthy participants. As pointed out by Chapman, Chapman, Curran, and Miller (1994),
though, RTs' difference scores cannot always be assumed to be free of the effects of
generalized slowing, especially when the two groups being considered differ significantly
in terms of their baseline scores. This is precisely the case in our study, where
brain-injured patients completed fewer items than controls in the color-naming condition.
on the incongruent, color-naming condition compared to control participants. In contrast,
examination of error rates revealed that TBI patients showed a pattern of performance
suggestive of inhibitory deficits: they committed more errors than control participants on
the incongruent, but not on the congruent and neutral conditions of the color-naming task.
Even more importantly, their error rates differed from those of control participants at the
long, but not at the short delay of the incongruent condition. This later result is consistent
with the main prediction stemming from the hypothesis of a context maintenance deficit
in a given population (Cohen et al., 1999; Cohen et al., 1996): the poorest performance
should be observed in conditions in which there are both inhibitory and working memory
requirements. This is precisely the case for the long delay, incongruent color-naming
condition of the single-trial Stroop, where participants have to maintain the context (i.e.,
task instructions) over the delay in order to inhibit the prepotent tendency to read the
word. Our overall findings parallel those ofPerlstein et al. (1998), who found that
schizophrenics showed increased error rate interference on the single-trial Stroop, but no
increased RT interference on the card or single-trial Stroop. They suggest that working
memory and inhibition of prepotent response tendencies are two closely related
processes, a hypothesis consistent with the results of Roberts, Hager and Heron (1994),
who found that requiring healthy participants to maintain and manipulate information in
working memory decreased performance on the antisaccade task.
In order to examine the ecological validity (i.e., the relation between performance
and day-to-day difficulties experienced by TBI patients) of the two versions of the Stroop
paradigm used in our study, we compared various indices of performance of TBI patients
with their report and significant-others' report of impairment after injury along the three
surrogate factor scores of the NRS (Levin et al., 1987): cognitive functioning,
hyperactivity and mood. Number of items completed in the card Stroop and median RTs
in the single-trial Stroop were not significantly related to reports of impairment. Error
rates, on the other hand, especially in the color-naming task, were significantly correlated
with reports of impairment along all three surrogate factor scores. The correlations
generally fell in the moderate range and were of greater magnitude than the relation
between RT interference score and Sickness Impact Profile total score reported in
(Levine et al., 2000). Interestingly, the relation between performance and impairment
after injury tended to be stronger for self-reports than significant-others' reports. This
result contrasts with the finding by Sunderland et al. (1983) that significant-others'
ratings of TBI patients' memory difficulties correlated more strongly than self-reports
with their performance on standard memory tests. This discrepancy between the two
studies raises the possibility that self-report of TBI patients may be more reliable for
general areas of functioning (i.e., cognition or mood) than for specific deficits after
injury. Our results suggest that the long-lasting emotional, behavioral and cognitive
difficulties incurred by individuals having sustained brain injury (Mathias & Coats, 1999;
Olver et al., 1996) may be related to and predicted by their performance on tasks
requiring the maintenance of context representations. Future studies are needed to
examine whether the relation between cognitive performance and self-reports of
impairment generalizes to objective psychosocial outcomes after brain injury, such as
social isolation, employment status or ability to drive.
One pervasive issue confronted by cognitive neuropsychologists is the difficulty to
show the specificity of deficits in a given population. Simply stated, the finding that a
group of patients differs significantly from control participants on a given task is not
sufficient to conclude that this group is specifically impaired regarding the ability
purportedly measured by the task: indeed, several general factors, such as poor attention,
concentration, or motivation, result in poor performance across a broad array of tasks.
Moreover, as Chapman, Chapman, Curran, and Miller (1994) pointed out, the use of
difference scores for RTs (or number of items completed), such as in the traditional card
Stroop, cannot always be assumed to "remove" the effects of generalized slowing.
Similarly, the use of difference scores for error rates does not always correct for the
effects of generalized deficits, especially when the two groups compared in the study
differ regarding their baseline error rates (Chapman & Chapman, 1988, 1989). In our
study, for instance, TBI patients' and control participants' error rates differed in the
incongruent, but not in the congruent or neutral conditions of the color-naming task of the
single-trial Stroop. This finding, however, does not provide strong evidence for the
specificity of the deficits shown by brain-injured patients, because both groups were at
floor levels in the congruent and neutral conditions. The fact, however, that the two
groups differed significantly at the long, but not at the short delay of the incongruent
condition, suggests that the deficits experienced by TBI patients are specific rather than
generalized. As we mentioned before, this finding is exactly in line with the predictions
stemming from the hypothesis of a deficit in the maintenance of context representations.
As suggested by our study, the concept of context representations provides a
theoretical framework with the potential to explain a vast array of seemingly disparate
deficits in a variety of populations, such as schizophrenics (see e.g., Cohen et al., 1999;
Cohen et al., 1996; Perlstein et al., 1998) and older adults (see Braver & Barch, 2002;
Braver et al., 2001).2 This framework also provides a starting point for the study of the
neurochemical and neurobiological bases of cognitive control: namely, Cohen and
Servan-Schreiber (1992; 1993) have postulated that the maintenance of context
representations is related to the DA system in the prefrontal cortex (PFC), and
specifically the dorsolateral prefrontal cortex (DL-PFC). Indeed, a large body of literature
now supports an important role of the DL-PFC in working memory and cognitive control
(see Salmon, Heindel, & Hamilton, 2001, for a review), and several studies have shown
the role of the DA system on cognitive control tasks (Braver et al., 2001). As mentioned
before, neuroimaging studies (Levin & Kraus, 1994) suggest that the frontal lobes may be
especially vulnerable to TBI. Functional imaging studies of TBI patients during working
memory tasks resulted in a more dispersed pattern of cerebral activation than in healthy
controls, with increased lateralization to the right hemisphere, especially in the parietal
and frontal lobes (Christodoulou et al., 2001; McAllister et al., 1999). In addition,
McDowell, Whyte, & D'Esposito (1998) conducted a double-blind, placebo controlled
study on the effects of a DA receptor agonist on patients having sustained TBI. They
found that the performance of TBI patients who were administered the DA agonist
improved specifically on dual tasks and other tasks with cognitive control demands.
2 An alternate conceptual framework, developed by Kimberg and Farah (1993), may also
explain the findings of our study: these authors propose that a weakening of the
associations among working memory representations is responsible for the various
"executive" deficits observed following frontal lobe damage. They note that their account
of frontal lobe dysfunction and the maintenance of context representations model
developed by Cohen and Servan-Schreiber (1993) yield similar predictions for many
"executive" task, but differ in terms of the neural mechanisms underlying normal and
impaired performance. They also contend that a deficit in context maintenance, contrary
to their model, fails to account for the deficits in contextual memory observed in patients
with frontal lobe lesions. Although we chose to present the model of Cohen and
Servan-Schreiber as a framework for developing our predictions, we note that both
theories may equally explain the results of our study.
Taken together, these findings provide some evidence for the hypothesis that the
disturbances of cognitive control experienced by brain-injured patients may be mediated
by a disruption of the DA system in the DL-PFC.
It should be pointed out, however, that the DL-PFC is not the only area of the PFC
that has been implicated in the completion of the incongruent condition of the Stroop
task. In a study of patients with focal lesions localized in different areas of the frontal
lobes, Stuss, Floden, Alexander, Levine, and Katz (2001) found that an increased
interference score was observed for patients in the superior medial frontal areas. Lateral
lesions were associated with increased error rates rather than a disproportionate
interference score. In an event-related potential (ERP) study of Stroop performance in
mild TBI patients, Potter, Jory, Basset, Barrett and Mychalkiw (2002) found an increased
negativity, compared to control participants, in a latency range consistent with the
activation of the anterior cingulate (AC) gyms. They interpreted these findings as
suggesting that brain-injured patients may have to engage in more effortful processing to
achieve the same performance than control participants. Using functional magnetic
resonance imaging (fMRI), MacDonald, Cohen, Stenger and Carter (2000) found a
dissociation of the role of the DL-PFC and the AC on a long-delay version of the
single-trial Stroop task in healthy participants: whereas the DL-PFC was more active,
during task preparation, for the color-naming conditions (consistent with a role in
cognitive control), the AC was more active when responding to incongruent stimuli,
consistent with a role in conflict monitoring. These results, combined with the findings
by Potter et al. (2002), suggest that TBI patients may compensate for their difficulties
with cognitive control related to impaired functioning of the DL-PFC by an increased
activation of the AC during performance monitoring. Future research using functional
imaging and event related potentials (ERPs) to examine the relation between DL-PFC
and AC activation in TBI patients and healthy participants may confirm or disconfirm
this hypothesis and help uncover the mechanisms of recovery and compensation after
A number of limitations and alternate explanations to the present findings require
discussion. First, any study of TBI must take into account the heterogeneity of this
population in terms of time since injury, severity and injury localization (Lezak, 1995).
Previous studies examining the performance of TBI patients on the Stroop task have
varied greatly in terms of injury severity (see Table 1-1). In our experiment, all TBI
patients had sustained moderate-to-severe injuries. Obviously, our results cannot readily
generalize to mild TBI, which presents with a set of unique issues in terms of assessment
and outcome (Binder, 1997; Binder, Rohling, & Larrabee, 1997; Mathias & Coats, 1999).
Similarly, a direct comparison of our results with previous findings must take into
account the great variability in terms of time since injury across studies. According to
Rao and Lyketsos (2000), cognitive deficits after TBI can be divided into four successive
phases: a first period of coma (which may occur or not), a phase of confusion, agitation
and PTA (lasting from a few days to a month), a third period of recovery of cognitive
functions (up to 24 months), and a fourth phase of generally stable cognitive sequelae
(see Cripe, 1987; Levin et al., 1987). The performance of TBI patients on any cognitive
task, including the Stroop, is likely to vary depending on when they are tested after the
time of the trauma. In our study, most TBI participants (17 out of 23) were tested more
than two years after injury, corresponding to the phase of stable cognitive deficits
according to Rao and Lyketsos (2000) classification. The average time since injury in the
study conducted by Stuss et al. (1985) corresponded to the same fourth phase of cognitive
deficits (M = 2.6 years). By contrast, Bohnen, Jolles, and Twijnstra (1992) conducted
testing from 6 to 14 days after injury. Other researchers (Bate et al., 2001) included
patients with a wide range of time since injury. Future research is needed to explore in a
systematic way the relationship between time since injury and performance on the Stroop
task in TBI patients.
Secondly, the absence of disproportionate slowing of TBI patients in the
incongruent condition of the single-trial Stroop (and in the color-word naming condition
of the card Stroop) may have an alternate explanation than poor sensitivity of RTs to
context maintenance deficits. Namely, we did not discuss so far the possibility than the
prepotent tendency to read words may not be as strong for brain-injured patients as it is
for control participants. If this were the case, brain-injured patients would have less to
inhibit in order to name the color of incongruent stimuli, and the lack of disproportionate
slowing could not be readily interpreted as the absence of an inhibitory (or context
maintenance) deficit. Fortunately, the data from our study allow us to estimate the
prepotency of the tendency to read words in brain-injured patients and control
participants. First, we compared the two groups with respect to median RTs in the
word-reading task, averaged across all conditions. Control participants (M = 806, SD =
159) were indeed faster than TBI patients (M = 989, SD = 137) on this measure, t(42) =
-4.1, p < 0.001. This result, however, cannot be readily interpreted as indicative of a
lesser prepotency to read words in the TBI group, because previous literature shows that
brain injury consistently results in generalized slowing across a broad array of tasks
(Lezak, 1995). In order to control for generalized slowing, we conducted the same
analysis, but after entering the number of items completed in the Digit Symbol task as
covariate. Using this procedure, control participants (M = 835, SD = 42) did not differ
significantly from brain-injured patients (M = 974, SD = 51) in terms of residual scores,
F(1, 30) = 0.2, p > 0.1.3 As a different and complementary way to control for generalized
slowing, we compared the two groups on word-reading and color-naming tasks: if
brain-injured patients were less drawn than control participants to read the word of
presented stimuli, they should show a decreased difference score between word-reading
and color-naming tasks. In order to investigate this possibility, we averaged the median
RTs for all word-reading conditions, on the one hand, and all color-naming conditions, on
the other hand. We then subtracted these totals from one another and compared the two
groups with respect to this difference score. Using this procedure, control participants
actually had a smaller difference score (M = 49, SD = 75) than TBI patients (M = 98, SD
= 84), t(42) = -2.1, p < 0.05. These results suggest that a weaker prepotency to read
words in brain-injured patients is an unlikely explanation for our finding of a lack of
disproportionate slowing in the incongruent condition of the Stroop task for this group.
Another limitation of our study is that we did not measure error rates in the card
version of the Stroop paradigm. As a result, our finding of poor sensitivity of the card
Stroop to the inhibitory deficits after TBI may be due to a general poor sensitivity of RTs
rather than the characteristics of the task itself (i.e., the confounding of errors and number
of items completed and the fact that conditions are blocked, thereby reducing context
maintenance requirements). This is an important point, as our goal in this study was to
3 The above analysis was conducted with 19 control participants and 15 TBI patients out
of our total sample.
show that the performance of TBI patients on different versions of the Stroop paradigm
may be better explained by a deficit in context maintenance than by poor inhibition of
prepotent response tendencies. Future research should take this possibility into account
and include the measurement of error rates in the card Stroop to disentangle these two
In addition, the pattern of error rates in the incongruent, color-naming condition of
the single-trial Stroop was somewhat different from our predictions: although there was,
as we predicted, an interaction between group and delay, this interaction was due to a
reduction in error rates from the short to the long delay in control participants rather than
an increase in TBI patients. In other words, the extended delay allowed healthy
participants to reduce their error rates, which we did not expect, whereas the error rates of
TBI patients remained stable across the two delay conditions. These results suggest that
TBI patients have difficulty in the preparation to override prepotent response tendencies:
contrary to healthy participants, they were not able to use the increased delay to reduce
their error rates. This finding may seem surprising, as the short and long delays were 1
and 5 seconds, respectively, and 1 second may seem a sufficient time to process task
instructions (which, in this study, consisted in a simple auditory word, "color" or "word")
and prepare the inhibition of the prepotent tendency to read the word. Future research
should attempt to examine the processes through which control participants manage to
decrease their error rates between 1 and 5 seconds, and to determine what specific
deficits in brain-injured patients are responsible for their inability to accomplish a similar
decrease. The use of specific strategies (such as rehearsing task instructions in one's mind
during the delay) in brain-injured patients and other populations may be one methodology
to explore these questions in future research.
Finally, our measure of everyday functioning, the NRS, does not have
well-established psychometric properties, especially under its self and significant-other
reports versions. Although useful, because designed specifically for impairments after
TBI, it should be supplemented, in future research, by more well-researched and
documented measures of everyday functioning, such as the Sickness Impact Profile
(Bergner et al., 1976; Pollard et al., 1976). As a positive note, though, we should point
out that the internal consistency estimates in our sample of brain-injured patients tended
to be satisfactory (above 0.80) for self-ratings, despite the small number of items
constituting each of the subscales. However, they tended to be lower for significant
others' ratings, especially for the hyperactivity and mood subscales, which, combined
with the finding of somewhat higher correlations of self-ratings with error rates, suggests
that TBI patients themselves rather than significant others may be better informants of
their symptomatology after brain injury. Future research is needed to confirm and explore
these findings in greater detail.
In our study, we found a significant and moderate correlation between error rates in
the incongruent color-naming condition of the single-trial Stroop and the three surrogate
factor scores of the NRS we extracted from the questionnaires. We failed, however, to
find any meaningful pattern of correlations that would relate performance of TBI patients
on the Stroop task and specific domains of impairment in everyday life. In fact, the two
domains of the NRS we expected to be most related with error rates were cognitive
functioning (because the Stroop task is a cognitive task in nature) and hyperactivity
(because it has frequently been related to malfunctioning of the frontal lobes, which also
play a crucial role in context maintenance). If anything, though, the strongest correlations
in our study were found with the mood factor of the NRS. Future research, using
well-established measures of impairment after illness or injury, should examine more
closely the relation between performance on the Stroop task and domains of everyday
functioning. We should point out, however, that our study is one of the first to examine
the ecological validity of the Stroop task in TBI patients, and that the finding of moderate
correlations with a self-report measure of impairment is an encouraging finding regarding
the usefulness of the Stroop paradigm for predicting adjustment after brain injury.
In conclusion, the results of our study suggest that:
* The performance of TBI patients on a single-trial version of the Stroop task
designed to maximize inhibitory and working memory requirements is consistent
with a deficit in the preparation to override prepotent response tendencies.
* Error rates are more sensitive than RTs to these deficits in TBI populations.
* Deficits in the preparation to override prepotent response tendencies in TBI patients
have meaningful ecological implications, that is, they are significantly related to
self-reports of impairment after brain-injury.
These findings suggest the possibility of developing new tools for the assessment
and prediction of cognitive deficits after TBI. They also offer a framework for the study
of the neural mechanisms responsible for the impairment, recovery and compensation
strategies used by individuals having sustained brain injuries.
LIST OF REFERENCES
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 of Neurology,
Alexander, M. P. (1995). Mild traumatic brain injury: pathophysiology, natural history,
and clinical management. Neurology, 45(7), 1253-1260.
Batchelor, J., Harvey, A. G., & Bryant, R. A. (1995). Stroop colour word test as a
measure of attentional deficit following mild head injury. The Clinical
Neuropsychologist, 9(2), 180-186.
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. Clin Neuropsychol, 15(3), 405-422.
Bergner, M., Bobbitt, R. A., Pollard, W. E., Martin, D. P., & Gilson, B. S. (1976). The
sickness impact profile: validation of a health status measure. Medical Care, 14(1),
Binder, L. M. (1997). A review of mild head trauma. Part II: Clinical implications.
Journal of Clinical and Experimental Neuropsychology, 19(3), 432-457.
Binder, L. M., Rohling, M. L., & Larrabee, J. (1997). A review of mild head trauma. Part
I: Meta-analytic review of neuropsychological studies. Journal of Clinical and
Experimental Neuropsychology, 19(3), 421-431.
Bohnen, N., Jolles, J., & Twijnstra, A. (1992). Modification of the Stroop colour word
test improves differentiation between patients with mild head injury and matched
controls. The Clinical Neuropsychologist, 6(2), 178-184.
Bohnen, N., Twijnstra, A., & Jolles, J. (1992). Performance in the Stroop color word test
in relationship to the persistence of symptoms following mild head injury. Acta
Neurol Scand, 85(2), 116-121.
Braver, T. S., & Barch, D. M. (2002). A theory of cognitive control, aging cognition, and
neuromodulation. Neuroscience and Biobehavioral Reviews, 26(7), 809-817.
Braver, T. S., Barch, D. M., Keys, B. A., Carter, C. S., Cohen, J. D., Kaye, J. A.,
Janowsky, J. S., Taylor, S. F., Yesavage, J. A., Mumenthaler, M. S., Jagust, W. J.,
& Reed, B. R. (2001). Context processing in older adults: evidence for a theory
relating cognitive control to neurobiology in healthy aging. Journal of Experimental
Psychology: General, 130(4), 746-763.
Carter, C. S., MacDonald, A. M., Botvinick, M., Ross, L. L., Stenger, V. A., Noll, D., &
Cohen, J. D. (2000). Parsing executive processes: strategic vs. evaluative functions
of the anterior cingulate cortex. Proceedings of the National Academy of Sciences:
U S A, 97(4), 1944-1948.
Chapman, L. J., & Chapman, J. P. (1988). Artifactual and genuine relationships of lateral
difference scores to overall accuracy in studies of laterality. Psychological Bulletin,
Chapman, L. J., & Chapman, J. P. (1989). Strategies for resolving the heterogeneity of
schizophrenics and their relatives using cognitive measures. Journal of Abnormal
Psychology, 98(4), 357-366.
Chapman, L. J., Chapman, J. P., Curran, T. E., & Miller, M. B. (1994). Do children and
the elderly show heightened semantic priming? How to answer the question.
Developmental Review, 14, 159-185.
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 after
traumatic brain injury. Journal of Neurology, Neurosurgery, and Psychiatry, 71(2),
Cohen, J. D., Barch, D. M., Carter, C., & Servan-Schreiber, D. (1999).
Context-processing deficits in schizophrenia: converging evidence from three
theoretically motivated cognitive tasks. Journal of Abnormal Psychology, 108(1),
Cohen, J. D., Braver, T. S., & O'Reilly, R. C. (1996). A computational approach to
prefrontal cortex, cognitive control and schizophrenia: recent developments and
current challenges. Philosophical Transactions of the Royal Society of London
Series B, 351(1346), 1515-1527.
Cohen, J. D., MacWhinney, B., Flatt, M. R., & Provost, J. (1993). PsyScope: An
interactive graphic system for designing and controlling experiments in the
psychology laboratory using Macintosh computers. Behavioral Research Methods:
Instruments and Computers, 25, 257-271.
Cohen, J. D., & Servan-Schreiber, D. (1992). Context, cortex, and dopamine: a
connectionist approach to behavior and biology in schizophrenia. Psychological
Review, 99(1), 45-77.
Cohen, J. D., & Servan-Schreiber, D. (1993). A theory of dopamine function and its role
in cognitive deficits in schizophrenia. Schizophrenia Bulletin, 19(1), 85-104.
Crevits, L., Hanse, M. C., Tummers, P., & Van Maele, G. (2000). Antisaccades and
remembered saccades in mild traumatic brain injury. Journal of Neurology, 247(3),
Cripe, L. I. (1987). The neuropsychological assessment and management of closed head
injury: General guidelines. Cognitive Rehabilitation, 5(1), 18-22.
Golden, C. J. (1975). The measurement of creativity by the Stroop Color and Word Test.
Journal of Personality Assessment, 39(5), 502-506.
Golden, C. J. (1976). Identification of brain disorders by the Stroop Color and Word Test.
Journal of Clinical Psychology, 32(3), 654-658.
Golden, C. J. (1978). Stroop Color and Word Test, Stoelting. Chicago.
Groswasser, Z., Reider-Groswasser, I., Soroker, N., & Machtey, Y. (1987). Magnetic
resonance imaging in head injured patients with normal late computed tomography
scans. Surgical Neurology, 27(4), 331-337.
Groth-Marnat, G. (2000). Neuropsychological assessment in clinical practice : a guide to
test interpretation and integration. New York: Wiley.
Guskiewicz, K. M., Riemann, B. L., Perrin, D. H., & Nashner, L. M. (1997). Alternative
approaches to the assessment of mild head injury in athletes. Med Sci Sports Exerc,
29(7 Suppl), S213-221.
Hair, J. F., Anderson, R. E., & Black, W. C. (1995). Multivariate Data Analysis (4th ed.).
Englewood Cliffs, NJ: Prentice Hall.
Jahanshahi, M., Profice, P., Brown, R. G., Ridding, M. C., Dirnberger, G., & Rothwell, J.
C. (1998). The effects of transcranial magnetic stimulation over the dorsolateral
prefrontal cortex on suppression of habitual counting during random number
generation. Brain, 121 (Pt 8), 1533-1544.
Johnstone, B., Callahan, C. D., Kapila, C. J., & Bouman, D. E. (1996). The comparability
of the WRAT-R reading test and NAART as estimates of premorbid intelligence in
neurologically impaired patients. Archives of Clinical Neuropsychology, 11(6),
Kiefer, M., Marzinzik, F., Weisbrod, M., Scherg, M., & Spitzer, M. (1998). The time
course of brain activations during response inhibition: evidence from event-related
potentials in a go/no go task. Neuroreport, 9(4), 765-770.
Kimberg, D. Y., & Farah, M. J. (1993). A unified account of cognitive impairments
following frontal lobe damage: the role of working memory in complex, organized
behavior. Journal of Experimental Psychology: General, 122(4), 411-428.
Kingma, A., La Heij, W., Fasotti, L., & Eling, P. (1996). Stroop interference and
disorders of selective attention. Neuropsychologia, 34(4), 273-281.
Kraus, M. F., & Maki, P. M. (1997). Effect of amantadine hydrochloride on symptoms of
frontal lobe dysfunction in brain injury: case studies and review. Journal of
Neuropsychiatry and Clinical Neurosciences, 9(2), 222-230.
Levin, H., & Kraus, M. F. (1994). The frontal lobes and traumatic brain injury. Journal of
Neuropsychiatry and Clinical Neurosciences, 6(4), 443-454.
Levin, H. S., Eisenberg, H. M., & Benton, A. L. (1991). Mild Head Injury. New York:
Oxford University Press.
Levin, H. S., High, W. M., Goethe, K. E., Sisson, R. A., Overall, J. E., Rhoades, H. M.,
Eisenberg, H. M., Kalisky, Z., & Gary, H. E. (1987). The neurobehavioural rating
scale: assessment of the behavioral sequelae of head injury by the clinician.
Journal of Neurology, Neurosurgery, and Psychiatry, 50(2), 183-193.
Levine, B., Dawson, D., Boutet, I., Schwartz, M. L., & Stuss, D. T. (2000). Assessment
of strategic self-regulation in traumatic brain injury: its relationship to injury
severity and psychosocial outcome. Neuropsychology, 14(4), 491-500.
Levine, M. J. (1988). Issues in neurobehavioural assessment of mild head injuries.
Cognitive Rehabilitation, 6, 14-20.
Lezak, M. D. (1995). Neuropsychological assessment (3rd ed.). New York: Oxford
Lishman, W. A. (1988). Physiogenesis and psychogenesis in the 'post-concussional
syndrome'. British Journal of Psychiatry, 153, 460-469.
MacDonald, A. W., 3rd, Cohen, J. D., Stenger, V. A., & Carter, C. S. (2000).
Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in
cognitive control. Science, 288(5472), 1835-1838.
MacLeod, C. M. (1991). Half a century of research on the Stroop effect: an integrative
review. Psychological Bulletin, 109(2), 163-203.
Mathias, J. L., & Coats, J. L. (1999). Emotional and cognitive sequelae to mild traumatic
brain injury. Journal of Clinical and Experimental Neuropsychology, 21(2), 200-
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 1 month after mild traumatic brain injury: a
functional MRI study. Neurology, 53(6), 1300-1308.
McCauley, S. R., Levin, H. S., Vanier, M., Mazaux, J. M., Boake, C., Goldfader, P. R.,
Rockers, D., Butters, M., Kareken, D. A., Lambert, J., & Clifton, G. L. (2001). The
neurobehavioural rating scale-revised: sensitivity and validity in closed head injury
assessment. Journal of Neurolology, Neurosurgery, and Psychiatry, 71(5), 643-651.
McDowell, S., Whyte, J., & D'Esposito, M. (1997). Working memory impairments in
traumatic brain injury: evidence from a dual-task paradigm. Neuropsychologia,
McDowell, S., Whyte, J., & D'Esposito, M. (1998). Differential effect of a dopaminergic
agonist on prefrontal function in traumatic brain injury patients. Brain, 121 (Pt 6),
Miyake, A., Emerson, M. J., & Friedman, N. P. (2000). Assessment of executive
functions in clinical settings: problems and recommendations. Seminars in Speech
and Language, 21(2), 169-183.
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T.
D. (2000). The unity and diversity of executive functions and their contributions to
complex "Frontal Lobe" tasks: a latent variable analysis. Cognitive Psychology,
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.
Olver, J. H., Ponsford, J. L., & Curran, C. A. (1996). Outcome following traumatic brain
injury: a comparison between 2 and 5 years after injury. Brain Injury, 10(11), 841-
Perlstein, W. M., Carter, C. S., Barch, D. M., & Baird, J. W. (1998). The Stroop task and
attention deficits in schizophrenia: a critical evaluation of card and single-trial
Stroop methodologies. Neuropsychology, 12(3), 414-425.
Pollard, W. E., Bobbitt, R. A., Bergner, M., Martin, D. P., & Gilson, B. S. (1976). The
Sickness Impact Profile: reliability of a health status measure. Medical Care, 14(2),
Ponsford, J., & Kinsella, G. (1992). Attentional deficits following closed-head injury. J
Clin Exp Neuropsychol, 14(5), 822-838.
Potter, D. D., Jory, S. H., Bassett, M. R., Barrett, 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(6), 828-837.
Rao, V., & Lyketsos, C. (2000). Neuropsychiatric sequelae of traumatic brain injury.
Psychosomatics, 41(2), 95-103.
Ratcliff, R. (1993). Methods for dealing with reaction time outliers. Psychological
Bulletin, 114(3), 510-532.
Rieger, M., & Gauggel, S. (2002). Inhibition of ongoing responses in patients with
traumatic brain injury. Neuropsychologia, 40(1), 76-85.
Roberts, R. J., Hager, L. D., & Heron, C. (1994). Prefrontal cognitive processes: Working
memory and inhibition in the Antisaccade task. Journal of Experimental
Psychology: General, 123, 374-393.
Rojas, D. C., & Bennett, T. L. (1995). Single versus composite score discriminative
validity with the Halstead-Reitan battery and the Stroop test in mild brain injury.
Archives of Clinical Neuropsychology, 10, 101-110.
Salmon, D. P., Heindel, W. C., & Hamilton, J. M. (2001). Cognitive abilities mediated by
frontal-subcortical circuits. In J. L. Cummings (Ed.), Frontal-subcortical circuits in
psychiatric and neurological disorders (pp. 114-150). New York: The Guilford
Salo, R., Avishai, H., & Lynn, C. R. (2001). Interpreting Stroop interference: An analysis
of differences between task versions. Neuropsychology, 15, 462-471.
Spreen, O., & Strauss, E. (1991). A compendium of neuropsychological tests :
administration, norms, and commentary. New York: Oxford University Press.
Stuss, D. T., Ely, P., Hugenholtz, H., Richard, M. T., LaRochelle, S., Poirier, C. A., &
Bell, I. (1985). Subtle neuropsychological deficits in patients with good recovery
after closed head injury. Neurosurgery, 17(1), 41-47.
Stuss, D. T., Floden, D., Alexander, M. P., Levine, B., & Katz, D. (2001). Stroop
performance in focal lesion patients: dissociation of processes and frontal lobe
lesion location. Neuropsychologia, 39(8), 771-786.
Sunderland, A., Harris, J. E., & Baddeley, A. D. (1983). Do laboratory tests predict
everyday memory? A neuropsychological study. Journal of Verbal Learning and
Verbal Behavior, 22(3), 341-357.
Trennery, M. R., Crosson, B., DeBoe, J., & Leber, W. R. (1989). Stroop
Neuropsychological Screening Test Manual. Odessa, FL: Psychological
Vanier, M., Mazaux, J. M., Lambert, J., Dassa, C., & Levin, H. S. (2000). Assessment of
neuropsychologic impairments after head injury: interrater reliability and factorial
and criterion validity of the Neurobehavioral Rating Scale-Revised. Archives of
Physical Medecine and Rehabilitation, 81(6), 796-806.
van Zomeren, A. H., & van den Burg, W. (1985). Residual complaints of patients two
years after severe head injury. Journal of Neurology, Neurosurgery, and Psychiatry,
WAIS-III and WMS-III Technical Manual. (1997). San Antonio, TX: The Psychological
Paul J. Seignourel studied mathematics in France and received a Ph.D. in
probability from the University Paris VI and Ecole Polytechnique in 1999. He then
moved to the United States and, after a year of post-baccalaureate studies in psychology,
entered the Department of Clinical and Health Psychology at the University of Florida.