A Behavioral and Electrophysiological Evaluation of Attentional Networks in Parkinson's Disease.

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A Behavioral and Electrophysiological Evaluation of Attentional Networks in Parkinson's Disease.
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english
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Gravano, Jason T
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Master's ( M.S.)
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University of Florida
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Psychology, Clinical and Health Psychology
Committee Chair:
Perlstein, William
Committee Members:
Bowers, Dawn
Pereira, Deidre B
Janicke, David M

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attention -- erp -- parkinson's
Clinical and Health Psychology -- Dissertations, Academic -- UF
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Abstract:
Many individuals with Parkinson's disease (PD) display attentional deficits which are thought to be due to dysfunction of frontal-striatal pathways; however, the nature of these deficits remains unclear. The present study examined the efficiency of three interactive components of attentional processing- alerting, orienting, and executive control (conflict processing)-in 11 PD and 14 neurologically-normal, demographically-matched participants. We hypothesized that PD patients would show selective deficits in the executive aspects of attention. High density scalp-recorded electroencephalogram (EEG) was acquired for transformation into event-related potentials (ERPs) while participants performed the Attention Network Test (ANT). Behaviorally, reaction time (RT) results indicate that PD patients differ from controls in the orienting component of attention, such that PDs benefitted less from spatial cueing. While no significant RT differences were found between groups with the alerting or executive control networks, PD patients committed significantly more errors versus controls on incongruent than congruent trials. ERP data revealed that PD patients do not show the same pattern of P3 amplitude reduction for incongruent trials as controls, which suggests impairment in conflict detection and processing. Interestingly, PDs showed a proportionally larger target N1 for spatially cued targets compared to center, which suggests that while they do not behaviorally benefit from spatial cues as much as controls, their orienting response may be more reflexive. Findings suggest that PD patients show differences in the orienting and executive control of attention and that the ANT may be clinically useful in the characterization of attention deficits in PD.
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by Jason T Gravano.
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Thesis (M.S.)--University of Florida, 2012.
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Adviser: Perlstein, William.
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1 A BEHAVIORAL AND ELECTROPHYSIOLOGICAL EXAMINATION OF ATTENTIONAL By JASON THOMAS GRAVANO 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 20 12

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2 2012 Jason Gravano

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3 ACKNOWLEDGEMENTS I thank my mentor, William Perlstein, Ph.D. for his support and guidance. I wish to acknowledge Chris Sozda a nd David Kaufman, Ph.D., for their tremendous contributions. I would also like to thank my committee, Dawn Bowers, Ph.D., Dave Janicke, Ph.D., and Deidre Pereira, Ph.D. for their constructive feedback. This research was supported by Pre doctoral National I nstitute of Health Fellowship, #T32 AG020499 ( Kaufman), NIH R01 NS050633, t he Michael J. Fox Foundation & t he University of Florida

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4 TABLE OF CONTENTS page ACKNOWLEDGEMENTS ................................ ................................ ............................... 3 LIST OF TABLES ................................ ................................ ................................ ............ 6 LIST OF FIGURES ................................ ................................ ................................ .......... 7 ABSTRACT ................................ ................................ ................................ ..................... 8 CHAPTER 1 INTR ODUCTION ................................ ................................ ................................ .... 10 Statement of the Problem ................................ ................................ ....................... 10 ................................ ............ 10 ................................ ..... 11 Attentional Deficits: a Functional Systems Approach ................................ .............. 13 Alerting ................................ ................................ ................................ ............. 14 Orienting ................................ ................................ ................................ ........... 14 Executive Control ................................ ................................ ............................. 15 Electrophysiological Eva luation of Attention ................................ ........................... 16 N1 ................................ ................................ ................................ ..................... 17 P3 ................................ ................................ ................................ ..................... 18 Summary and Predictions ................................ ................................ ....................... 18 2 METHODS & PROCEDURES ................................ ................................ ................ 22 Attention Network Task ................................ ................................ ........................... 22 Neuropsychological Measures ................................ ................................ ................ 23 Emotional Measures ................................ ................................ ............................... 23 Participants ................................ ................................ ................................ ............. 24 Procedure ................................ ................................ ................................ ............... 25 Electrophysiological Data Acquisition and Reduction ................................ ............. 25 Behavioral Data Analyses ................................ ................................ ....................... 27 ERP Data Ana lyses ................................ ................................ ................................ 27 3 RESULTS ................................ ................................ ................................ ............... 34 ANT Behavioral Performance ................................ ................................ ................. 34 Reaction Time Group x Flanker Type x Cue Type ................................ ........ 34 Reaction Time Attention Network Difference Scores ................................ ..... 34 Error Rates Group x Flanker Type x Cue Type ................................ ............. 35 ERP Components ................................ ................................ ................................ ... 35 Cue locked Target N1 Activity (Alerting: Double Cue vs. No Cue) ................... 35 Cue locked Target N1 Activity (Orienting: Spatial Cue vs. Center Cue) ........... 36

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5 Target P3 Activity (Executive: Incongruent vs. Congruent vs. Neutral) ............ 37 Association Between Attention Network Scores and Other Measures of ................................ ....................... 38 Association Between Attention Network Scores and Measures of Emotion ........... 39 Discussion ................................ ................................ ................................ .............. 40 Limitations and Future Directions ................................ ................................ ........... 44 LIST OF REFERENCES ................................ ................................ ............................... 66 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 72

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6 LIST OF TABLES Table page 2 1 Mean and standard devia tion (SD) demographic and neuropsychological data for PD patients and controls. ................................ ................................ ...... 29 2 2 ............................... 30 3 1 Average attention score network (RT and Z score) as a function of group membership. ................................ ................................ ................................ ....... 48 3 2 Correlations of attention network RTs with measures of executive functioning and proce ssing speed across all participants. ................................ .................... 49 3 3 Correlations of attention network RTs with measures of executive functioning ............................... 50 3 4 chronicity, stage, motor dysfunction, and medication dosage. ........................... 51 3 5 Correlati ons between attention network scores and measures of emotional functioning across all participants. ................................ ................................ ...... 52 3 6 Correlations between attention network scores and measures of emotion disease participants. ................................ ............................. 53

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7 LIST OF FIGURES Figure page 1 1 Anatomy of three attentional networks: alerting, orienting, and executive control. ................................ ................................ ................................ ................ 21 2 1 The attention network test ................................ ................................ .................. 31 2 2 Schematic illustrating the calculation of attention network scores from the attention network test ................................ ................................ ......................... 32 2 3 Posterior electrode sites used in ERP analyses, with internati onal 10 10 system equivalencies ................................ ................................ ......................... 33 3 1 Mean ANT RTs as a function of group, cue type and flanker type ................... 54 3 2 Mean ANT error rates a function of gr oup, cue type, and flanker type ............... 55 3 3 Cue locked gran d averaged ERPs as function of group and cue type in the alerting comparison. ................................ ................................ ........................... 56 3 4 Mean N1 amplitudes as a function of group, cue type, and electrode posi tion in the alerting comparison ................................ ................................ .................. 57 3 5 Cue locked grand averaged ERPs as function of group and cue t ype in the orienting comparison ................................ ................................ .......................... 58 3 6 Mean N1 amplitudes as a function o f group, cue type, and electrode posit ion in the orienting comparison ................................ ................................ ................. 59 3 7 Target locked grand averaged ERPs as a function of group and flanker type in the executive control comparison. ................................ ................................ .. 60 3 8 Mean P3 amplitudes as a function of group, flanker type, and electrode position in t he executive control comparison ................................ ..................... 61 3 9 Correlatio n betwee n alerting RT and Trails A time ................................ ............. 62 3 10 Correlation between orienting RT and Digit Symbol Coding score. .................... 63 3 11 Correlation be tween orientin g RT and Trails B Trails A Time ............................. 64 3 12 Correlation between executive c ontrol RT and WCST total errors ..................... 65

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8 Abstract of Thesis Presented to the Grad uate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science A BEHAVIORAL AND ELECTROPHYSIOLOGICAL EXAMINATION OF ATTENTIONAL By Jason Thomas Grav ano May 2012 Chair: William M. Perlstein Major: Psychology are thought to be due to dysfunction of frontal striatal pathways; however, the nature of these deficits remains unclear. The present study examined the efficiency of three interactive components of attentional processing alerting, orienting, and executive control (conflict processing) in 11 PD and 14 neurologically normal, demographically matched participants. We h ypothesized that PD patients would show selective deficits in the executive aspects of attention. High density scalp recorded electroencephalogram (EEG) was acquired for transformation into event related potentials (ERPs) while participants performed the A ttention Network Test (ANT). Behaviorally, reaction time (RT) results indicate that PD patients differ from controls in the orienting component of attention, such that PDs benefitted less from spatial cueing. While no significant RT differences were found between groups with the alerting or executive control networks, PD patients committed significantly more errors versus controls on incongruent than congruent trials. ERP data revealed that PD patients do not show the same pattern of P3 amplitude reduction for incongruent trials as controls, which suggests impairment in

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9 conflict detection and processing. Interestingly, PDs showed a proportionally larger target N1 for spatially cued targets compared to center, which suggests that while they do not behaviorall y benefit from spatial cues as much as controls, their orienting response may be more reflexive. Findings suggest that PD patients show differences in the orienting and executive control of attention and that the ANT may be clinically useful in the charact erization of attention deficits in PD.

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10 CHAPTER 1 INTRODUCTION Statement of the Problem approximately 1 million people in the United States and 5 million worldwide (Olanow, Ster n, & Sethi, 2009). Currently, it is the second most common neurological disorder diagnosed and the cost of treatment of individuals with PD in the US is in excess of $10.8 billion annually ( O'Brien, Ward, Michels, Tzivelekis, & Brandt, 2009 ). While Parkin may further affect their ability to perform everyday tasks and for some may eventually progre ss into dementia (Cummings 19 8 8 ; Aarsland, Bronnick, Larsen, Tysnes, & Alves, 2009 ). Indeed, the National Institute of Health recognized the importance of cognitive and behavioral dysfunction in PD and acknowledged the relative lack of knowledge in this a rea in both clinical and pre clinical stages in its 2006 statement on PD research planning. Furthermore, current treatments of the disease that are often targeted toward motor symptoms have mixed results regarding cognitive dysfunctions ( Schneider, Elm, Pa rashos, Ravina, & Galpern, 2010 ). D isease: Pathophysiology and Cognition to the proposed dysfunction of multiple brain networks, or loops, that reciprocally con nect the basal ganglia to the frontal lobe ( Alexander, DeLong, & Strick, 1986 ) This dysfunction is thought to be associated with the loss of dopamine producing cells in the substantia nigra. This loss of dopamine in the frontal lobes has been linked to de ficits in

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11 so called executive functions, or higher order supervisory cognitive abilities such as maintaining or switching mental set planning, and self monitoring (Raskin, Borod, & Tweedy, 1990; Dubois & Pillon, 1997) The decline of these abilities in PD patients and their link to the frontal lobe has led some to conclude that to some extent, the d ys regulation of frontal control of attention contributes to cognitive dysfunctions seen in PD ( Stam et al., 1993 ); however, other pathological mechanisms of co gnitive dysfunction in addition to dopamine loss have been proposed The degradation of several neurotransmitter systems (e.g., cholinergic, serotonic, and norepineprine) have been reported in PD and postulated to be related to cognitive impairments and d ementia (Dubois & Pillon, 1997). Specifically, the degradation of the cholinergic neurotransmitter system, which is thought to affect the entire cortex, has been linked to cognitive dysfunctions in PD and other neurodegenerative diseases (Perry et al., 198 5). While primarily associated with functions such as memory, acytelcholine has also been implicated in other types of cognitive functions. For example, Bohnen et al. (2006) linked the neurotransmitter acytelcholine to executive and attention functioning i n PD as measured by simple digit span. In the subset of individuals with PD who develop dementia for which cumulative incidence may be as high as 80% (Aarsland et al., 2003) attentional dysfunctio n has activities necessary for safe and independent living ( Bronnick et al., 2006 ). Furthermore, some authors have argued that there may be interactive effects of attentional dysfunction and motor symptoms. Specifically, McDowell and Harris (1997) suggested that overactive attentional orienting to exogenous stimuli may contribute to

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12 In addition, several strateg ies toward helping motor functioning (e.g., postural control, gait) may rely to some extent on intact attentional functioning ( Woollacott & Shumway Cook, 2002 ). Even slight attentional disturbances in the early disease state may be consequential. Taylor et al. (2008) found that subtle deficits of attention predicted future general cognitive decline (as, for example on the Mini Mental Status Exam score, MMSE) three years later independent of motor subtype. The measure of attention used by Taylor et al. (200 8) was a composite Power of Attention score derived from simple mean reaction times (RT) to different subtests (choice RT, simple RT, digit vigilance RT) of the Cognitive Drug Research computerized assessment. The potential for the early identification of those who are at risk of future cognitive decline as well as increased knowledge about the neural bases of these dysfunctions has many implications for future study and treatment. In sum, further characterization of attention deficits is needed to best und erstand pathological processes at work and to guide efforts at remediation. Several studies have demonstrated deficits of attention in PD ( Raskin, Borod, & Tweedy, 1990 ) ; however, to what extent and in what ways attention is affected in the disease is open for debate (Hirsch & Rhrle, 2011). Most recently, Sampaio et al. (2011) reported visuospatial attention dysfunction when accounting for visual acuity. In the context of cueing paradigms, the results are somewhat mixed. Generally speaking, cueing paradigm s employ short duration stimuli (e.g., auditory, visual, tactile) to relate the temporal or spatial characteristics of impending target stimuli and have been used experimentally to examine attention abilities of humans and animals in a variety of

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13 contexts. Early investigat ions found normal target facilitation through cues, a finding supported by more recent studies (Poliakoff et al., 2003); though, Yamada, Izyuuinn, Schulzer, and Hirayama ( 1990 ) reported no cueing effect in more impaired PD patients, which suggests attention impairment. One possibility for conflicting or poorly characterized deficits may be the variability in operational definitions of attention. We seek to clarify what attention deficits exist in PD by using the Attention Network Task a c ueing paradigm combined with the classic Erikson Flanker test which purports to assess interdependent components of attention in a single experimental session ( Fan, McCandliss, Sommers, Raz, & Posner, 2002 ). This task is based on a theoretical model that a ttention is composed of three distinct functions: alerting the ability to activate and maintain an alert state, orienting the ability to move attention in space, and executive control the ability to selectively act on stimuli while suppressing competing alternate responses. By measuring these distinct functions of attention, we may better characterize the nature of attentional functioning in PD. Attentional Deficits: a F unctional S ystems A pproach One theoretical model of attention proposed by Posner and colle a g ue s (e.g., Posner & Fan, 2004) maintains that attention is not a unitary construct, but a system that is composed of three component processes: achieving and maintaining an alert state, orienting to stimuli, and monitoring for and selecting betwee n conflicting information. These subcomponents of attention have been labeled alerting, orienting, and executive control respectively. They are thought to be instantiated in different anatomical systems and rely upon separate neurotransmitter systems as described below Thus, in order to gain a detailed understanding of the nature of attentional

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14 deficits in PD, we chose to use this model allowing us to investigate the relative changes in theoretically orthogonal yet interactive, attentional sub processes Alerting Alerting is defined as the ability, through physiological arousal, to increase response readiness to an impending stimulus. Behaviorally, modulations of alertness can be examined by measuring improved processing (e.g., faster RT or improved per formance accuracy ) of a target when it is preceded by a temporally informative cue. The neural centers supporting this mechanism are distributed in the thalamus, posterior parietal lobe, and frontal lobe (Figure 1 1), while t he neurotransmitter thought to be primarily responsible for mediating this function is norepinephrine (Posner & Fan, 2004) B ehavioral studies have shown that PD patients benefit similarly in reaction time to target stimuli (compared to controls) when given exogenous alerting cues, whi ch suggests that PD patient s show intact phasic arousal ( Heilman, Bowers, Watson, & Greer, 1976 ) In contrast, Vieregge, Verleger, Wascher, Stiiven, and K mpf ( 1994 ) argued that norepinephrine depletion due to dysfunction of the locus coruleus may explain attentional processing differences in PD (and thus indices of attention would be independent of dopaminergic state). Orienting Orienting refers to efficiently shifting the focus of preferential processing (e.g., attention) to a specific spatial location. The efficiency of attentional orienting can be assessed by measuring improved processing of a target when it is preceded by a spatially informative cue. Neural areas involved in orienting are the superior parietal lobe, temporal parietal junction, frontal eye fields, and superior colliculus (Figure 1 1) The primary neurotransmitter of this system is acetycholine (Posner & Fan, 2004).

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15 With regard to orienting in PD, the primary findings have been quicker more reflexive, orienting to environmental stimuli ( Briand, Hening, Poizner, & Sereno, 2001 ) and reduced costs when shifting attention to an unexpected location. Indeed, in certain circumstances PD patients show quicker reaction times to stimuli presented in unexpected locations (Sharpe 1990; Wright, Bur ns, Geffen, & Geffen, 1990 ), which has been thought to show either a dysfunction of maintenance of attention in that location, or a dysfunction of the attentional inhibition of the surround ( Filoteo et al., 1997 ). Despite showing reduced costs to incorrect ly cued targets, PD patients seem to benefit similarly from spatial cues; however, many of these studies used invalid cueing as well, which presents a potential confound and makes interpretation difficult Interestingly, as previously mentioned, the cholin ergic system (which supports orienting) is thought to be dysfunctional in PD. Furthermore, cognitive symptoms and incident dementia in PD have been linked to these cholinergic systems (Emre, 2003). Executive Control It has been proposed that the executive control network is the control circuitry of Regard ing neuroanatomical instantiation, t he anterior cingulate cortex (ACC) is thought to support monitor ing of conflict elicite d by competing responses (e.g., van Veen & Carter, 2002 ). In addition, the dorsolateral prefrontal cortex (DLPFC) is thought to maintain selective sensory bias in working memory, thereby facilitating or suppressing visual stimuli via dorsal (where) and ven tral (what) pathways ( Hillyard & Anllo Vento, 1998 ). The primary neurotransmitter associated with these functions is dopamine (Posner & Fan, 2004; Figure 1 1) Behaviorally, flanker paradigms have been used to illicit competition between responses. In bri ef, flanker paradigms require a behavioral

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16 response to a specific stimulus (often a directional arrow) while that stimuli is surrounded by other similar stimuli that are either congruent ( e.g., the same direction/response ) or incongruent ( e.g., an alternat ive direction/ response). In the ANT correct responding requires action on the central arrow, while suppressing competing alternative responses (arrows on either side of the central arrow). In this paradigm, the ACC is thought to be evoked by the presentat ion incongruent flankers ( Neuhaus et al., 2007 ; 2010 ). This component of attention e ffectively dealing with conflicting information toward ac tion h as been shown to be i mpaired in individuals with PD (e.g., Wylie et al., 2009 ) and is thought to be directly related to pathological processes in PD Specifically, two of the fronto striatal loop systems outlined by Alexander, DeLong, and Strick (1986) that are thought to be dysfunctional in PD involve the ACC and DLPFC. Interestingly, the neural structures inv olved in attentional conflict resolution, primarily the ACC, have also been implicated as possible sites of dysfunction with regard to emotional disturbance (e.g., depression, anxiety, apathy) as well ( Bush, Luu, & Posner 2000 ). Electrop hysiological E valu ation of A ttention the relationship between neural activity cognitive processes. Electroencephalography (EEG) is a non invasive technique used to record volume conducted el ectrical activity of the brain on the scalp by electrodes. When EEG is averaged over many time locked stimulus presentations, the random signal is reduced, and reliable deflections in voltage e so called component deflections and are thought to reflect the neural response to a stimulus response or cognitive event (event related potentials ERPs).

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17 Thus, i n addition to obtaining behavioral response data, scalp recorded brain event related poten tials (ERPs) were recorded in order to obtain real time ms X ms less dependent on overt motor responses which is an important consideration in evaluating cognition in disorders in which motor responding is affected such as PD. The visual stimulus locked ERP waveform consists of several reliable, well validated components: C1 (50 90ms post stimulus), P1 (80 130ms), and N1 (140 200ms), with spatial /selective attention modulating the amplitude of P1 and N1 components ( Hillyard & Anllo Vento, 1998 ). For example, P1 and N1 amplitudes are larger for stimuli that appear in attended locations (versus unattended) and when targets are preceded by spatially informative cues. Changes in P1 have been observ ed in PD; however the degree to which these changes are based on retinal damage, primary sensory dysfunction or attention dysfunction is unclear ( O'Donnell, Squires, Martz, Chen, & Phay, 1987 ; Ebmeier et al., 1992 ). Another ERP component associated with attention functioning is the P3. P3 is a deflection that appears in varied cognitive tasks (Polich, 2007), but there is evidence to suggest that the P3 amplitude may be sensitive to ACC mediated executive control (Neuhaus et al., 2007; 2010). N1 The visual N1 has been shown to be sensitive to modulations of attention, and likely reflects the enhancement of task relevant sensory information that is used for perceptual judgments ( Hillyard & Anllo Vento, 1998 ). Its distribution on the scalp is over frontal, pa rietal, and occipital regions and its specific neural generator is poorly defined ( Hillyard & Anllo Vento, 1998 ). A recent study using the ANT reported that efficient alerting and orienting resulted in significant increases in cue locked target N1 (Neuhaus

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18 et al., 2010) Thus, the N1 component may be a sensitive marker of dysfunctions in both alerting and orienting processes. P3 A P3 component (often called P3b to differentiate it from the novelty P3a) is elicited by task relevant stimuli under conditions of active attention and its latency is determined by stimulus evaluation time ( Polich, 2007; Tachibana, Toda, & Gugita, 1992 ). Thus, the dynamics of the P3, which is the neural response thought to reflect stimulus evaluation and categorization, appears to be affected by attentional functioning. In the context of the ANT, changes in P3 amplitude in incongruent versus congruent conditions likely reflect ACC mediated conflict detection and/or resolution process Thus, the P3 component is thought to be sensitiv e to disruptions in the executive network. Summary and Predictions attentional dysfunction, but the nature of these deficits is unclear. We seek to better characterize attentional def icits by examining the efficiency of three subcomponents of attention: alerting, orienting, and executive control. Bennett and Castiello (1996) argue that the basal ganglia may mediate attentional processes in both executive and orienting networks and thus explain some attentional dysfunctions seen in PD Anatomically, the basal ganglia are well placed to influence the executive and orienting attention networks. Specifically, o utput pathways from the substantia nigra and globus pallidus project to the thala mus, which in turn project to the posterior parietal cortex (orienting) as well as the anterior cingluate cortex and dorsolateral prefrontal cortex (executive control ). In addition, postulated changes in norepinephnrine in PD may

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19 affect alerting. We aim t o measure the efficiency of three attentional components a lerting, orienting, and executive control within the same experimental participants in the context of a single experimental paradigm to determine (1) if there is disproportionate impairment in one o r more of these processes in PD and (2) if these attention network processes relate to other cognitive abilities, emotional functioning, or disease state. While this second aim is more exploratory, it serves to provide a basis on which further hypothesis r egarding the impact of attentional functioning may be generated. The Attention Network Test (ANT) was developed as a brief instrument capable of quantifying the efficiency of the attentional subsystems proposed by Posner and colleagues (Posner & Fan, 2004; Fan et al., 2002) Moreover, the ANT has been found to reliably assay the three attentional networks in studies employing behavioral (e.g., Fan et al., 2002), electrophysiological (e.g., Fan et al., 2007; Neuhaus et al., 2007), and hemodynamic (e.g., Fan, McCandliss, Fossella, Flombaum, & Posner, 2005; Posner, Sheese, Odludas, & Tang, 2006) methodologies. Aim 1. Establish whether there is disproportionate dysfunction of one or more of the attentional component processes in non demented PD. Hypothesis 1. Current evidence suggests that executive control of attention, as it is mediated by structures and neuro transmitters most clearly associated with PD dysfunction (e.g., prefrontal areas, ACC, dopamine) will be disproportionately impaired. This impairment w as predicted to evident behaviorally by disproportionately increased RT and error rate to incongruent (vs. congruent) targets. In addition, while controls are expected to show attenuated P3 amplitudes to incongruent targets (vs. congruent)

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20 reflecting intac t neural conflict processing, PD patients are predicted to show disproportionately less attenuation of P3 amplitude to incongruent targets consistent with executive network dysfunction reflective of impaired conflict processing. Regarding the efficiency of orienting and alerting networks, previous findings suggest that PD patients will show proportional RT benefit to targets following temporally and spatially informative cues compared to controls. In addition, PD patients are expected to show proportional target N1 amplitude increases, reflecting similar allocation of attentional resources, in both the alerting and orienting comparisons compared to controls. Aim 2. In a series of exploratory correlations, for future hypothesis generation, we will i nvestigat e and evaluate the extent to which changes in attentional network systems relate to other cognitive /executive dysfunctions emotional disturbance, motor symptoms, and disease state (specifically duration with symptoms, levodopa equivalent dosage, and Hoehn Yahr stage). Hypothesis 2. Executive control of attention will significantly correlate with executive, affective, and motor disturbance. While this hypothesis is preliminary, it is supported by the proposed dysfunction of the parallel neural circuits conn ecting the basal ganglia to the frontal lobe in PD, which have diverse cognitive, affective, and motor functions. We also expect that variations in alerting and orienting will correlate with neuropsychological measures that emphasize processing speed, such that those that are more efficient in alerting or orienting will have faster completion times on measures of processing speed.

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21 Figure 1 1. Anatomy of three attentional networks: alerting, orienting, and executive control. Adapted from Posner and Roth bart (2007).

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22 CHAPTER 2 METHODS & PROCEDURES Attention Network Task All participants completed a computerized task identical to that of Fan et al. (2002). The task is summarized in Figure 2 1. Stimuli were presented using E Prime (v.1.0, Psychology Softwa re tools, Inc.) at a 2.18 horizontal and 1.45 vertical maximum visual angle. Participants were instructed to focus on a central fixation cross and determine and respond to the direction of the target probe, the central arrow (left or right). Speed and ac curacy were emphasized. Target probes appeared in two locations (above or below fixation), were accompanied by congruent or incongruent flankers in 67% of trials, and were preceded by cues in 75% of trials. Moreover, t he task utilized 2 target locations ( above or below central fixation), 2 target directions (left or right), 4 cue conditions (no cue, center cue, double cue and spatial cue), and 3 flanker conditions (congruent, incongruent, or neutral), yielding 48 different types of trials. Each trial last ed ~4 seconds and consisted of five events: 1) random variable pre cue fixation (400 1600 ms), 2) warning cue presentation (100 ms), 3) post cue fixation (400 ms), 4) target and flanker presentation (self terminating up to 1700 ms), and 5) post target fixa tion (3500 ms minus duration of pre cue fixation minus RT). Participants completed a 24 trial practice block, followed by 3 experimental blocks of 96 pseudo random trials (2 target locations x 2 target directions x 2 repetitions x 3 flanker conditions x 4 cue conditions). Accuracy and RT feedback were only provided to participants during the practice block The test retest reliability of this measure has been documented as .77 in the executive network, .61 in the orienting network, and .52 in the alerting network (Fan et al., 2002).

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23 Neuropsychological M easures Participants were administered a brief battery of neuropsychological tests to assess executive functioning. They were screened for dementia and other global cognitive problems using the Mini Mental State Exam (MMSE; M. F. Folstein, Folstein, & McHugh, 1975 ). In addition, participants completed the Trail Making Test A and B (Trails; Reitan & Wolfson, 1995) to assess psychomotor speed and cognitive flexibility, respectively. The Digit Symbol test ( WAIS III; Wechsler, 1997 ) was used to assess psychomotor speed and complex sustained attention. Lastly, the Wisconsin Card Sorting Test (Heaton, Chelune, Talley, Kay, & Curtiss, 1993) was used to assess abstract problem solving and set shifting ( Lezak, Howieso n, & Loring, 2004) Emotional Measures Depression, anxiety, and apathy are common psychiatric symptoms experienced by PD patients (Lieberman, 2006). Thus, participants completed several self report questionnaires of emotional functioning. The State Trait Anxiety Inventory (STAI; Speilberger, Gorusch, Luschene, Vagg, & Jacobs, 1983) was used to assess for symptoms of anxiety and anxious symptoms during the evaluation. The Beck Depression Inventory Second Edition (BDI II; Beck, 1996) and the Geriatric Depre ssion Scale (GDS; Yesavage et al., 1983) were used to assess for symptoms of depression. The GDS was normed on an elderly population and may be a more valid measure of depressive symptoms in this group because, unlike the BDI II, it does not rely on somati c complaints (Blazer, 2002). Lastly, a modified version of the Apathy Evaluation Scale (AES; Starkstein et al., 1992 ) was used to assess for the presence of self reported apathy.

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24 Participants Participants used in analyses were eleven patients with idiopat disease recruited through the Movement Disorders Center of the University of Florida and fourteen non affected controls recruited from the community. Original recruitment for the larger study included 15 PD patients and 16 controls; however three PD patients and two controls were excluded due to unusable EEG data (due to too much muscle induced artifact that could not be reliably filtered out) and one PD patient for the D medications). Control volunteers were screened for the presence of psychiatric illness, learning disability, or history of neurological disease or head injury via verbal self report and demographically matched to disease patients met diagnostic criteria for PD and were free from dementia and other medical illnesses known to affect cognition. The clinical criteria for PD was presence of at least two of the four cardinal motor features ( akinesia, bradykinesia, resti ng tremor, rigidity; Hughes, Ben Shlomo, Daniel, & Lees, 1992) and a history of therapeutic response to dopamine replacement therapy as measured by improvement in motor symptoms on the United Parkinson Disease Rating Scale Third Edition (UPDRS; Fahn & Elto n, 1 987) Available demographic emotional, and neuropsychological data for the participants is presented in Table 2 1 Patients received standard measures for staging their motor symptoms and disease course, including the motor subscale of the UPDRS (on m edication) and a modified Hoehn Yahr scale (Hoehn & Yahr, 1967). Of the eleven PD patients, five received Hoehn Yahr scores of 2, three were scored as 3, one was a 4, and two were unscored. In addition, two of the PD patients reported previous deep brain s timulation

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25 treatment and two reported taking antidepressants. Available PD patient characteristics are displayed in Table 2 2. Procedure After obtaining informed consent, participants completed neuropsychological and emotional measures, then completed seve ral computer based tasks (including the ANT) while EEG was recorded. Control participants completed the experimental procedures course of two days to reduce fatigue. Contr ols were compensated $10 per hour of participation. Measures of disease state and motor symptoms (e.g., UPDRS, Hoehn Yahr, Levodopa Equivalent Dosage) were obtained from medical records of assessments at the Movement Disorders Center within one calendar ye ar of the experiment. Electrophysiological Data Acquisition and Reduction Electroencephalogram (EEG) was recorded from 64 scalp sites using a geodesic sensor net and Electrical Geodesics, Inc., (EGI; Eugene, Oregon) amplifier system (20K gain, nominal band pass = .10 100 Hz). Reported electrode sites have been renamed from the 64 channel geodesic sensor net to conform to the international 10 10 positions (Figure 2 3) Electrode placements enabled recording vertical and horizontal eye movements reflecting el ectro oculographic (EOG) activity. EEG was digitized continuously at 250 Hz with a 16 bit analog to digital converter and referenced to Cz. A right posterior electrode served as common ground, and electrode impedances were mai electromyographic muscle artifact, electro ocular eye movement, and blink artifacts using computer algorithms implemented in Brain Electrical Source Analysis software

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26 (BESA ver sion 5.1; Scherg, 1990). EEG activity was excluded from the remaining data using threshold criteria that maximized the number of trials accepted from each individual. The average voltage threshold used for excluding trials was 115.20 SD : 16.86 range: 100 150 for target locked data and 113.40 (SD: 16.38 range: 100 150) which did not significantly differ between groups ( Point to point Individual subject event related potentials (ERPs ) were separately extracted and averaged together from the continuous EEG recording in discrete temporal windows coinciding with each stimulus onset for cue locked (center, double, spatial, and no cue) and target locked (congruent, incongruent, and neutral ) conditions. Epoch duration of cue locked epochs lasted 1600 ms (300 ms pre cue to 800 ms post probe including 400 ms cue offset probe onset interval); target locked epochs were extracted with duration of 200ms pre and 1200 ms post target probe presentat ion. All averaged ERP epochs were digitally filtered at 30 Hz low pass, high pass filtered at 1.6 Hz (cue locked) or .53 Hz (target locked), and baseline corrected using respective pre stimulus windows. Peak voltage values for cue locked N1 amplitude wer e measured bilaterally over posterior parietal scalp sites (e.g., 10 10 system equivalents = P03, P04 PO7, PO8) between 148 248 ms post target onset. Target locked ERPs were scored such that peak amplitude of the P3 component was measured from 300 600 ms at central posterior electrode sites (e.g., 10 10 equivalents = CPz, Pz, and POz). The scoring windows for each group were determined by identifying the maximum peak amplitude of P3 within grand averaged waveforms for each group.

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27 Behavioral Data Analyses Median correct trial RT s (Ratcliff, 1993) and error rates excluding non responses (Neter, Wasserman, & Kutner, 1985) were analyzed separately using 2 Group (PD, Controls) x 3 Flanker type (incongruent, neutral, congruent) x 4 Cue type (no, spatial, double and center) mixed model restricted maximum likelihood analyses of variance (REML ANOVAs; Wolfinger, Tobias, & Sall, 1994). A ttention network RT effects were calculated using the following cognitive subtractions: alerting effect = no cue RT minus double c ue RT; orienting effect = center cue RT minus spatial cue RT; executive control effect = incongruent RT minus congruent RT (Fan et al., 2002) Calculation of attention network (difference) scores for RT and accuracy are illustrated in Figure 2 2. Attention network RT difference scores were analyzed using one way mixed model REML ANOVAs. Additionally, to examine whether network RT effects were artificially created due to generalized slowing experienced by PD patients, we recalculated network scores using z transformed condition RTs. Specifically, we calculated a z score transformation condition RT by taking the mean over all conditions for a given individual, subtracting his/her condition mean from the overall mean, and dividing by the overall standard deviation across the overall mean (Bush et al., 1993; Faust et al., d effect sizes (Cohen, 1988) were calculated using pooled standard deviations for group and/or c ondition related effects. ERP Data Analyses A ttention network effects were analyzed using the following cognitive comparisons: alerting effect = no cue amplitude vs. double cue amplitude; orienting effect = center cue amplitude vs. spatial cue amplitude; e xecutive control effect =

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28 incongruent amplitude vs. congruent amplitude. For analysis of attention network ERP activity, REML ANOVAs included the factors group, channel ( cue locked analyses = 10 10 equivalents PO3, PO4, PO7, PO8; target locked analyses = 10 10 equivalents CPz, Pz, and POz), and condition (either double cue and no cue, spatial cue and center cue, or congruent target and incongruent target depending on the attention network being analyzed). Selection of electrode sites for analyses of elec trophysiological data was based on prior findings indicating modulations of interest over parieto occipital sites for cue locked data (e.g., N1, Neuhaus et al., 2010) and posterior parietal sites for target locked effects (e.g., P3, Neuhaus et al., 2007), as well as evaluation of the scalp distribution maps of the present data set which indicated increased N1 and P3 amplitudes over these regions. Electrode locations are presented in Figure 2 3.

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29 Table 2 1. Mean and standard deviation (SD) demographic and n europsychological data for PD patients and controls. Control N Mean (SD) N Mean (SD) Demographics Age 11 61.81 8.99 14 63.86 8.02 Education 11 13.91 3.73 14 16.42 2.85 Female (%) 27.27 50.00 Cognitive Functioning MMSE 11 29.09 1.04 14 28.93 0.92 Digit Symbol Coding** 11 51.27 15.47 14 73.86 10.26 Trails A 11 42.27 15.07 14 32.43 10.11 Trails B 11 113.18 69.34 14 72.93 28.00 WCST Categories** 11 4.00 1.90 14 5.71 1.07 WCST Total Errors 9 33. 44 15.96 14 19.57 15.95 WCST Perseverative Errors 9 18.78 8.63 14 11.07 9.68 WCST Failure to Maintain Set 8 1.38 1.69 14 0.50 0.65 Emotional Functioning BDI II** 11 12.36 7.83 14 2.93 3.24 GDS* 11 6.00 7.69 14 0.71 1.27 AES 11 10.64 8 .03 14 8.79 4.74 STAI Trait* 10 40.20 12.20 14 28.14 5.32 STAI State* 10 37.10 9.98 14 26.86 7.37 *p<.05, **p<.01

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30 Table 2 N Mean (SD) Minimum Maximum Hoehn Yahr Stage 9 2.56 0.73 2 4 UPDRS Motor 11 23.82 13.21 8 53 Levodopa Equivalent Dose 10 932.33 623.74 100 1965 Months with Symptoms 11 125.00 36.42 69 125

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31 Figure 2 1. The attention network test: (a) The four cue conditions ; (b) The six stimuli used as targets in the present experiment ; (c) An example sample trial (spatial cue incongruent target stimuli) Adapted from Fan et al., (2002).

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32 Figure 2 2. Schematic illustrating the calculation of attention network scores from the attention network test. Top row: Alerting = No Cue minus Double Cue; Middle row: Orienting = Center cue minus Spatial cue; Bottom row: Executive = Incongruent target minus Congruent target.

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33 Figure 2 3. Posterior electrode sites used in ERP analyses, with international 10 10 system equivalencies. S ites of interest include PO7, PO3, PO8, and PO4 (alerting and orienting comparisons) and CPz, Pz, and POz (executive control comparison).

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34 CHAPTER 3 RESULTS ANT Behavioral Performance Reaction Time Group x Flanker Type x Cue Type A 2 Group X 2 Flanker t ype X 4 Cue type REML ANOVA on correct trial median RTs revealed a main effect of Group F ( 1,23)=8.56, p < 0 .01, such that PD patients demonstrated generalized slowing. There was also a main effect of Flanker type, F ( 2,253)=303.91, p < 0 .0001, such that partici pants were slower to respond to targets with incongruent flankers than with congruent flankers. Lastly, there was a main effect of Cue type F ( 3,253)=25.09, p < 0 .0001, which indicated that participants were significantly faster in responding to targets after receiving a spatial cue relative to other cue conditions. Group X Flanker type F ( 2,253)=2.83, p =0.06, Group X Cue type F ( 3,253)=0.52, p =0.67, Group X Flanker Type X Cue Type F ( 6,253)=0.61, p =0.72, and Flanker type X Cue type F ( 6,253)=0.76, p =0.60 inte ractions were not significant. Mean RTs as a function of G roup, Cue type, and Flanker type are summarized in Figure 3 1 Reaction Time Attention Network Difference Scores Separate one way REML ANOVA s assess ed group differences in each of the three attent ional networks. Controls and PD patients did not significantly differ in executive F ( 1,23)=1.10, p= 0.31, d =0.41 or alerting F ( 1,23)=0.09, p= 0.76, d =0.12 comparisons; however, controls showed significantly more efficient orienting than PD patients F ( 1, 23)=6.45, p< 0 .05, d =0.99, an effect that remained after controlling for generalized slowing F ( 1,23)=5.08, p< 0.05, d =0.89. Mean network RTs and Z transformed scores are summarized in Table 3 1

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35 Error Rates Group x Flanker Type x Cue Type Regarding respo nse accuracy, a 2 Group X 2 Flanker type X 4 Cue type REML ANOVA on mean error rates excluding non responses revealed a main effect of Group, F ( 1,23)=5.19, p< 0 .05, such that PD patients made more errors overall. There was a main effect of Flanker type, F ( 2 ,253)=37.35, p< 0.0001, such that participants made more errors when targets were surrounded by incongruent than congruent flankers. These main effects were m oderated by the presence of a significant Group X Flanker type interaction, F ( 2,253)=14.61, p< 0.00 01, indicating that PD patients made disproportionately more errors in response to incongruently flanked targets compared to controls. There was no significant effect of Cue type F ( 3,253)=1.18, p< 0 .32 nor significant Flanker type X Cue type F ( 6,253)=0.5 5, p= 0.77, Group X Cue F ( 3,253)=1.10, p= 0.35, or Group X Flanker type X Cue type F ( 6,253)=1.13, p= 0.35 interactions with regard to error rate. Mean error rates as a function of Group, Flanker type, and Cue type are summarized in Figure 3 2 ERP Component s Cue locked Target N1 A ctivity ( A lerting: D ouble C ue vs. N o C ue) Subject grand averages for the double cue condition were based on an average of 64.57 3.78 segmented sweeps for controls and 59.73 7.25 segmented sweeps for PD patients, which differed s ignificantly between groups t ( 23)=2.16, p= 0.04 While the groups differed in raw trials accepted, this was due to controls making more correct responses and not to differences in the percentage of trials accepted after artifact rejection, t ( 23)= 0.65, p= 0 .52. Grand averages for the no cue condition were based on an average of 63.07 5.06 segmented sweeps for controls and 60.09 7.54 segmented sweeps for PD patients, which did not differ by group, t ( 23)=1.18, p= 0.25. A

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36 2 Group X 4 Cue type X 4 Channel R EML ANOVA on target N1 ERP amplitudes revealed a main effect of Cue type, F ( 1,161)=14.57, p< 0.001, such that double cues, relative to no cue, produced greater target N1 amplitude. There was a main effect of Channel F ( 3,161)=11.64, p< 0.0001, which indicate d maximal negativity at a left hemisphere posterior site ( PO7 ). There was no significant effect of Group F ( 1,23)=1.84, p= 0 .19, nor significant Group X Cue type, F ( 1,161)=0.41, Group X Channel F ( 3,161)=0.42, p= 0.74, Cue type X Channel F ( 3,161)=2.38, p= 0 .07, or Group X Cue type X Channel F ( 3,161)=0.24, p= 0.87 interactions. Grand averaged ERPs as a function of group and Cue type are displayed in Figure 3 3 and m ean peak N1 amplitudes are presented in Figure 3 4 Cue locked Target N1 A ctivity ( O rienting: S patial C ue vs. C enter C ue) Subject grand averages for the spatial cue condition were based on an average of 65.21 3.42 segmented sweeps for controls and 60.45 7.29 segmented sweeps for PD patients, which differed significantly t ( 23)=2.17, p= 0.04 betwe en groups; however, the percent of excluded trials did not differ by group, t ( 23)=0.32, p= 0.75. Grand averages for the center cue condition were based on an average of 64.50 4.63 segmented sweeps for controls and 61.64 5.54 segmented sweeps for PD pat ients, which did not differ by group, t ( 23)=1.41, p= 0.17. The analysis revealed a main effect of Cue type, F ( 1,161)=37.13, p< 0 .0001, such that spatial cues, relative to center cues, produced greater target N1 amplitude. This main effect was moderated by t he presence of a significant Group X Cue type interaction F ( 1,161)=4.24, p< 0 .05, demonstrating that PD patients showed disproportionately greater spatial cueing effects in terms of target N1 amplitude. There was also a main effect of Channel, F ( 3,161)=14. 27, p< 0 .0001, which indicated maximal negativity at a left hemisphere

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37 posterior site ( PO7 ). Group ( F ( 1,23)=1.41, p= 0.25), Group X Channel F ( 3,161)=0.22, p= 0.89, Cue X Channel F ( 3,161)=0.89, p= 0 .45, and Group X Cue type X Channel F ( 3,161)=0.07, p= 0.98 in teraction effects were not significant. Grand averaged ERPs as a function of group and Cue type are displayed in Figure 3 5 Mean condition N1 amplitudes are presented in Figure 3 6 Target P3 A ctivity ( E xecutive: I ncongruent vs. C ongruent vs. N eutral) Gra nd averages for the congruent condition were based on an average of 82.796.08 segmented sweeps for controls and 78.91 10.39 segmented sweeps for PD patients, which did not differ by group, t ( 23)=1.17, p= 0.26. Grand averages for the neutral condition wer e based on an average of 80.21 7.24 segmented sweeps for controls and 75.45 11.33 segmented sweeps for PD patients, which did not significantly differ, t ( 23)=1.28, p= 0.21. Grand averages for the incongruent condition were based on an average of 81.00 6.71 segmented sweeps for controls and 70.55 19.76 segmented sweeps for PD patients, which also did not significantly differ, t ( 23)=1.86, p= 0.08. The analysis revealed a significant main effect to Flanker type, F ( 2,184)=13.55, p< 0 .001, such that incongr uently flanked targets produced attenuated P3 amplitudes relative to neutral or congruently flanked targets. This effect was moderated by the presence of a significant Group X Flanker type interaction, F ( 2,184)=3.14, p< 0 .05, such that only controls showed significant attenuation in P3 amplitude during incongruently flanked trials. There was also a significant Group X Channel interaction, F ( 4,184)=10.22, p< 0.0001, such that amplitudes were more negative in PD patients at the most posterior site ( Pz ). There was no significant effect of Channel F ( 2,184)=0.47, p= 0.63 or Group F ( 1,23)=0.28, p= 0 .60, nor significant Flanker type X Channel

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38 F ( 4,184)=1.29, p= 0.27, or Group X Flanker type X Channel F ( 4,184)=0.17, p= 0.95 interactions. Grand averaged ERPs as a f unction of Group and Flanker type are summarized in Figure 3 7 Mean peak P3 amplitudes are presented in Figure 3 8 Association B etween A ttention N etwork S cores and O ther M easures of C ognition D isease S everity Correlations between attentio n network scores and neuropsychological measures over all participants are summarized in Table 3 2 B oo t strapped correlations were used to confirm significance of simple Pearson correlations by providing more robust estimates of standard errors. Briefly, i ndividuals who were more efficient in orienting tended to have higher Digit Symbol Coding scores r ( 25)=0.46, p< 0.05 (Figure 3 10), and faster Trails B time, r ( 25)= 0.37, p< 0 .05. An additional measure thought to better isolate the executive components of the task (Trails B time minus Trails A time) had a similar relationship to orienting scores r ( 25)= 0.39, p< 0 .05 (Figure 3 11) Individuals who were more efficient in alerting tended to have faster Trails A times r ( 25)= 0.40, p< 0 .05 (Figure 3 9) Individ uals who were more efficient in executive control tended to have higher Digit Symbol Coding scores r ( 25)= 0.38, p< 0 .05, faster Trails A r ( 25)=0.47, p< 0 .05 and Trails B times r ( 25)=0.47, p< 0 .05, and attain more categories r ( 25)= 0.36, p< 0 .05 and produce fewer errors r ( 25)= 0.35, p< 0 .05 (Figure 3 12), on the Wisconsin Card Sorting test. In order to further assess the effects of inefficient executive control of attention, error rates (incongruent condition minus congruent condition) were correlated with neuropsychological performance across all participants. First, error rates were positively correlated with executive control scores r ( 25)=0.75, p< 0 .001, such that less efficient

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39 executive control RT was associated with higher error rate, which indicates t hat there was no speed accuracy trade off. In addition, individuals who were more efficient in orienting tended to make fewer errors r ( 25)= 0.36, p< 0.05; however, this correlation was not significant with bootstrapped standard errors. Individuals who com mitted fewer errors tended to have higher scores on the Digit Symbol Coding test r ( 25)= 0.43, p< 0.05, faster Trails A r ( 25)=0.34, p< 0.05 and Trails B times, r ( 25)=0.75, p< 0.001, attain more categories r ( 25)= 0 .48, p< 0.01 and commit fewer set losses r ( 22)=0.44, p< 0.05 on the WCST. Interestingly, there were several significant correlations within the PD participants, summarized in Table 3 3 alerting also tended to have faster Trails A times r ( 11)= 0.59, p< 0 .05. Oddly, those who were more efficient in orienting tended to make more perseverative errors on the WCST r ( 9)=0.62, p< 0 .05. Lastly, PD patients who were more efficient in executive control tended to have faster Trails A times r ( 11)=0.54, p< 0 .05; however, this relationship was no longer significant with bootstrapped standard errors. Despite significant correlations between attention network scores and cognition, no significant correlations were observed between attention network scores an d measures of 3 4 ). Association B etween A ttention N etwork S cores and M easures of E motion Correlations between attention networks and measures of emotional functioning across all participants are summarized in Table 3 5 Briefly, individuals who were more efficient in orienting reported fewer symptoms of depression (BDI ) r ( 25)= 0.39, p< 0.05 and trait anxiety r ( 25)= 0.55, p< 0.01. In addition, individuals who were more efficient in executive control reported fewer sympt oms of depression (BDI ) r ( 25)=0.58, p< 0.0 1,

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40 ( GDS ) r ( 25)=0.52, p< 0.01, apathy r ( 25)=0.44, p< 0.05, and state r ( 24)=0.57, p< 0 .01 and trait anxiety r ( 24)=0.42, p< 0 .05. Within PD participants, similar associations existed (Table 3 6) disease patients who were more efficient in orienting reported fewer symptoms of depression BDI, r ( 11)= 0.57, p< 0.05. Lastly, those who were more efficient in executive control reported fewer symptoms of depression BDI, r ( 11)=0.68, p< 0 .05 and state anxiety r ( 1 0)=0.65, p< 0.05. Discussion We sought to investigate the efficiency of separate attentional networks in medicated patients with in an exploratory hypothesis generating manner, examine the relationship between attentional functionin g and cognitive executive dysfunction, emotional, and motor symptoms. Our initial hypothesis that PD patients would show the proportionally larger dysfunction in the executive control network was partially supported. While PD patients and controls did no t differ significantly in incongruent versus congruent target RT, PD patients committed significantly more errors in response to incongruent targets relative to controls. This supports the notion that PD patients have difficulty in detecting or resolving r esponse conflict (e.g., when two or more simultaneous mutually incompatible responses are available, but only one is relevant to task demands ) ( Wylie et al., 2009 ) In addition, PD patients showed a dis proportionally smaller P3 amplitude attenuation to inc ongruently flanked targets compared to controls, a response that has been linked to dysfunction in the neural structure involved in monitoring for response conflict, the anterior cingulate cortex (Neuhaus et al., 2007 ; van Veen & Carter, 2002 ). In general, these findings are consistent with frontal striatal dysfunction seen in PD.

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41 More efficient executive control (e.g., quicker conflict resolution of incongruent targets, relative to congruent) was associated with better performance on measures of processin g speed (Digit Symbol Coding, Trails A), attentional switching (Trails B, Trails B Trails A), and abstract problem solving (WCST categories, total errors). Thus, while there was no significant group difference in RT, executive control network scores may s till be important for understanding changes in cognition. The executive control network RT was also associated with self reports of emotional functioning. Specifically, those who were more efficient in resolving conflict reported fewer symptoms of depressi on, anxiety, and apathy. This relationship is particularly interesting because of role in cognitive and affective regulation (Bush, Luu, & Posner 2000) and implies that diverse affective and cognitive dysfunction may thus be caused by common pat hology in PD. Granted, within our PD participants, in efficient conflict resolution was only significantly associated with depression and state anxiety. With regard to alerting of attention, no significant differences were shown between PD patients and co ntrols behaviorally or in ERPs. This finding suggests that PD patients show intact phasic exogenous alerting in that they are equally capable of preferential stimulus processing when temporally cued relative to controls. That is, PD patients and healthy co ntrols benefited equally from the presentation of cues that alerted them to a shortly following target stimulus presentation. Furthermore, PD patients and healthy controls displayed equally enhanced target N1 amplitude following presentation of cues alerti ng them to the presentation of an upcoming target. Interestingly, across all participants, and within PD patients, efficient alerting was associated with better performance on a measure of visuospatial processing speed, Trails A time. This seems

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42 to sugges t that phasic arousal mechanisms may affect dynamic processes such as visual search. However, several participants had negative alerting scores (meaning they were faster when uncued), which suggests that the relationship between the alerting score and Trai ls A time is complex. The results regarding orienting of attention were unexpected. Contrary to several studies that showed that PD patients and healthy controls exhibited parallel benefit in RT to spatially cued targets (e.g., Filoteo et al., 1997 ) PD pa tients in our study showed significantly less benefit in response speed to spatially informative cue s of the location of pending target N1 amplitude to spatially cued targets relative to c enter cued targets. These data seem to suggest that PD patients successfully shifted attention to the location of the target following spatial cues but w ere unable to translate the benefit of being oriented to the target into faster correct response to th e targets Taken together, the idea that PD patients can successfully orient to stimuli, but not benefit in terms of acting on them is consistent with the view that PD patients show more reflexive shifts of attention ( Briand, Hening, Poizner, & Sereno, 20 01 ), less guided by top down behaviorally relevant goals. Thus, they are capable of moving attention exogenously (e.g., from the bottom up) but may still be slow to act on complex stimuli due to poor preparation. Attentional models proposed by Corbetta an d Shulman (2002) investigations of the changes in orienting described here. Recent evi dence suggests that expectations facilitate stimulus processing via frontoparietal networks including the

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43 frontal eye field and intraparietal sulcus (Capotosto, Babiloni, Romani, & Corbetta, 2009). It may be that frontal disruption affects attentional orie Regarding the findings of previous studies many of the aforementioned studies showing similar attentional orienting among PD patients and controls used simple RT measures which did not include discrimination a s the ANT does (left versus right target). Thus, they did not specifically test the degree to which orienting of attention aids in more complex stimulus processing (over and above stimulus detection), an important function of attention. More efficient ori enting of attention was associated with better performance on a measure of processing speed (Digit Symbol Coding). Interestingly, efficient orienting was also associated with better performance on measures of attentional switching (Trails B time; Trails B Trails A). Most surprising was that within PD patients, efficient orienting was associated with increased number of perseverative errors in the WCST. It is difficult to speculate as to the nature of this relationship and should be investigated further. R e gard ing the relationship between attentional orienting and emotional functioning, we found that overall those who were more efficient in orienting tended to endorse fewer symptoms of depression and anxiety. Within PD patients, more efficient orienting wa s also related to self reported trait anxiety. Given these correlations, it may be that the neural correlates of attentional orienting and mood disturbance are influenced by similar neural pathology

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44 In sum, these findings demonstrate that non demented PD patients show dysfunction in the orienting of attention and executive control aspects of attention. These changes were associated with cognitive and affective sequ e lae commonly but independent of disease chronicity, medica tion level, and gross motor dysfunction. Limitations and Future Directions Findings of the present study must be considered within the context of several potential limitations. First, the small sample size places some constraints on the generalizabil i ty of findings. Several PD patients in this study were seeking evaluations for deep brain stimulation surgery, which may reflect sampling bias. That said, and despite the small number PD participants in the present study represented a wide range of disease ch ronicity and severity. Unfortunately, this range in chronicity prevented us from assessing whether these deficits are present early in the disease state. Second, the fact that none of our PD participants were treatment naive precluded more meaningful inves tigation into the effects of medication, which has been shown to both positively and negatively impact the cognitive deficits seen in PD ( e.g., Kulisevsky, 2000 ). While we included two individuals who had previous deep brain stimulation surgery in analyses subsequent analyses showed that their removal did not affect the pattern of results reported here. Lastly, the small sample size was associated with significantly limited statistical power We chose to not correct alpha levels for multiple comparisons i n correlation analyses for this reason. Another limitation was that ERPs for PD patients in the alerting and orienting comparisons used fewer sweeps. While this was due primarily to fewer correct responses of PD patients and not to differences in artifact rejection by group, the lower

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45 number of raw trials may have resulted in ERPs with poorer signal to noise ratio for PD patients. This study was not designed to localize function to specific brain regions. While it has been assumed that P3 attenuation for i ncongruent targets is related to ACC mediated conflict monitoring, this was not assessed directly in our study. Future studies with the capacity for greater spatial resolution (e.g., fMRI with EEG) could be used to provide support for system specific contr ibutions to dysfunction. In addition, due to the relatively small number of incorrect responses generated by both groups, we were unable to assess electrophysiologically (due to insufficient signal to noise ratio) the ways in which trials with correct resp onses and those with incorrect responses were differentially processed and were unable to examine the so called error related negativity (ERN) which is thought to reflect aspects of performance monitoring mediated by the ACC (e.g., van Veen & Carter, 2002) as has been done, for example in traumatic brain injury (e.g., Larson, Stigge Kaufman, Schmalfus,& Perlstein, 2007). Future studies may further explore the specific hypothesis of ACC dysfunction in PD by evaluating the neural processes involved in making errors to assess aspects of performance monitoring in PD patients. Lastly, the observed difference in peak P3 latency was unexpected, and it is currently unclear whether this latency shift is related to the same neural dynamics that contribute to P3 ampli tude changes. Recently, the psychometric properties of the ANT have come under scrutiny. Macleod et al. (2010) cautioned against the over interpretation of significance values in individual networks due to their differential power to detect differences. H owever, in their evaluation Macleod et al. (2010) determined that the executive control network was the

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46 most likely to show differences in small samples I n this study the orienting network was the only to show a significant group difference. This sugges ts to us that the study was adequately powered to determine disproportionate dysfunction in one or more attention network. Correlation analyses were used to test general hypotheses and to provide data for future hypothesis generation regarding the dynamic relationship between attention network dysfunction and cognitive, emotional, and motor functioning. These analyses lacked adequate statistical controls for clear conclusions to be made and may have been influenced by overall group differences. That said, future research may benefit from knowledge of the relationships shown in this study. The purpose of the present study was to identify which aspects of attention were other aspects of cognitive executive functioning, emotional dysfunction, or motor symptoms. These goals came in light of findings that attention functioning (as measured by simple RT tasks) may be a salient predictor of future general cognitive decline ( Taylor e t al., 2008 ). Thus, the current findings that orienting of attention and executive control are affected in PD should guide future longitudinal studies toward identifying those who are at increased risk of general cognitive decline. Further clarifying and identifying which aspects of attention are impaired in PD also serves another important purpose. Namely, by better characterizing the dysfunctions of attention, with each sub system instantiated through different neuroanatomical networks and neurochemical pathways, more targeted treatments can be created to address when cognitive dysfunctions begin to impact important abilities

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47 later in the disease. G iven the preliminary nature of findings regarding orienting of attention, more research is necessary to dete rmine the cause of this dysfunction and the degree to which this change is clinically relevant. Additionally, the use of more comprehensive cognitive tests (including measures of other domains such as visuospatial and memory functioning) may further clarif y the effects of the disease process in PD on cognitive functioning more generally.

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48 Table 3 1. Average attention score network (RT and Z score) as a function of group membership. Control Mean (SD) Mean (SD) d Alerting (ms) 21.36 57.54 15 .79 32.33 0.12 Orienting (ms)* 43.32 46.90 83.61 32.38 0.99 Executive (ms) 179.27 118.22 142.82 18.84 0.41 Alerting Z 0.00 0.52 0.23 0.42 0.48 Orienting Z* 0.19 0.52 0.69 0.56 0.89 Executive Z 1.59 0.41 1.63 0.23 0.12 *p<.05

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49 Table 3 2. Correlations of attention network RTs with measures of executive functioning and processing speed across all participants. Alerting Orienting Executive Digit Symbol Coding (n=25) 0.00 0.46* 0.38* Trails A (n=25) 0.40* 0.11 0.47** Trails B (n=25) 0.24 0.37* 0 .47** Trails B Trails A (n=25) 0.16 0.39* 0.40** WCST Categories (n=25) 0.09 0.14 0.36* WCST Total Errors (n=23) 0.08 0.10 0.35* WCST Perseverative Errors (n=23) 0.11 0.13 0.30 WCST Failure to Maintain Set (n=22) 0.23 0.14 0.24 *p<.05, **p<.01

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50 Table 3 3. Correlations of attention network RTs with measures of executive functioning Alerting Orienting Executive Digit Symbol Coding (n=11) 0.62 0.06 0.37 Trails A (n=11) 0.59* 0.20 0.54* Trails B (n=11) 0.41 0.33 0.48 Trails B Trails A (n=11) 0.30 0.41 0.40 WCST Categories (n=11) 0.26 0.23 0.37 WCST Total Errors (n=9) 0.18 0.56 0.49 WCST Perseverative Errors (n=9) 0.23 0.62* 0.42 WCST Failure to Maintain Set (n=8) 0.26 0.12 0.22 *p<.05

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51 Table 3 chronicity, stage, motor dysfunction, and medication dosage. Alerting Orienting Executive Hoehn Yahr Stage (n=9) 0.28 0.08 0.25 UPDRS Motor (n=11) 0.10 0.33 0 .03 Levodopa Equivalent Dose (n=10) 0.09 0.16 0.35 Months with Symptoms (n=11) 0.04 0.22 0.27

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52 Table 3 5. Correlations between attention network scores and measures of emotional functioning across all participants. Alerting Orienting Executive Beck Depression Inventory II (n=25) 0.02 0.39* 0.58** Geriatric Depression Scale (n=25) 0.21 0.33 0.52** Apathy Scale (n=25) 0.02 0.20 0.44* STAI Trait (n=24) 0.06 0.55** 0.42* STAI State (n=24) 0.17 0.21 0.57** *p<.05, **p<.01

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53 Table 3 6. Correlations between attention network scores and measures of emotion Alerting Orienting Executive Beck Depression Inventory II (n=11) 0.01 0.13 0.68* Geriatric Depression Scale (n=11) 0.20 0.14 0.51 Apathy S cale (n=11) 0.05 0.27 0.52 STAI Trait (n=10) 0.06 0.57* 0.33 STAI State (n=10) 0.48 0.28 0.65* *p<.05

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54 Figure 3 1. Mean ANT RTs as a function of group, cue type, and flanker type. Error bars reflect twice the standard error of the mean (e.g., 95% confidence interval). 500 700 900 1100 1300 Congruent Incongruent Neutral Reaction Time (ms) Control No Double Center Spatial 500 700 900 1100 1300 Congruent Incongruent Neutral Reaction Time (ms) PD No Double Center Spatial

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55 Figure 3 2. Mean ANT error rates a function of group, cue type, and flanker type. Error bars reflect twice the standard error of the mean (e.g., 95% confidence interval). 0 5 10 15 20 Congruent Incongruent Neutral Error Rate (%) Control None Double Center Spatial 0 5 10 15 20 Congruent Incongruent Neutral Error Rate (%) PD None Double Center Spatial

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56 Figure 3 3. Cue locked grand averaged ERPs over parietal occipital sites (average: PO7, PO8, PO4, PO3) as function of group and cue type in the alerting comparison.

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57 Figure 3 4. Mean N1 amplitudes as a function of group, cue type, and electrode position in the alerting comparison. Error bars refl ect twice the standard error of the mean (e.g., 95% confidence interval). 5 4 3 2 1 0 PO7 PO3 PO4 PO8 Amplitude (V) Control Electrode Double No 5 4 3 2 1 0 PO7 PO3 PO4 PO8 Amplitude (V) Parkinson Electrode Double No

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58 Figure 3 5. Cue locked grand averaged ERPs over parietal occipital sites (average: PO7, PO8, PO4, PO3) as function of group and cue type in the orienting comparison.

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59 Figur e 3 6. Mean N1 amplitudes as a function of group, cue type, and electrode position in the orienting comparison. Error bars reflect twice the standard error of the mean (e.g., 95% confidence interval). 6 4 2 0 PO7 PO3 PO4 PO8 Amplitude (V) Control Electrode Center Spatial 6 4 2 0 PO7 PO3 PO4 PO8 Amplitude (V) Parkinson Electrode Center Spatial

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60 Figure 3 7. Target locked grand averaged ERPs over posterior midline sites (average: CPz, Pz, POz) as a function of group and flanker type in the executive control comparison.

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61 Figure 3 8. Mean P3 amplitudes as a function of group, flanker type, and electrode position in the executive control compar ison. Error bars reflect twice the standard error of the mean (e.g., 95% confidence interval). 0 1 2 3 4 CPz Pz POz Amplitude (V) Electrode Control Neutral Congruent Incongruent 0 1 2 3 4 CPz Pz POz Amplitude (V) Electrode Parkinson Neutral Congruent Incongruent

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62 Figure 3 9. Correlation between alerting RT and Trails A time. Collapsed across both groups, R=0.16.

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63 Figure 3 10. Correlation between orienting RT and D igit Symbol Coding score. Collapsed across both groups, R=0.21.

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64 Figure 3 11. Correlation between orienting RT and Trails B Trails A Time. Collapsed across both groups, R=0.15.

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65 Figure 3 12. Correlation between executive control RT and WCST total errors. Collapsed across both groups, R=0.13

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72 BIOGRAPHICAL SKETCH Jas on Gravano earned his Bachelor of Science degree in Psychology from the University of California at San Diego in 2008. After two years as a research assistant in a neuropsychology of aging lab in the V eterans Medical Research Foundation and VA San Diego Healthcare system, he began a Ph.D. program in clinical psychology at the University of Florida. In May 2012, he received his Master of Science in Clinical Psychology.