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Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-08-31.

Permanent Link: http://ufdc.ufl.edu/UFE0043142/00001

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Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-08-31.
Physical Description: Book
Language: english
Creator: Zahodne, Laura B
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: Clinical and Health Psychology -- Dissertations, Academic -- UF
Genre: Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Laura B Zahodne.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Bowers, Dawn.
Electronic Access: INACCESSIBLE UNTIL 2014-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0043142:00001

Permanent Link: http://ufdc.ufl.edu/UFE0043142/00001

Material Information

Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-08-31.
Physical Description: Book
Language: english
Creator: Zahodne, Laura B
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: Clinical and Health Psychology -- Dissertations, Academic -- UF
Genre: Psychology thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Laura B Zahodne.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Bowers, Dawn.
Electronic Access: INACCESSIBLE UNTIL 2014-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0043142:00001


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1 COMPONENTS OF DEPRESSION IN PARKINSON DISEASE: RELATION TO PSYCHOPHYSIOLOGY AND AFFECTIVE CHRONOMETRY By LAURA BETH ZAHODNE A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLME NT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 201 2

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2 201 2 Laura Beth Zahodne

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3 To William James Carr

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4 TABLE OF CONTENTS page LIST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 9 ABSTRACT ................................................................................................................... 10 CHAPTER 1 OVERVIEW ............................................................................................................ 12 2 BACKGROUND ...................................................................................................... 14 Parkinson Disease (PD) .......................................................................................... 14 Overview .......................................................................................................... 14 Impact ............................................................................................................... 14 Neurobiology of NonMotor Symptoms ............................................................ 15 Depression in PD ............................................................................................. 16 Apathy in PD .................................................................................................... 21 Parsing Depression ................................................................................................ 23 Subtypes of Depression ................................................................................... 24 Components of Depression .............................................................................. 25 Temporal Dynamics of Affective Processing ........................................................... 34 Affective Chronometry ...................................................................................... 34 Anticipation/Expectancy vs. Perception ............................................................ 34 Startle Eyeblink Psychophysiology ......................................................................... 35 Neurobiology of Startle Reactivity .................................................................... 36 Startle Eyeblink and Anticipation Paradigms .................................................... 37 Emotion Modulation of Startle Eyeblink in Depression ..................................... 39 3 STATEMENT OF THE PROBLEM ......................................................................... 43 Apathy ..................................................................................................................... 44 Anhedonia ............................................................................................................... 46 Negative Affect ....................................................................................................... 46 General and Specific Aims ...................................................................................... 47 Aim 1: Identifying Emotion Components in PD Depression .............................. 48 Aim 2: Patterns of Emotion Psychophysiology in PD Depression .................... 48 Aim 3: Relation of Depression Components to Psychophysiology Variables ... 51 Importance of the Knowledge to be Gained ............................................................ 52 4 RESEARCH DESIGN AND METHODS .................................................................. 55 Participants ............................................................................................................. 55 Parkinson Disease Patients .............................................................................. 55

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5 Healthy Control Participants ............................................................................. 57 Procedure ............................................................................................................... 58 Overview of Design .......................................................................................... 58 General Procedure ........................................................................................... 59 Study 1: Psychometric Characterization of PD Depression .............................. 60 Study 2: Psychophysiology ............................................................................... 65 Data Analyses ......................................................................................................... 70 Specific Aim 1 ................................................................................................... 70 Specific Aim 2 ................................................................................................... 71 Specific Aim 3 ................................................................................................... 73 5 RESULTS ............................................................................................................... 81 Aim 1: Characterization of Depression in PD .......................................................... 81 Frequency of Depression ................................................................................. 81 Demographics and Disease Characteristics ..................................................... 82 Psychological Scores of Depressed and Non Depressed Patients .................. 82 Confirmatory Factor Analysis ........................................................................... 82 Discriminant Function Analysis ......................................................................... 84 Summary of Aim 1 Results ............................................................................... 84 Aim 2: Startle Psychophysiology ............................................................................. 85 Participant Characteristics ................................................................................ 85 Startle Eyeblink Responses on Baseline (Unprimed) Trials ............................. 86 Startle Eyeblink Responses on Emotion Picture Trials ..................................... 87 Subjective Ratings of Pictures .......................................................................... 94 Effects of Antidepressants on Physiologic Reactivity in PD Depression Group ............................................................................................................ 96 Effects of Sad Mood on Physiologic Reactivity in PD Depression Group ......... 97 Summary of Aim 2 Results ............................................................................... 98 Aim 3: Relating Psychophysiology Variables to Depression Components .............. 98 Apathy .............................................................................................................. 99 Anhedonia ...................................................................................................... 101 Negative Affect ............................................................................................... 102 Summary of Aim 3 Results ............................................................................. 103 6 DISCUSSION ....................................................................................................... 126 Prevalence of Depression ..................................................................................... 127 Aim 1: Characterizing Depression in PD ............................................................... 130 Factor Structure of Psychological Symptoms in PD ....................................... 130 Discriminating Depression in PD .................................................................... 131 Aim 2: Star tle Psychophysiology ........................................................................... 132 Startle Psychophysiology in Healthy Controls ................................................ 134 Startle Psychophysiology in Depressed PD ................................................... 138 Startle Psychophysiology in Nondepressed PD ............................................ 146 Modulation of Startle Eyeblink Psychophysiology by Negative Versus Positive Material .......................................................................................... 148

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6 Aim 3: Relating Psychophysiology Variables to Depression Components ............ 150 Apathy ............................................................................................................ 151 Anhedonia ...................................................................................................... 155 Negative Affect ............................................................................................... 155 Overall Conceptual Perspective ............................................................................ 156 Limitations ............................................................................................................. 159 Conclusions and Directions for Future Research .................................................. 160 REFERENCE LIST ...................................................................................................... 164 BIOGRAPHICAL SKETCH .......................................................................................... 190

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7 LIST OF TABLES Table page 2 1 Studies of depression using emotionmodulated startle eyeblink ....................... 41 4 1 Characteristics of the total Parkinson patient sample ......................................... 76 4 2 Psychological measures .................................................................................... 77 4 3 Normative ratings for selected pictures .............................................................. 78 5 1 Diagnostic features of depressed patients ....................................................... 105 5 2 Characteristics of depressed and nondepressed PD patients ........................ 106 5 3 Scores on the psychological scales for depressed and nondepressed PD patients ............................................................................................................. 107 5 4 Standardized factor loadings in the nested first order models ......................... 108 5 5 Standardized factor loadings in the secondorder model ................................. 109 5 6 Correlation matrix of factor scores ................................................................... 109 5 7 Classification accuracy in the discriminant function analysis ........................... 109 5 8 Characteristics of Study 2 participants ............................................................. 110 5 9 Group differences on the psychological measures ........................................... 111 5 10 Number of valid trials during the psychophysiology startle task ...................... 112 5 11 Mean latencies and raw amplitudes ................................................................ 112 5 12 Startle amplitudes in T score metric ................................................................ 112 5 13 Subjective ratings of valence and arousal by group and picture type .............. 113 5 14 Percentages of normatively classified pictures ................................................ 113 5 15 Number of valid trials for analyses using subjective picture classification ....... 113 5 16 Startle amplitudes during the perception of subjectively classified pictures .... 114 5 17 Startle eyeblink responses in T score metric in exploratory analyses with depressed patients ......................................................................................... 114

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8 5 18 Correlations between factor scores and startle eyeblink responses during the anticipation and perception of negative, neut ral and positive pictures ...... 115 5 19 Results from separate linear regressions in which apathy, anhedonia and negative affect factor scores were regressed on startle eyeblink responses (T sco re) in each condition ............................................................................. 116 5 20 Correlations between individual psychological measures and startle eyeblink responses during the anticipation of negative, neutral and positive pictures .. 117 5 21 Correlations between individual psychological measures and startle eyeblink responses during the perception of normatively classified negative, neutral and positive pictures ....................................................................................... 118 5 22 Correlations between individual psychological measures and startle eyeblink responses during the perception of subjectively classified negative, neutral and positive pictures ....................................................................................... 119

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9 LIST OF FIGURES Figure page 3 1 Aim 2 expected results ........................................................................................ 54 4 1 Study flow ........................................................................................................... 79 4 2 Trial schematic ................................................................................................... 80 5 1 Schematic model of the secondorder confirmatory factor analysi s .................. 120 5 2 Standardized startle eyeblink responses (T score) by group and affect condition during the anticipation period ............................................................ 121 5 3 Standardized startle eyeblink responses (T score) by group and affect conditi on during the perception period .............................................................. 122 5 4 Standardized startle eyeblink responses during the perception period using subjec tive classification of pictures ................................................................... 123 5 5 Standardized startle magnitudes in PD Depressed patients as a function of antidepressant usage during anticipati on and perception period ...................... 124 5 6 Standardized startle magnitudes in PD Depressed patients as a function of presence/absence of sad mood during anticipati on and perception period ...... 125

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10 Abstract of Dissertation Presented to the Graduate School of the Univ ersity of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy COMPONENTS OF DEPRESSION IN PARKINSON DISEASE: RELATION TO PSYCHOPHYSIOLOGY AND AFFECTIVE CHRONOMETRY By Laura Beth Zahodne August 201 2 Chair: Dawn Bowers Major: Psychology The overall goal was to characterize Parkinsons disease ( PD ) depression in terms of psychophysiology and affective chronometry. Specific aims were threefold: 1) to characterize PD depression via components: apathy, anhedonia, negative affect; 2) to identify patterns of startle eyeblink psychophysiology during emotional anticipation and perception; and 3) to learn how the components map onto psychophysiologic markers. It was predicted that apathy would correspond to reduced anticip atory responding, anhedonia would correspond to reduced startle modulation by pleasant stimuli, and negative affect would correspond to exaggerated physiologic reactivity across conditions. To address Aim 1, 95 nondemented PD patients underwent comprehensive mood assessment 28% met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for major or minor depression. Results indicated good fit for a confirmatory factor analysis model with three factors A pathy loaded most strong ly onto a secondorder global affective disturbance factor D iscriminant function analysis

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11 classified depressed patients well above chance (89%), and negative affect contributed most to classification. To address Aim 2, 3 0 PD patients (10 with depression) a nd 20 healthy controls participated in a startle eyeblink psychophysiology paradigm involving emotional pictures. As predicted, depressed PD patients did not exhibit psycho physiologic al expectancy which may reflect a working memory deficit due to reduc ed motivation and/or rumination. D epressed PD patients demonstrate d exaggerated responses during negative picture viewing, which may reflect hyper responsivity to aversive context. Aim 3 f indings were not strongly supportive of a priori hypotheses. Apathy did not correspond to blunted anticipat ory startle A nhedonia was not associated with valencespecific startle modulation. N egative affect was associated with greater emotion modulation of startle during perception. A ffective disturbance in PD is heterog eneous and can produce symptoms of apathy, anhedonia, and negative affect. Apathy is the core neuropsychiatric feature of PD, whereas negative affect is most pathognom on ic of PD depression. M ild to moderate PD depress ion is associated with reduced emotional expectancy and exaggerated physiologic threat responses. While the components did not map onto affective chronometry within the startle paradigm there was support for the existence of separate components. F uture may benefit from exploring relationships between these components and other variables (e.g., subjective experience, treatment response)

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12 CHAPTER 1 OVERVIEW Parkinson disease (PD) is the second most common neurodegenerative disease and is diagnosed based on its prominent motor symptoms: resti ng tremor, bradykinesia, rigidity, and postural instability. While these cardinal symptoms reduce functional abilities, it is now well accepted that common nonmotor features can exert an even greater impact on patients quality of life and level of disabi lity ( Weintraub, Moberg, Duda, Katz, & Stern, 2004; Visser et al., 2008 ). Indeed, the contemporary view of PD is that of a neuropsychiatric condition involving a constellation of physical, cognitive, and psychological symptoms One of the most common nonm otor symptoms of PD is depression, a neurobiological phenomenon related to actions of the neurodegenerative process on limbic regions of the brain. While several neurotransmitter systems have been implicated, current knowledge regarding the complex neurobi ology of depression in PD is limited. Further, phenomenological and pathophysiological differences in depression between individuals with PD and those with a primary affective disturbance are not clear. Recently, it has been shown that apathy, often a core symptom of depression, is encountered by a majority of individuals with PD and often manifests as an independent syndrome. There is growing recognition of a need to employ the methods of cognitive neuroscience and systems level neurobiology to understand the representation and regulation of mood states in the human brain. Indeed, the National Institute of Mental Health established a work group devoted to the topic, which is emphasized in their Strategic Plan for Mood Disorders research, published in 2003. Technological advances and the complete mapping of the human genome have, in part, fueled current interest in

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13 explicating the neuropathophysiological processes underlying affective disorders, which is required for more precise tailoring of future therapies. This study represents an attempt to combine psychometric and neuroscientific methods to examine affective disturbance in PD. The overall aim of t he project was to examine the relationship between depression components and affective chronometry in PD The potential contributions of this study include increased understanding of the unique pathophysiologies of different dimensions of affective disturbance in PD Such information may be useful for future development of targeted rehabilitation strategies for burdensome nonmotor sequelae in PD. The following section provides more background for this project

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14 CHAPTER 2 BACKGROUND Parkinson Disease (PD) Overview Parkinson disease (PD) is the second most common neurodegenerative disease and is characterized by its cardinal motor symptoms: resting tremor, bradykinesia, rigidity, and postural instability. The pathophysiology of PD involves the death of dopaminecontaining neurons in the substantia nigra pars compacta and resultant reduction of dopamine in the nigro striatal pathway. This deficiency in striatal dopamine disrupts activity in the corticobasal gangliathalamocortical circuits, resulting in pronounced motor impairment (Albin, Young, & Penney, 1989). Specifically, reduced striatal input reduces positive feedback via the direct pathway and increases negative feedback via the indirect pathway (Alexander, DeLong & Strick, 1986). This imbalance of pathway activity leads to the hallmark reduction in overall movement. Motor symptoms can be fairly well controlled with medications that aim to enhance dopaminergic activity (Schapira, 2005). However, drug treatments are often associated with adverse side effects such as unpredictable on/off motor fluctuations and dyskinesias, or excessive movements (Marsden, Parkes, & Quinn, 1982). Adjunct surgical intervention represents an alternative to exclusive pharmacological management of PD and has been shown to reduce the burden of these drug related side effects (Fabbrini, Brotchie, Grandas, Nomotor, & Goetz, 2007). Impact The incidence of PD in the elderly is estimated to be about 160 per 100,000 (Hirtz et al., 2007). Due to the aging of our population, general incidence is expected to

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15 triple over the next 50 years (Tanner, Goldman, & Ross, 2002). In 1817, Ja mes Parkinson described PD as a pure motor disorder in which the senses and the intellect remain uninjured. A surfeit of more recent investigations has documented a wide range of non motor sequelae that are often implicated by patients as more burdensome t han their impoverished movements. Indeed, not only do these nonmotor symptoms reduce patient reported quality of life, they directly contribute to disability and perform ance of act i vities of daily living (Weintraub et al., 2004; Visser et al., 2008). Furt her, they are highly predictive of both nursing home placement and mortality (Aarsland, Larsen, Tandberg, & Laake 2000; Hughes, Ross, Mindham & Spokes, 2004). Aside from their impact on the patient, nonmotor symptoms also contribute substantially to caregiver distress (Carter et al., 1998). Neurobiology of NonMotor Symptoms Parallel cortico basal gangliathalamocortical circuits funnel and refine cortical signals (Bar Gad & Bergman, 2001). Numerous segregated loops containing different types of cognit ive and behavioral information have been identified (Middleton & Strick, 2000; Alexander, DeLong & Strick, 1986). Motor symptoms have been shown to result from dysfunction within the motor loop, which comprises primary motor cortex, putamen, lateral globus pallidus interna, and the ventral lateral nucleus of the thalamus (Gibb, 1997). However, t he neurodegenerative process of PD may also affect nonmotor loops, which refine signals originating in cognitive regions such as the dorsolateral prefrontal cortex and limbic regions such as the anterior cingulate and orbitofrontal cortex (Middleton & Strick, 2000; Alexander, DeLong and Strick, 1986). D ysfunction within thes e systems, which all rely on midbrain (i.e., substantia nigra or ventral tegmental

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16 area) dopam inergic input, may underlie certain cognitive and affective symptoms (Obeso et al., 2008). Dopaminergic changes in PD have also been documented in regions outside of the midbrain. For example, reductions in amygdalar dopamine agonist binding of 30 45% hav e been documented in PD (Ouchi et al., 1999). In a study using functional neuroimaging, Tessitore, et al. (2002) identified reduced blood oxygen level dependent responses in the amygdala during a faceemotion matching task that was improved, but not revers ed, with dopaminergic medication. In addition to dopaminergic changes, PD also involves the formation of Lewy Bodies in many nonmotor regions of the brain, as well as abnormalities in neurotransmitter systems other than the dopamine system (e.g., norepin ephrine, serotonin) (Braak et al., 1993; Jellinger, 1991). These nondopaminergic mechanisms have also been implicated in some nonmotor features of PD, many of which tend to be less responsive to traditional pharmacological treatment (JavoyAgid & Agid, 1 980; Jellinger, 1999). Depression in PD Definition The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM IV ) defines major depression as the presence of depressed mood or loss of interest or pleasure for at least two weeks toget her with at least four other symptoms if they represent significant change from previous functioning (APA 2000). Other features include changes in appetite or weight, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue or loss of energy, feelings of worthlessness or excessive or inappropriate guilt, diminished ability to think or concentrate, indecisiveness, recurrent thoughts of death, or recurrent suicidal ideation. The DSM IV defines minor

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17 depression as the presence of depressed mood or loss of interest or pleasure for at least two weeks together with at least one other symptom if they represent significant change from previous functioning (APA 2000). Prevalence. Depression is one of the most common nonmotor features of PD, with averag e prevalence rates in cross sectional studies of PD patients of 40% (Brown & Jahanshahi, 1995). Major depression, as defined above, is estimated to occur in 1731% of PD patients (Reijnders, Ehrt, Weber, Aarsland, & Leentjens, 2008; Starkstein et al., 2008). Minor depression, as defined above, is estimated to occur in an additional 25% of patients (Reijnders et al., 2008; Marsh et al., 2006). The prevalence of clinically significant depressive symptoms, defined psychometrically or as dysthymia or subsyndrom al depression are also of clinical interest and are found in up to 90% of patients (Starkstein et al., 2008; Slaughter, Slaughter, Nichols, Holmes, & Martens, 2001; Tumas, Rodrigues, Farias, & Crippa, 2008). One study found that the frequency of depression diagnosed based on the presence of loss of interest/pleasure without sad mood was significantly higher in cases of minor (33%) as compared to major (8%) depression, suggesting that the diagnosis of minor depression is less specific for the presence of sad mood than is major depression (Starkstein et al., 2008). Overlap between symptoms of depression and s ymptoms of PD Depression is often under diagnosed and under treated in PD (Weintraub Moberg, Duda, Ketz, & Stern, 2003). A variety of issues complicate its identification, including overlap with motor features and difficulties in evaluating cognitively impaired patients (Schrag et al., 2007). Despite the numerous overlapping symptoms between PD and depression (i.e., cognitive impairment, apathy, psychomo tor changes, attentional changes, loss of

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18 appetite, weight change, sleep disturbances, and fatigue), an inclusive approach to diagnosing depression PD was recently recommended by a National Institute of Neurological Disorders and Stroke ( NINDS ) workgroup ( Marsh et al., 2006). Nonsomatic core symptoms of depression have been identified to discriminate depression in PD; however, somatic symptoms such as reduced appetite and early morning awakening are also important (Leentjens, Van den Akker, Metsemakers, Lo usberg, & Verjey, 2003). Features. In PD, depression is associated with decreased functional abilities, increased caregiver stress, reduced quality of life, more rapid progression of both cognitive and motor impairments, and mortality (Kuhn et al., 1996; W eintraub et al., 2004; Schrag, Jahanshahi, & Quinn, 2000; Trster et al., 1995; Aarsland et al., 1999). Depression often occurs prior to the onset of motor symptoms (Gmez Esteban et al., 2009). In addition, there is a documented association between depres sion and hereditary forms of PD, and there is no linear correlation between motor symptom severity and depression (Tandberg, Larsen, Aarsland, & Cummings, 1997; Huber, Paulson, & Shuttleworth, 1988). Thus, depression is believed to be a direct consequence of the neurodegenerative process, not merely a reaction to having a chronic disease (Lemke et al., 2004; Aarsland et al., 2007; Gmez Esteban et al., 2009). Indeed, several studies have shown that PD patients exhibit more depressive symptoms than other neurologic, nonneurologic medically ill, and geriatric populations (Robbins, 1976; Tandberg, Larsen, Aarsland, & Cummings, 1996; Veiga et al., 2009). Compared to PD patients without depression, PD patients with major depression have

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19 been noted to have longer disease duration and greater symptom severity (Palhagen, Carlsson, Curman, Walinder, & Granerus, 2008). Depression in PD shares many pathogenic factors with depression in primary affective disorders (Sano, Stern, Cote, Williams, & Mayeux, 1990; Leentjens Lousberg, & Verhey, 2002). However, it has been suggested that the localization, distribution and severity of neurotransmitter disturbances in PD depression differ from those in primary depression (Mayeux, Stern, Sano, Williams, & Cote, 1988). Further, preliminary evidence supports phenomenologically different depression profiles in PD (Gotham, Brown, & Marsden, 1986; Schiffer, Kurlan, Rubin, & Boer, 1988; Starkstein, Preziosi, Forrester, & Robinson, 1990; Ehmann, Beninger, Gawel, & Riopelle, 1990; Erdal, 2001; Merschdorf et al., 2003). Specifically, these authors have described a pattern of fewer classical depressive symptoms such as guilt and suicidal ideation and more somatic and cognitive symptoms in depressed individuals with PD. Anxiety, dysphoria, and irritability may also be more prominent in PD depression (Schiffer et al., 1988; Menza, RobertsonHoffman, & Banapace, 1993; Henderson, Kurlan, Kersun, & Como, 1992; Gotham, Brown, & Marsden, 1986; Brown, MacCarthy, Gotham, Der, & Marsden, 1988; Huber Freidenberg, Paulson, & Shuttleworth, 1990). The existence of distinct profiles was supported by a recent study using the Montgomery Asberg Depression Rating Scale that directly compared depression profiles of over 100 depressed patients with PD and 100 depressed elders matched for cognitive status and overall depression severity (Ehrt, Bronnic, Leentjens, Larsen, & Aarsland, 2006). In this study, depression in PD was associated with less sadness, guilt, and anergia and more concentration difficulties.

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20 D espite these preliminary findings, a recent NINDS workgroup concluded that a distinctive profile of depression has not yet been clearly identified in PD (Marsh et al., 2006). This workgroup recommended use of an inclusive diagnostic approach rather than an exclusive etiologic approach to maximize the likelihood of identifying clinically significant depression due to the existence of a broad spectrum of depressive disturbances in PD. Additionally, the work group recommended including nonmajor forms of depressive disturbances in clinical studies because such disturbances are often overlooked in PD and contribute to morbidity. The present study followed these recommendations in diagnosing PD depression. Specifically, an inclusive approach was used, and patient s who met criteria for either major or minor depression were included in the depressed PD group. Neurobiology The neurobiology of depression in PD is unclear, but one hypothesis involves degeneration of mesolimbic and mesocortical structures of the dopaminergic system, including the ventral tegmental area (VTA; Fibiger, 1984). Another hypothesis implicates reduced serotonergic activity, which has been documented in studies examining the cerebrospinal fluid of PD patients (Mayeux, Stern, Cote, & Williams, 1984). Serotonergic reduction may represent a compensatory mechanism for striatal dopamine depletion, as serotonin is known to inhibit the release of dopamine in the striatum normally (Mayeux, 1990). Independent of motor symptom severity, PD depression has been associated with morphological alteration of the mesencephalic raphe, a heterogeneous region of dopaminergic fiber tracts originating from the VTA, serotonergic projections from the superior central nucleus and the dorsal raphe nucleus, and noradrenergic fibers from the locus coeruleus (Walter, Skoloudik &

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21 Berg, 2009; Becker et al., 1997). Finally, recent demonstrations of the moodregulating effects of deep brain stimulation of the subthalamic nucleus in PD implicate a prominent role for the basal ganglia itself in mood regulation (Ardouin et al., 1999; Krack et al., 2001; Romito et al., 2002). Thus, the precise neuroanatomical and neurochemical substrates of PD depression remains to be determined (Leentjens, 2004). Apathy in PD Definition Apathy is characterized by a primary lack of motivation and can manifest in behavioral, cognitive, affective, and social domains (Marin, 1991; Marin, Biedrzycki, & Firinciogullari, 1991; Stuss, Van Reekum & Murphy, 2000). Behaviorally, it presents with reduced productivity, lack of effort, and reliance on others to structure daily activities. Cognitively, it presents with a lack of concern and reduced interest. Affectively, it presents with blunted affect and reduced responsiveness to positive or negative stimuli. S ocially, it presents with lack of action in ones own self interest (Marin, 1991; Starkstein et al., 1992; Sockeel et al., 2006; Stuss, Picton & Alexander, 1999). Apathy is often a core symptom of depression; however, it is known to manifest as an independ ent syndrome in neurologic conditions such as PD and dementia (KirschDarrow, Fernandez, Marsiske, Okun, & Bowers, 2006; Assal & Cummings, 2002). A key distinction between apathy and depression is the lack of dysphoria that is symptomatic of depression (Mi mura, 2007). Consequences of apathy can include physical deconditioning, worse performance on activities of daily living, uncooperativeness with care, social isolation, adverse interpersonal interactions, and caregiver distress (van Reekum, Stuss, & Ostran der, 2005)

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22 The DSM IV does not provide diagnostic criteria for apathy as an independent disorder. However, provisional criteria have been proposed (Starkstein, Petracca, Chemerinski, & Kramer, 2001; Drijgers, Dujardin, Reijnders, Defebvre & Leentjens, 201 0; Mulin et al., 2011). According to these criteria, a diagnosis of apathy in PD requires the presence of both a lack of motivation relative to a previous level of functioning or the standards of his/her age or culture, as well as at least one additional symptom from each of three domains: 1) Diminished goal directed behavior (e.g., lack of effort or energy to perform everyday activities, dependency on prompts from others to structure everyday activities); 2) Diminished goal directed cognition (e.g., lack o f interest in learning new things or in new experiences, lack of concern about ones personal problems); and 3) Diminished concomitants of goal directed behavior (e.g., unchanging or flat affect, lack of emotional response to positive or negative events). Diagnosis also requires the symptoms to cause clinically significant distress or impairment in social, occupation, or other important areas of functioning and that the symptoms are not due to physical disabilities, motor disabilities, a diminished level of consciousness, or the direct physiological effects of a substance. These criteria were recently endorsed by a Movement Disorder Society task force examining apathy rating scales in PD (Leentjens et al., 2008b) and validated on a sample of 122 patients wit h idiopathic PD in France (Drijgers et al., 2010). Prevalence. Because there is a lack of widely accepted, formal diagnostic criteria, the prevalence of apathy in PD has been studied using severity rating scales. Prevalence estimates have ranged from 17% to 70%, with variation related to different scales, cut off values, and patient samples (Leentjens et al., 2008b). Apathy in the

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23 absence of depression has been identified in 1630% of PD patients (KirschDarrow et al., 2006; Pederson, Larsen, Alves, & Aars land, 2009). Contemporary research suggests that apathy is core, naturally occurring neuropsychiatric feature of PD ( Starkstein et al., 1992; Aarsland et al., 2007). While apathy and depression can cooccur and feature some overlapping symptoms, apathy can also manifest as an independent syndrome (KirschDarrow et al., 2006; Isella et al., 2002). One study identified apathy as the driving feature in PD patients diagnosed with minor depression, as the frequency of depression diagnosed based on the presence o f loss of interest without sad mood was significantly higher in cases of minor (33%) as compared to major (8%) depression (Starkstein et al., 2008). Thus, diagnoses of minor depression in patients with PD may be more accurately classified as apathy. Parsi ng Depression A frequently cited problem in depression research is the use of global indices of depression despite growing recognition of its clinical heterogeneity (e.g., Shafer, 2006). A wealth of research supports the separability of different components of depression. These components have been shown to manifest differently in various groups of depressed patients, and they are differentially responsive to treatment (e.g., Kilgore, 1999; Barefoot et al., 2000; Boyer, Tassin, Falissart, & Troy, 2000). D i screpant research on depression may relate to differential severity of components in different patient samples. In the following sections, findings from two different approaches for addressing depression heterogeneity will be briefly reviewed, one involving depression subtypes and the other involving depression components.

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24 Subtypes of Depression Catatonic, m elancholic and a typical The DSM IV specifies three subtypes of depression. Catatonic depression (59% of patients) implies motoric immobility, e xcessive motor activity, extreme negativism, peculiarities of voluntary movement, and/or echolalia/echopraxia. Melancholic (10% of patients) and atypical (40% of patients) depression differ by their descriptions of reactivity to positive events and vegetat ive signs. Individuals with melancholic depression do not experience improved mood in response to positive events, while those with atypical depression are able to do so. Regarding vegetative symptoms, individuals with melancholic depression exhibit decreased appetite and insomnia, while those with atypical depression exhibit increased appetite (i.e., comfort eating) and hypersomnia. While consideration of these subtypes has proven useful in designing treatment plans for many patients, efforts to determine distinct neurobiological signatures of melancholic and atypical depressive subtypes have been largely unsuccessful (e.g., Greenberg, Payne, MacFall, Steffens, & Krishnan, 2008). Other s ubtypings In recent years there has been a proliferation of depres sive subtypings based on different collections of psychological symptoms, biological variables and demographic profiles. One subtype refers to 3 specific symptoms: withdrawal apathy and lack of vigor (WAV). The WAV subtype has been associated with increased age (Adams, 2001) and is described as a depletion syndrome resembling depression without sadness. Interesting, the WAV syndrome seems to resemble apathy or minor depression seen in PD. Findings from the stroke literature have identified other depress ion subtypes. In a study of 243 stroke patients (52%

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25 depressed), Hama and colleagues (2007) identified subtypes of affective and apathetic depression. The affective subtype was associated with left frontal lesions, and the apathetic subtype was associated with basal ganglia damage. Still other examples of depression subtyping include vascular depression, agitated depression, alexithymic depression, anxiety/aggressiondriven depression and reproductive depression. Components of Depression In contrast to the subtyping approach, the component approach does not assume the existence of specific, predetermined collections of symptoms to best describe groups of patients. Rather, this approach allows for the consideration of the levels of severity of individual depressive symptoms unique to each patient. Contemporary biological psychiatry is interested in examining the neural correlates of specific components of complex disorders in order to improve treatment (Harro & Oreland 2001). Mapping of the human genome is one driving force behind increased interest in parsing complex disorders in order to allow for identification of specific genetic vulnerabilities. Depression components, as described here, are referred to as endophenotypes in the behavioral genetics li terature. Factor analytic approaches have commonly been used to parse depression. One of the most widely used scales for quantifying depression severity in PD is the Beck Depression Inventory Second Edition ( BDI II; Marsh et al., 2006). From a principal components analysis (PCA) on an undergraduate sample described in the BDI II manual (Beck, Steer, & Brown, 1996), a twofactor solution emerged: a cognitive affective factor and a somatic factor. This solution has been replicated using PCA in a

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26 separate sam ple of over 1,000 undergraduates (Dozois, Dobson, & Ahnberg, 1998). This same twofactor solution (cognitiveaffective, somatic) was also confirmed in a PCA conducted on a sample of over 200 PD patients, although only 40% of total variance was explained (V isser et al., 2006). Studies conducted in other patient populations, with other depression scales, and/or using different factor analytic approaches have yielded slightly different results. For example, a PCA of the 15item Geriatric Depression Scale (GDS) supported the presence of three factors: sad mood, negative thoughts and apathy (Weintraub, Xie, Karlawish, & Siderowf, 2007). No somatic factor emerged with the GDS. This likely occurred because the GDS was designed not to include many somatic items due to the prevalence of bodily symptoms associated with increased health problems in older adults. A recent metaanalysis of 33 factor analytic studies of nearly 14,000 individuals who completed the Beck Depression Inventory supported the existence of three discrete factors: (1) Negative Affect, (2) MoodMotivation and Anhedonia, and (3) Somatic Concerns (Shafer, 2006). In this metaanalysis, approximately 1/3 of the studies involved patient samples, 1/3 involved student samples, and 1/3 involved adult samples. A meta analysis was also conducted on three other depression instruments: the Hamilton Depression Inventory (HAM D), the Center for Epidemiologic Studies Depression Scale (CES D), and the Zung Self Rating Depression Scale (SDS). Various factors we re identified depending on the particular scale and included: somatic, depressed affect, positive affect, interpersonal problems, anxiety, insomnia, positive symptoms, and negative symptoms (Shafer, 2006). Conclusions from this multi instrument study included the identification of three common factors found across

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27 depression tests: general depression (e.g., negative attitude toward self, depressed affect), positive symptoms (e.g., experience of pleasure, motivated behavior), and somatic symptoms Examinat ion of specific items revealed that the general depression factor resembled negative affect, and the positive symptoms factor resembled apathy and anhedonia. Implications for present project While apathy and anhedonia are often grouped together, the pres ent dissertation project considered them separately. The rationale for this approach relates to three lines of evidence. First, experimental studies of Schultz (1998) and Robinson and Berridge (1998) support the temporal and neurobiological differentiation of pre goal motivation and the post goal pleasure. In our current conceptualization, apathy is broadly viewed as a disorder of motivated behavior, which involves readying for action (i.e., pregoal motivation), and it may be dopaminemediated. Anhedonia, on the other hand, involves the experience of pleasure (i.e., post goal pleasure) and may be opioidmediated. Second, a recent confirmatory factor analysis of all items from the Apathy Scale and the Beck Depression Inventory pooled together in a single analysis supported a four factor model in 161 nondemented PD patients (Kirsch Darrow, 2009). These four factors were: apathy/loss of motivation, dysphoric mood, loss of interest/pleasure, and somatic complaints (KirschDarrow, 2009). Importantly, apathy/loss of motivation was distinct from loss of interest/pleasure (anhedonia). Third, the recent finding in our laboratory that apathy in PD strongly correlated with a paper and pencil measure of anticipatory pleasure, but not consummatory pleasure (Jordan, Ferencz, McKently, Okun, & Bowers, 2010).

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28 In the section below, neurobiological research on three cognitiveaffective components of depression will be reviewed: apathy, anhedonia, and negative affect. Because the present study was concerned primarily with pars ing affective symptoms of depression and because somatic symptoms are often experienced by PD patients without a mood disturbance, we did not explicitly examine somatic symptoms in this project. Apathy component of depression. As previously described, apat hy refers to a lack of motivation or goal directed behavior (Marin, 1991). In a recent study, Jordan, et al. (2010) found that apathy in PD correlated with reduced anticipation of pleasure but not with reduced experience of pleasure on several self report instruments: the Temporal Experience of Pleasure Scale (TEPS, Gard, Gard, Kring, & John, 2006) and the Behavioral InhibitionBehavioral Activation Scales (BIS/BAS, Carver & White, 1994). This finding corresponds to the view that apathy is primarily a motiv ational rather than a hedonic deficiency In studies of patients with acquired brain injuries (i.e., traumatic brain injury, stroke, hypoxia), apathy has been linked to reduced cardiovascular reactivity (i.e., blood pressure and heart rate) during therapeutic verbalization and in response to a cognitive stressor (Andersson, Krogstad & Finset, 1999; Andersson, Gundersen & Finset, 1999). However, no studies have examined PD apathy in relation to aspects of emotional psychophysiology that are specifically linked to motivational systems ( Bradley, 2009). Apathy can result from lesions of the frontal lobe ( Apostolova, et al., 2007; Andersson, Kroqstad, & Finset, 1999) and/or basal ganglia (Mendez, Adams & Lewandowski 1989; Benke, Delzaer, Bartha & Auer, 2003; Hama et al., 2007). Several

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29 studies in older adults with and without dementia have documented a relationship between apathy and anterior cingulate cortex (ACC) dysfunction in terms of hypoperfusion and reduced gray matter volumes (Craig et al., 1996; Lavrets ky, Ballmaier, Pham, Toga, & Kumar, 2007). The ACC has been identified as a substrate for ones willingness to invest effort to obtain rewards (Walton, Rudebeck, Bannerman, & Rushworth, 2007). Because of the position of the ACC in a limbic corticobasal ga nglia thalamocortical loop, a potential cause of ACC hypoactivity involves reduced tonic dopaminergic input to the nucleus accumbens core within the ventral striatum. Indeed, a recent study with 20 PD patients (eight with major depression) revealed an inve rse correlation between apathy severity and [11C]RTI 32 binding an index of nigrostriatal nerve terminals, in the ventral striatum bilaterally (Remy, Doder, Lees, Turjanski, & Brooks 2005) A study of 39 cognitively impaired elders recruited from a psyc hogeriatric day center (10 with mild cognitive impairment, 29 with dementia) demonstrated an association between apathy and reduced white matter density particularly frontal leukoariosis (Thomas, Hazif Thomas, Saccardy, & Vandermarq, 2004). These findings further implicate frontostriatal circuitry in the pathophysiology of apathy. Given that apathy is a common core symptom of depression, according to the DSM IV, it is not surprising that many of the frontal and striatal subregions implicated in the pathophysiology of apathy have also been shown to be dysfunctional in PD patients with depression (Fibiger, 1984; Ebmeier, Donaghey, & Steele, 2006 ; Remy et al., 2005). Several positron emission tomography studies have identified ACC hypometabolism in PD depressi on (Ring et al., 1994; Mentis et al., 2002). Remy and colleagues (2005)

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30 suggested that ACC dysfunction amongst PD patients with depression may result from a loss of catecholaminergic projections, as measured with lower [11C]RTI 32 binding potential in this region. Interestingly, deep brain stimulation of either an ACC subregion or the nucleus accumbens, the two areas most frequently implicated in PD apathy, effectively treats severe depression in many individuals without PD ( Mayberg et al., 2005; Schlaepfer et al., 2008). Czernecki, et al. (2002) demonstrated that PD patients endorsed fewer symptoms of apathy when assessed on versus off their normal dopaminergic medications. This observation suggests that apathy may be at least partially dopaminemediated. In addition, several case reports and case series as well as at least one randomized control trial have suggested that dopaminergic drugs such as methylphenidate (Hermann et al., 2008; Watanabe et al., 1995), amantadine (Andersson et al., 1992), bupropion (Corcoran, Wong, & OKeane, 2004), and bromocriptine (Powell, al Adawai, Morgan, & Greenword, 1996) improve apathy and related disorders of motivation. A recent study examined changes in apathy (Apathy Scale) versus depression (BDI) in a sample of medicall y managed PD patients over a two year time period (Zahodne, Marsiske, Okun, & Bowers, 2011). Apathy severity significantly worsened over two years in line with motor deterioration. In contrast, there were no changes in depression severity over time, and this pattern of results was not explained by antidepressant medications. Thus, PD apathy may be more closely linked to dopaminergic degeneration than is PD depression, which does not exhibit a linear trajectory over time (Schrag, Jahanshahi, & Quinn, 2001; B rown & Jahanshahi, 1995).

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31 Anhedonia component of depression. Anhedonia refers to the reduced ability to experience pleasure and is a core feature of major depressive disorder (APA, 2000; Gorwood, 2008). However, it has received less attention in current psychiatric literature, perhaps due to a shift in focus onto depressed mood (discussed below) as the pathognomic feature of Major Depressive Disorder (MDD) (Snaith, 1993; Silverstone, 1991). Neuroanatomically, anhedonia is generally considered to result fro m dysfunction within the central reward system, specifically to underactivity of the ventral striatum and excess activity of the ventromedial prefrontal cortex (Gorwood, 2008; Keedwell, Andrew, Williams, Brammer, & Phillips, 2005). However, the precise neurochemical signature of anhedonia is more controversial. Some authors attribute a primary role of dopamine in the hedonic experience (e.g., Drevets et al., 2001). However, much research suggests that dopamine plays more of a motivational role (Bressan & Cr ippa, 2005; Berridge & Robinson 1998). Instead, the hedonic experience may be mediated by an opioid system (Smith & Berridge, 2007). In contrast to apathy, which affects the processing of affective material regardless of valence, anhedonia is characterized by abnormal neural responses to pleasant stimuli, but not negative stimuli (Keedwell et al., 2005). The NINDS recently recommend that anhedonia may be more specific to PD depression than is loss of interest, which, as a symptom of apathy, may occur in the absence of depression (Marsh et al., 2006). Negative affect component of depression. One important distinction between depression and an independent apathy syndrome is the unique presence of dysphoric mood in the former (Mimura, 2007). Dysphoria refers t o a state of feeling unwell or unhappy and is more broadly subsumed under the construct negative affect. Included

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32 in negative affect are irritability, anxiety, as well as dysphoria (Watson & Clark, 1984). The neural circuitry of negative affect has been conceptualized as a withdrawal system that facilitates and organizes appropriate responses to cues of threat (Lang, Bradley & Cuthbert, 1990). Converging evidence from stroke research, animal lesion studies, and functional neuroimaging studies of mood induction suggests that the negative affect system comprises neural systems within the right prefrontal cortex (i.e., dorsolateral and ventromedial subregions) and the extended amygdala (Davidson, 2002; Barrett, Bliss Moreau, Duncan, Rauch, & Wright, 2007) Various neurochemical changes have been implicated in the neurobiology of negative affect. Specifically, reductions in dopamine, endogenous opioids, and serotonin may contribute to dysphoria and anger, while increases in norepinephrine, glutamate, and corticotrophinreleasing factor (CRF) and reductions in gamma aminobutyric acid ( GABA) may contribute to stress and anxiety (Koob, 2000; Painuly, Sharan & Mattoo, 2005). Of particular relevance to the current study is the finding that negative affect, including dysphoria and anxiety, is associated with enhanced psychophysiologic reactivity to affective stimuli regardless of valence (e.g., Kaviani et al., 2004). This finding is likely related to pathological activation of the amygdalae in mood disorders (Drevets, 2003). Negative mood states, both acute and chronic, have been linked to underactivity within the left dorsolateral prefrontal cortex (DLPFC) in healthy adults of varying ages (Gemar, Kapur, Segal, Brown, & Houle, 1996; Killgore, Gruber, & YurgelunTo dd 2007; Bench, Friston, Brown, Frackowiak, & Dolan, 1993). The common finding of hypoactivity of the left DLPFC in depression has been replicated in PD depression. For example, the efficacious treatment of PD depression with repetitive transcranial magnet ic stimulation

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33 (rTMS) correlates with increased blood flow in left DLPFC (Cardoso et al., 2008). Data from a recent positron emission tomography (PET) study suggest that greater serotonin transporter density within this region may contribute to PD depressi on (Boileau et al., 2008). Reduced gray matter volumes in bilateral orbitofrontal cortices (OFC) have also been documented in depressed individuals with PD and depressed elders without PD (Feldman et al., 2008; Lavretsky et al., 2007). Interestingly, contr olling for depression within this cohort revealed an independent correlation between apathy severity and reduced gray matter volumes within the ACC (Lavretsky et al., 2007). Findings of hypoactivation of prefrontal cortex and concomitant hyperactivation of subcortical regions such as the amygdala have been combined in circuit models of depression (Mayberg et al., 2005; Drevets, 2003). Summary. T he neurobiological studies reviewed in the sections above suggest that depression may comprise various symptom cl usters or components (i.e., apathy, anhedonia, and negative affect) that are mediated by different (though perhaps overlapping) neural systems (Heinzel et al., 2009; Keedwell et al., 2005; Milak et al., 2005). Preliminary findings suggest that apathy resu lts from reduced activity within the ACC and ventral striatum (including the nucleus accumbens) and/or deficient connectivity between these regions. Apathy also seems to be at least partially related to dopaminergic pathology. Anhedonia has been linked to dysfunction of the central reward system, specifically reduced activity of the ventral striatum and excess activity of the ventromedial prefrontal cortex. While some authors contend that the pathophysiology of anhedonia is dopamine mediated, contemporary r esearch supports primary involvement of the opioid system. Negative affect which includes features of

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34 dysphoria, anxiety and anger, has been linked to an extended withdrawal/threat network consisting of right prefrontal cortex, including dorsolateral and ventromedial subregions, and the extended amygdala. In addition, dysphoria has been consistently linked to hypoactivation of left dorsolateral prefrontal cortex in a variety of patient populations, including PD. Thus, neurobiological research demonstrates that the clinical heterogeneity of depressive symptomatology may map onto separable neural substrates. Temporal Dynamics of Affective Processing Affective Chronometry Another approach to enhancing our understanding of normal versus abnormal affective fun ctioning in individuals with mood disturbances involves examining the temporal dynamics of affective responding. Davidson (1998) has termed this approach affective chronometry It involves examining individual differences in emotional processing during per iods of expectancy versus periods of perception (e.g., Dichter & Tomarken, 2008). Substantial research supports the dissociability of these phases with regard to both behavioral and neural processes. Anti ci pation/Expectancy vs. Perception In 1892, William James proposed that the same neural networks underlie both the anticipation and the perception of a stimulus (James, 1950). Contemporary research in the domains of vision and sensation largely support this view, insofar as similar brain regions are activated by the expectation and perception of tactile and visual stimuli (Carlsson et al., 2000; Shulman et al., 1999). In contrast research in the domains of reward and pain appear to support the opposite view N amely neural networks involved

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35 in the expectancy of reward are dissociable from those involved in its perception ( Knutson, Fong, Adams, Varner, & Hommer, 2001; ODoherty, Deichmann, Critchley, & Dolan, 2002; Ploghaus, Becerra, Borras, & Borsook 2003). A similar dissociation was observed in a function al magnetic resonance imaging (fMRI) study investigating the temporal responses to emotional pictures in 17 healthy adult volunteers (Bermpohl et al., 2006). In this study emotional expectancy was associated with activation of subregions of the cingulate as well as the parietooccipital sulcus. In contrast, e motional perception was associated with activation of nonoverlapping regions, including the amygdala, insula, medial and lateral prefrontal cortex, cerebellum, and occipitotemporal areas. Other studi es have further suggested that the neural circuitry underlying the anticipation of positive emotional pictures may differ from that of negative emotional pictures (Ueda et al., 2003). However, the fMRI methodology used in these studies involved measurement of blood oxygen level dependent ( BOLD ) signal ing which is not temporally sensitive due to the time lag between neuronal firing and changes in regional blood flow. Emotion processing occurs over the course of milliseconds, and establishing reliable links between the time courses of emotional experiences and their underlying neural processes requires measurements that are tightly coupled to biological events. Startle eyeblink psychophysiology represents such a temporally sensitive research method that will be described in the following section. Startle Eyeblink Psychophysiology The present study employed a startle eyeblink psychophysiology paradigm that has been used extensively to measure emotional reactivity (Lang, Bradley & Cuthbert, 1990). The paradigm involved measurement of the startle eyeblink response, a

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36 defensive reflex elicited by aversive stimuli such as an abrupt, loud noise (Bradley, 2009). A well replicated finding is that the amplitude of the startle eyeblink reflex increases with increasi ng physiological arousal and is affected by the contextual foreground, which determines which motivational system (i.e., defensive vs. appetitive) is engaged (Bradley, Codispoti, Cuthbert & Lang, 2001). Specifically, in the presence of negatively valenced material, the size of the eyeblink reflex increases, or is potentiated. Conversely, in the presence of positively valenced material, the size of the eyeblink reflex is reduced, or attenuated. This is because engaging the appetitive system results in concom itant inhibition of noncongruent defensive reflexes (Bradley, Codispoti, Cuthbert & Lang, 2001). Thus, emotionmodulated startle indexes both valence (i.e., positive and negative) and arousal (i.e., level of activation). Neurobiology of Startle Reactivi ty The neural circuitry of the startle eyeblink reflex and its modulation has been exquisitely detailed in studies by Davis and colleagues using a rodent model (Davis, 1998; Davis, Gendelman, Tischler, & Gendelman, 1982) In brief, the basic startle circu itry is mediated entirely at the level of brainstem. However, startle responses can be directly modulated (i.e., increased, decreased) by input from the central nucleus of the amygdala via its projection to the brainstem. In rats, electrical stimulation of the amygdala facilitates the startle eyeblink response (Rosen & Davis, 1990). In contrast, lesions of the amygdala diminish fear potentiated and shock sensitized startle responses while leaving the basic startle eyeblink reflex intact (Hitchcock, Sananes, & Davis, 1989). Dysfunction of the amygdala does not eliminate the basic startle response per s. Rather, it eliminates potentiation of startle reactivity during aversive emotional

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37 states. In humans, for example, temporal lobe ablations involving the amyg dala are associated with reduced startle modulation during the viewing of aversive pictures. In addition, several relay nuclei located within the midbrain, including the periaqueductal gray and the laterodorsal tegmental nucleus) may also be involved in certain types of startle potentiation. Interestingly, dopaminergic projections from the ventral tegmental area to the amygdala are also involved in the expression of fear potentiation of the startle response, and the reflex is enhanced by stimulation of the ventral tegmental area and the lateral periaqueductal gray (Borowski & Kokkinidis, 1996). Attenuation of the startle response in the presence of pleasant stimuli likely involves mesoaccumbal pallidal circuitry and not the amygdala (Koch, Schmidt, & Schni tzler, 1996). Several experiments have demonstrated that accumbal dopamine is important for the acquisition, but not for the expression, of pleasureassociated attenuation of the startle reflex (Yeomans & Frankland, 1995). Further, stimulation of the ventr al pallidum, a key target of accumbal projections, reduces the amplitude of the startle response (Panagis, Miliaressis, Anagnostakis, & Spyraki, 1995). While the specific neuronal pathways by which these regions interact with the primary startle response c ircuit are unknown, they may involve neurons within the pedunculopontine tegmental nucleus, which receives projections from both the nucleus accumbens and the ventral pallidum and projects to neurons within the pontine reticular formation (Steidl, Li, & Ye omans, 2001). Startle Eyeblink and Anticipation Paradigms As described above, the dominant findings from a wealth of human studies over the past 20 years have demonstrated that startle eyeblink responses are larger when

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38 elicited during the processing o f negative emotional stimuli (e.g., scenes, faces, odors, sentences) relative to neutral or positive stimuli (Bradley, Codispoti, Cuthbert & Lang, 2001). This observation has led some investigators to view startle eyeblink responses as a valence barometer (Bradley, Cuthbert, and Lang, 1990). More recently, Sabatinelli, Bradley, and Lang (2001) refined this view and were the first to report the counterintuitive finding that the amplitude of the startle eyeblink reflex is enhanced during the anticipatory period p rior to the delivery of an upcoming stimulus, either positive or negative Thus, the startle eyeblink response is potentiated during the anticipation of affective stimuli regardless of valence. This pattern of enhanced anticipatory startle eyeblink results has been replicated across at least three laboratories (Skolnick & Davidson, 2002; Dichter & Tomarken, 2008; Sabatinelli, Bradley, Lang, Costa, & Versace, 2007). It has been proposed that startle eyeblink potentiation during anticipation likely ref lects a generalized mobilization for action prior to the occurrence of a relevant event (Sabatinelli, Bradley, & Lang, 2001). The neurobiology of startle potentiation during the anticipation of possible reward is unknown. However, it is plausible that the phenomenon involves the amygdala and/or the ventral tegmental area, as stimulation of both areas has been shown to enhance startle responses (Borowski & Kokkinidis, 1996; Rosen & Davis, 1990). While the amygdala is traditionally associated with the emoti on of fear, this nuclear complex has been implicated in learning and memory of both positively and negatively valenced material (McGaugh, 2004). Further, coupling of basolateral amygdala (BLA) and nucleus accumbens activity increases during rewardbased le arning, and BLA input facilitates long term potentiation at corticostriatal synapses (Popescu, Popa & Par,

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39 2009). Interestingly, the amygdala has also been linked to the prediction of gains and losses. Emotion Modulation of Startle Eyeblink in Depression Table 21 provides an overview of studies that have examined emotion modulation of startle reactivity by individuals with depression or subclinical depressive symptomatology. One dominant theme is that individuals with a formal diagnosis of MDD do not di splay the typical pattern of emotion modulated startle eyeblink responses observed in normal, nondepressed individuals. Specifically, they do not display linearly increasing startle eye blink magnitudes during pleasant, neutral and negative stimuli (Allen Trinder, & Brennan, 1999; Kaviani et al., 2004; Dichter, Tomarken, Shelton, & Sutton, 2004; Dichter & Tomarken, 2008; Forbes et al., 2005). This lack of normal startle modulation by positive and negative material is in line with a view of depression as involving emotional context insensitivity (Rottenberg, 2007). In reviewing these studies, what clearly emerges is variability in how depression and depression severity alter the precise pattern of emotion modulation of the startle eyeblink response. S ome authors report that startle reactivity is uniformly blunted (i.e., no potentiation with negative stimuli, no inhibition with positive materials) (e.g., Kaviani et al., 2004). Others report that the deficit lies in a failure of negative emotional mater ials to prime the startle eyeblink response in depressed individuals (e.g., Forbes, Miller, Cohn, Fox, & Kovacs 2005). Still others report the opposite pattern, with a failure of positive materials to inhibit the startle eyeblink response (e.g., Seign ourel, 2007). The basis for these discrepant findings is unknown, and a variety of factors may be contributory.

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40 The relationship between depression symptom severity and the integrity of emotionmodulated startle responding is unclear. Some studies have found abnormal emotional reactivity in more severely depressed clinical subgroups (Kaviani et al., 2004) and nonclinically depressed individuals who obtained mildly elevated scores on a self report depression measure (Mneimne, McDermut & Powers, 2008). Other studies have documented abnormalities in only one valence condition. For example, Seignourel (2007) only identified abnormal responses to positive stimuli (i.e., lack of attenuation) in a sample of clinically depressed patients. Larson, Nitschke, and Davison (2007) found a lack of attenuation to pleasant pictures but normal potentiation to unpleasant pictures in a sample of nondepressed undergraduates with symptoms of anhedonic depression. Conversely, Forbes et al. (2005) and Allen, Trinder, & Brennan (1999) reported abnormal responses only to negative stimuli (i.e., lack of potentiation). However, a subgroup of severely depressed individuals in the latter study additionally showed a lack of startle eyeblink attenuation to positive pictures. Inter estingly, some studies have reported that individuals with depressive symptoms (but not MDD diagnoses) have enhanced rather than blunted startle eyeblink responses to negative stimuli (Cook, Hawk, David, & Stevenson, 1991; also see Grillon et al., 2005). This enhanced reactivity is consistent with a view of depression as involving hyperactivation of a defensive withdrawal system that mediates responses to aversive stimuli (Depue & Iacono, 1989; Fowles, 1988). Indeed, there is evidence for an association between negative affect and hyper responsivity to negative stimuli from other patient populations such as the anxiety disorders and premenstrual dysphoric disorder (Grillon & Bass, 2003).

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41 Table 2 1. Studies of depression using emotionmodulated startle eye blink Population Number of Subjects Delivery of Startle Probes Results Allen et al., 1999 Depressed inpatients (DSM IV) and controls 14 depressed, 14 controls While viewing IAPS pictures Depressed gr ou p showed lack of startle potentiation to negative. Only severely depressed patients showed lack of attenuation to positive. Kaviani et al., 2004 Depressed inpatients (DSM IV criteria) and controls 22 depressed, 22 controls While viewing positive, neutral and negative film clips Highly depressed and anhedonic patients did not show modulation. Highly anxious patients showed potentiation across conditions Dichter & Tomarken, 2004 Depressed outpatients (DSM IV) and controls 17 depressed, 16 controls While view ing IAPS pictures (at 300ms or 4s into picture vi ewing period) Depressed patients normal early but abnormal late Seignourel, 2007 Depressed outpatients (DSM IV) and controls 14 depressed, 15 control While viewing personally relevant/irrelevant emotional adjectives or after a 6 or 26 sec delay Depressed group showed lack of attenuation to positive 20s following stimulus offset Dichter & Tomarken, 2008 Depressed outpatients (DSM IV) and controls 27 depressed, 60 control Prior to (2s or 750ms before) and during viewing of IAPS pictures, Depressed gr ou p showed abnormal ities during anticipation and perception OBrien Simpson et al., 2009 Individuals with MDD in full remission (DSM IV) tested twice over two years 25 (7 with depression recurrence) 5 7s following offset of IAPS pictures (averaged across v alence condition) Attenuated startle at baseline predicted depression recurrence Forbes et al., 2005 Adults with childhoodonset depression (DSM III/IV) and controls 38 unipolar, 38 bipolar, 60 control During viewing and 3, 4 or 5s after offset of IAPS p ictures Unipolar gr ou p showed lack of potentiation during negative pictures. Grillon et al., 2005 Non depressed children or grandchildren of individuals with or without MDD (DSM IV) 108 children, 70 grandchildren During anticipation of threat (i.e., air b last to the larynx) or anticipation of no threat Enhanced startle across conditions in children and female grandchildren of individuals with MDD

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42 Table 2 1 Continued. Population Number of Subjects Delivery of Startle Probes Results Cook et al., 1991 Undergraduates screened with Fear Survey Schedule 15 Low fear, 17 High fear 8 13s into imagery period following emotional or neutral script Self reported depression (MMPI D) associated with enhanced potentiation to negative stimuli Mneimne, McDermut & Powers, 2008 Undergraduates without MDD 16 with BDI > 11, 50 with BDI<11 While viewing IAPS pictures (2 5s probes) High BDI gr ou p showed lack of attenuation to pleasant and lack of potentiation to unpleasant Larson, Nitschke, & Davidson, 2007 82 undergraduates screened with PSWQ and MASQ 14 anxious apprehension, 10 anxious arousal, 14 anhedonic depression, 39 control Immediately prior to, during or following IAPS pictures No group difference during anticipation Normal potentiation to unpleasant. Lack of attenuation during and after pleasant Nitschke et al., 2002 81 undergraduates screened with PSWQ and MASQ 12 anxious apprehension, 14 anxious arousal, 18 anhedonic depression Immediately prior to or following IAPS viewing Startle modulatio n not related to trait measures of anxiety and mood Note. DSM IV: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; IAPS: International Affective Picture System; MDD: Major Depressive Disorder; BDI: Beck Depression Inventory; PSWQ: P enn State Worry Questionnaire; MASQ: Mood and Anxiety Symptom Questionnaire.

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43 CHAPTER 3 STATEMENT OF THE PRO BLEM Depression is one of the most prominent emotional disturbances in PD and may be related to disruption of mesolimbic dopamine pathways and/or other functional neuroanatomical systems vulnerable to PD type neurodegeneration. Increasingly, depression is recognized as a clinically heterogeneous disorder featuring a variety of components that are differentially prominent in various patient populations and that differently related to external variables such as demographic characteristics and treatment response. Discrepant research findings on depression may be partly attributable to differences in the relative severity of these components. In PD, for e xample, at least one component of depression (i.e., apathy) has been identified as particularly common and may even represent a unique syndrome, independent of depression. Convergent clinical, psychometric, and neurobiological research summarized above sug gests the existence of three cognitiveaffective symptom clusters in PD depression: apathy, anhedonia and negative affect. The overall goal of the present study was to examine these three components of depression (apathy, anhedonia, negative affect ) in patients with PD using an affective chronometric approach. In line with a componential view of depression, we wished to learn whether apathy, anhedonia and negative affect differentially map onto psychophysiologic markers in PD. Apathy and anhedonia are considered separately based on three lines of evidence: 1) Animal studies supporting the temporal and neurobiological differentiation of pregoal motivation (i.e., apathy) and post goal pleasure (i.e., anhedonia); 2) Confirmatory factor analysis of the Apathy Scale and the Beck Depression Inventory that confirmed separate factors of apathy/loss of motivation,

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44 dysphoric mood, loss of interest and pleasure, and somatic complaints (KirschDarrow, 2009); and 3) Recent findings that apathy in PD strongly cor related with a paper and pencil measure of anticipatory pleasure, but not consummatory pleasure (Jordan et al., 2010). Specific background and rationale for hypotheses involving apathy, anhedonia and negative affect are provided below. Apathy Apathy refer s to a lack of motivation or goal directed behavior (Marin, 1991). Numerous studies have documented that apathy is the most common neuropsychiatric symptom in PD (see Leentjens et al., 2008b). While it is often a symptom of depression, it can occur as an i ndependent syndrome in a variety of neurological disorders, including PD (Assal & Cummings, 2002). The neuropathophysiology of apathy includes hypoactivity within the ACC, which may result from a disruption in the front striatal loop involving the ACC and the nucleus accumbens core due to reduced tonic dopaminergic input to the ventral striatum (Lavretsky et al., 2007; Remy et al., 2005). This circuit involving the ventral striatum is the primary circuit involved in human motivation (Robinson & Berridge, 1998). It also underlies rewardbased learning, in which an organism acquires knowledge about future rewards and punishments based on informational cues in the environment (Schultz, 1998). Apathy has been associated with reductions in both arousal and motiv ation. Arousal refers to generalized alertness and responsiveness to environmental stimuli (Andrew, 1974; Agmo, 2010; Luria, 1973). Arousal is necessary for the expression of psychophysiologic reactivity during the elaborate internal processing involved in emotional expectancy (Sarter & Bruno, 2000). Specifically, arousal facilitates elaborate

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45 processing via cholinergic projections from the basal forebrain to the medial prefrontal cortex (Berntson, Sarter, & Cacioppo, 1998). Although it remains unknown whet her apathy in PD is associated with reduced arousal, some evidence suggests an association between arousal and apathy in individuals with acquired brain injuries (stroke, traumatic brain injury). This is based on findings of reduced blood pressure and hear t rate reactivity in apathetic individuals with brain lesions (Andersson, Krogstad & Finset, 1999; Andersson, Gundersen & Finset, 1999). Motivation refers to processes activating, directing, and determining the persistence of specific behaviors (Agmo, 2010). This definition contrasts with that of arousal, which involves general alertness. Motivation is important for translating general arousal into specific cognitions and/or behaviors. Importantly, apathy is conceptualized as a motivational deficit, rather than a hedonic deficit. One hypothesis is that reductions in arousal and/or motivation due to apathy may prevent psychophysiologic reactivity during emotional expectancy. This hypothesis is consistent with evidence from studies showing that the same cortic al regions that are activated during emotional expectancy (e.g., ACC) also exhibit hypometabolism among individuals with apathy ( Craig et al., 1996; Lavretsky et al., 2007; Bermpohl et al., 2006; Ueda et al., 2003). This hypothesis proposes that apathetic individuals may be less able to initiate the elaborative working memory rehearsal that is required to maintain emotional expectancy throughout the duration of the anticipation period. This lack of elaborative working memory rehearsal could be due to defici ts in general arousal and/or in the motivation to engage in sustained higher order cognitive processing.

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46 Anhedonia Anhedonia refers to a reduced ability to experience pleasure and is generally considered to result from dysfunction within the central r eward system, specifically underactivity of the ventral striatum and excess activity of the ventromedial prefrontal cortex (Gorwood, 2008; Keedwell et al., 2005). Like apathy, anhedonia is a common symptom of depression. Unlike apathy, which affects the pr ocessing of affective material regardless of valence, anhedonia is characterized by abnormal neural responses to pleasant stimuli, but not negative stimuli (Keedwell et al., 2005). Rather than reflecting a motivational deficit related to dopaminergic dysfu nction, anhedonia reflects a hedonic deficit, likely mediated by the opioid system (Smith & Berridge, 2007). The NINDS recently recommended that anhedonia may be more specific to PD depression than is loss of interest. Specifically, they proposed that loss of interest, as a symptom of apathy, may occur in the absence of depression (Marsh et al., 2006). There is a need to more clearly identify phenotypic and neuropathophysiologic differences between apathy and anhedonia in order to better inform more targeted treatments. Due to its specificity to positive emotional experiences, anhedonia was expected to be associated with deficient emotionmodulated psychophysiology in anticipation and perception conditions involving positive stimuli. Such an association may reflect an inability to translate an understanding of the meaning of positive stimuli into physiological markers of engagement. Negative Affect An important distinction between depression and an independent apathy syndrome is the unique presence of dys phoric mood in the former (Mimura, 2007).

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47 Dysphoria is one emotional state subsumed under the construct of negative affect, which can also include anxiety and irritability (Watson & Clark, 1984). The neural circuitry underlying negative affect is concept ualized as a generalized withdrawal system that facilitates and organizes appropriate responses to cues of threat (Lang, Bradley & Cuthbert, 1990). This neural circuitry is thought to comprise the right prefrontal cortex and the extended amygdala (Davidson, 2002; Barrett et al., 2007). Because negative affect has been linked to enhanced psychophysiological reactivity to affective stimuli regardless of valence (e.g., Kaviani et al., 2004, Seignourel et al., 2007), it was expected that negative affect would be associated with hyper startle responding across conditions in the present study. This association would likely reflect pathological activation of the amygdala in mood disorders (Drevets, 2003). Indeed, stimulation of the amygdala in the absence of an em otional context has been consistently shown to enhance startle responding ( Rosen & Davis, 1990). General and Specific Aim s The overall goal of the present study was to better understand the nature of depression in patients with PD from the perspective o f a componential view in relation to emotion psychophysiology and affective chronometry. The working hypothesis was that apathy would be prominent neuropsychiatric feature of PD, whereas negative affect would be most closely linked to PD depression. It was further predicted that the apathy component of depression would correspond, psychophysologically, to a reduced capacity for the anticipation of emotional stimuli regardless of valence, whereas anhedonia would reflect deficient psychophysiologic modulation by positively valenced stimuli. Finally, negative affect ( e.g., dysphoria, anxiety ) would r eflect hyper responsivity

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48 during affective responding Because these components are often subsumed under depression, it was reasoned that a componential approach might provide a better explanatory framework for patterns of responding among patients with PD and depression. There were three specific aims, each described below. Aim 1: Identifying E mo tion C omponents in PD Depression This aim sought to describe PD depression in terms of three components: apathy, anhedonia and negative affect. To address this aim, we first used confirmatory factor analysis to extract these distinct constructs from a broad battery of mood measures administered to nondemented PD patients (N= 95) who were screened f or depression based on DSM IV criteria. Next, we determined the relative loadings of these three components (apathy, anhedonia, negative affect) on a secondorder factor that indicated global affective disturbance. Finally, we examined how well each of the three component factor scores could accurately classify PD patients as being depressed or nondepressed using discriminant function analysis. Hypotheses and p redictions The overall hypothesis was that apathy is the prominent neuropsychiatric feature of PD in general and is not specific to depression, whereas negative affect is most strongly contributory to PD depression. Based on this hypothesis, we predicted that apathy would load most highly onto the global affective distu rbance factor and that negative affect would contribute most to the discrimination of PD depression. Aim 2: Patterns of Emotion Psychophysiology in PD Depression This aim sought to determine whether PD patients with depression show a pattern of muted emo tional reactivity similar to that previously described by Dichter and

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49 Tomarken (2008) in individuals with major depression (but without PD). To address this aim, we administered an emotion psychophysiology task that was directly modeled after that of Dicht er and Tomarken (2008). In this task, a series of expectancy cues (positive, negative, neutral) were shown briefly and then followed by the presentation of an emotional or neutral picture. Acoustically elicited startle eyeblink responses were obtained duri ng two temporal epochs: the anticipation phase (i.e., following presentation of the cue but before the picture) and the perception phase (i.e., during picture viewing). To ensure that obtained effects would be specific to depression in PD, rather than the Parkinson disease state per s, we also examined the performance of a group of nondepressed PD patients and a group of nondepressed healthy controls. H ypotheses and p redictions The primary hypothesis was that clinical depression in PD is similar to that described in individuals without PD and involves emotional context insensitivity (Rottenberg, 2007). Based on this hypothesis and previous findings with depressed individuals without PD (e.g., Dichter & Tomarken, 2008), we made the following predictions regarding patterns of startle reactivity by each of the participant groups. These predictions are depicted graphically in Figure 31. PD patients with depression would exhibit muted modulation of the startle eyeblink reflex during both the anticipation an d perception epochs of the emotion psychophysiology task. Specifically, startle eyeblink magnitude was expected to be blunted during the anticipation phase for both negative and positive conditions (i.e., responses similar t o the neutral condition) D uring the perception phase, startle eyeblink magnitude was expected to be similar during the viewing of all three pictures types (i.e.,

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50 negative, neutral, positive). That is, responses were expected to be blunted during the viewing of negative pictures and enhanced during the viewing of positive pictures Healthy controls would exhibit potentiation of startle following positive and negative valence cues, as compared to neutral cues, during the anticipatory phase (i.e., a quadratic pattern). During the perception phase, healthy controls were predicted to exhibit a linear pattern of startle responding. Specifically, healthy controls would demonstrate startle potentiation during the viewing of negative pictures (relative to neutral pictures), and startle reduction during the viewing of positive pictures (relative to neutral pictures). These predictions were made based on numerous prior studies examining emotionmodulated startle responding during anticipation and perception in healthy adults populations. PD patients without depression would exhibit quadratic modulation of the startle eyeblink reflex during the anticipation phase but would not exhibit linear modulation of the startle eyeblink reflex during the perception phase of the emotion psychophysiology task. Spe cifically, startle eyeblink magnitudes during the anticipation of both negative and positive conditions would be larger than those during the neutral condition. However, this quadratic pattern was expected to be less robust than that seen in healthy controls This prediction was made because PD is associated with neuropathology in both the amygdala and the VTA, which are the two regions hypothesized to mediate normal startle potentiation during the anticipation of emotional pictures and because previous studies have shown partial disruption of startle eyeblink during the perception of emotional pictures. Because i t was hypothesized that limbic neuropathology is less pronounced in nondepressed PD patients, as compared to

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51 depressed PD patients it was predict ed that a quadratic pattern of startle modulation would be detectable D uring the perception phase, a lack of startle potentiation during the perception of negative pictures was expected, based on two previous pictureviewing studies conducted in our labor atory (Bowers et al., 2006; Miller, Okun, Marsiske, Fennell, & Bowers, 2009). Specifically the non depressed PD group was not predicted to show enhancement of startle when viewing negative pictures but was predicted to show reduction of startle w hen viewi ng positive pictures. Aim 3: Relation of Depression Components to Psychophysiology Variables This aim sought to test the hypothesis that depression components in PD reflect neuropathophysiological heterogeneity by investigating the relationships between the three prominent depression components and emotionmodulated startle psychophysiology. To address this aim, we examined associations between the depression components (apathy, anhedonia, negative affect) and specific psychophysiology variables indexing startle eyeblink magnitude during the anticipation or perception of emotional versus neutral pictures. Relationships among these psychophysiology variables, scores on a broad battery of self report instruments assessing affective disturbance, and the facto r scores created in Aim 1 were examined in both univariate and multivariate analyses. Hypotheses and predictions. The overall hypothesis was that the different components of depression alter different aspects of emotionmodulated startle psychophysiology. Based on this hypothesis, we predicted that different relationships would be found between the psychological constructs and the psychophysiology

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52 variables. Specific hypotheses and predictions for each of the three depression components are described below Apathy Based on the hypothesis that apathy reflects reduced arousal and/or motivation in anticipation of emotional events, it was predicted that greater apathy would be associated with deficient startle potentiation in both positive and negative conditi ons during the anticipation phase, but not during the perception phase. Anhedonia Based on the hypothesis that anhedonia reflects deficiency in translating positive stimuli into a hedonic experience, it was predicted that greater anhedonia would be associ ated with deficient startle modulation in the positive condition, but not the negative condition, during both anticipation and perception phases. Negative affect Based on the hypothesis that negative affect (e.g., dysphoria, anxiety) reflects hyper responsivity throughout the time course of affective responding to emotional stimuli, it was predicted that greater negative affect would be associated with exaggerated startle responding in all conditions. Importance of the Knowledge to be Gained A Cochrane Review concluded that there are insufficient data on the effectiveness of any therapy for the treatment of depression in PD (Ghaxi Noori et al., 2003). Similarly, there are currently no empirically validated treatments, either behavioral or pharmacologic, for PD apathy per s (KirschDarrow, Mikos, & Bowers, 2008). A major barrier to the development of effective treatment for these common and debilitating nonmotor features of PD is lack of understanding of their specific pathophysiologies. Intervention development is further limited by the paucity of objective

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53 correlates of psychological symptoms, as it is usually assessed via patient or clinician report. Differentiating the component processes of abnormal affective responding and identifying potential bio markers are important first steps toward characterizing the etiology of neuropsychiatric symptoms in PD and developing effective treatments. In addition to its potential clinical import this research is of theoretical importance in its potential to yield insights into subcortical emotion processing within normal and diseased brains.

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54 Figure 31. Aim 2 expected results. A) Anticipation, healthy controls. B) Anticipation, nondepressed Parkinsons disease (PD). C) Anticipation, depressed PD. D) Perception, healthy controls. E) Perception, nondepressed PD. F) Perception, depressed PD.

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55 CHAPTER 4 RESEARCH DESIGN AND METHODS Participants Parkinson Disease Patients Participants included 95 patients with idiopathic PD who visited the University of Florida Center for Movement Disorders and Neurorestoration and agreed to participate in a study on depression in PD. To be included, PD patients had to be between 40 and 89 years of age and meet the United Kingdom Brain Bank diagnostic criteria for idiopathic PD ( Hughes, Daniel, Kilford & Lees, 1992). These criteria require at least two of the four cardinal motor symptoms of PD: bradykinesia (i.e., slowed initiation and execution of voluntary movement), muscle rigidity, resting tremor, and postural instability. At least one of the two required symptoms must be bradykinesia. These symptoms were assessed using the motor portion of the Unified Parkinsons Disease Rating Scale (UPDRS III; Fahn & Elton, 1987) by neurologists who were fellowshiptrained in movement disorders. Eligible patients must also have demonstrated a marked improvement in motor symptoms following initiation of dopaminergic therapy. Demonstration of a positive response to dopaminergic therapy was required in order to exclude patients with Parkinson pl us syndromes (e.g., Lewy Body disease, Multiple Systems Atrophy, Corticobasal Degeneration, Shy Drager). To be included in the PD depressed group patients meeting the above criteria must also have demonstrated the presence of major or minor (unipolar) depression, as defined by DSM IV clinical and research criteria, respectively Specifically, patients must have been currently exhibiting either sad mood or loss of interest/pleasure for the majority of the day, more days than not, for at least two weeks. In addition, patients must have been exhibiting at least one

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56 (minor) or four (major) of the seven additional depressive symptoms nearly every day, including significant change in weight or appetite, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue, feelings of worthlessness or excessive guilt, indecisiveness or diminished concentration, and recurrent thoughts of death. All participants underwent an abbreviated version of the Structured Clinical Interview for the DSM IV axis 1 ( SCID; Fir st, Spitzer, Gibbon, & Williams, 1997), conducted by the author, a masters level graduate student in Clinical Psychology. Specific exclusion criteria were: 1) Co morbid neurological illness (e.g., stroke, brain tumor), 2 ) H istory of significant brain trauma due to injury or neurosurgery, 3) C linically significant medical problems other than PD (e.g., uncontrolled card iac disease or diabetes, cancer ), 4 ) History of severe psychiatric disturbance identified with the abbreviated SCID (e.g., schizophrenia, bip olar disorder), and 5) Evidence of dementia as assessed with the Dementia Rating Scale, Second edition (DRS 2; Mattis, 2001) or the Mini Mental State Exam (MMSE; Folstein, Folstein, & McHugh, 1975). The DRS 2 assesses domains of attention, initiation/perseveration, visuoconstruction, conceptualization/reasoning, and memory. There are 144 possible points, and participants were excluded if they obtained fewer than 124 points (Mattis, 2001; Porto, Caramelli & Nitrini, 2007). Due to its length, the DRS 2 was ad ministered only to participants in the psychophysiology session (Study 2), as described in the Procedures section below. For patients who participated only in the questionnaires session (Study 1), dementia was screened with the MMSE, a very brief test of m ultiple cognitive domains, including orientation, repetition, working and episodic memory, comprehension, and visuoconstruction. There are 30 possible points, and participants

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57 were excluded if they obtained fewer than 26 points (Dubois et al., 2007). An additional exclusion criterion for the PD nondepressed group was the presence of minor or major depression, as described above. No patients were excluded based on antidepressant regimen. Demographic and disease characteristics of the total PD sample (N=95) are shown in Table 4.1. The majority of patients were Caucasian of nonHispanic origin (91%), with a small number of other races and ethnicities (four patients were African American, three patients were Hispanic, one patient was Asian American, and one pat ient was Native American). On average, patients were in early to middle stages of their disease, as indicated by UPDRS III scores calculated while patients were on dopaminergic medications obtained from the UF INFORM clinical research database. All patient s were taking dopaminergic medications (e.g., levodopa, dopamine agonists). In the sample as a whole, the average apathy, depression, and anxiety symptoms were as follows. The mean Apathy Scale score was 13.0 ( Standard Deviation [ SD ] = 6.7, range 0 to 30) the mean BDI II score was 9.9 ( SD = 8.1, range 0 to 35), the mean State Trait Anxiety Inventory (STAI) state score was 35.9 ( SD = 11.1, ran ge 20 to 60), and the mean STAI trait score was 36.0 ( SD = 11.1, range 20 to 60). Of the total group of PD part icipants, 30 (32%) were taking an antidepressant at the time of assessment. Twenty of these 95 patients also participated in Study 2. Healthy Control Participants Twenty older individuals without PD were recruited from the community through advertisements and other ongoing research studies in the Cognitive Neuroscience Laboratory. Prior to participating, informed consent was obtained according to university

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58 and federal guidelines. To be included, the healthy control participants had to be between 40 and 89 years of age. Individuals were excluded if they met any of the above exclusion criteria for the PD non depressed group or had a history a movement disorder No participants were excluded based on antidepressant regimen. Of the 20 control participants, 12 were men and 8 were women. Control participants ranged in age from 54 to 85 years ( mean [ M ] = 72.44, SD =8.00). The majority of patients were Caucasian of nonHispanic origin (95%), and one participant was African American. Average apathy, depression and a nxiety symptoms in the healthy control group were as follows. The mean Apathy Scale score was 7.9 ( SD = 3.4, range 3 to 18), and the mean BDI II score was 3.3 ( SD = 3.1, range 0 to 12). The mean STAI state score was 25.0 ( SD = 6.2, rang e 20 to 43), and t he mean STAI trait score was 27.5 ( SD = 5.3, range 20 to 38). Of the total group of healthy control participants, only one participant (5%) was taking an antidepressant at the time of assessment. Procedure Overview of Design The overall goal of this p rospective study was to characterize relationships between specific components of depression and psychophysiological responding in PD patients. Two studies were completed. The first study (Study 1; Questionnaires) involved the entire sample of PD patients (N = 95) and examined the relationships between PD depression and the components of apathy, anhedonia and negative affect. The second study (Study 2; Psychophysiology) involved a subset of the PD sample (N =

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59 30) as well as the group of healthy controls (N = 20). This study examined the relationship between PD depression and its components to psychophysiology variables. General Procedure Patients with PD were recruited from the UF Center for Movement Disorders and Neurorestoration outpatient Neurology clinic, and healthy controls were recruited from the community or ongoing research projects in the Cognitive Neuroscience Laboratory. Patients underwent testing for Study 1 on the day they were recruited in a clinic room at the Shands Medical Plaza or on an ag reedupon testing date at the Cognitive Neuroscience Laboratory in the McKnight Brain Institute. Healthy controls underwent all testing at the Cognitive Neuroscience Laboratory. Participants provided written informed consent followed by a clinical history. Patients were tested while on their antiparkinsonian medications. All participants complete d the screening procedure, and pending clearance, completed a battery of psychological measures (Study 1). Patients who completed Study 1 at the outpatient clinic and who agreed to participate in the psychophysiology paradigm (Study 2) scheduled an appointment at the Cognitive Neuroscience Laboratory within 2 weeks. During both sessions, breaks were taken between tasks, and the participant s were encouraged to request additional breaks as necessary. Any psychological or physical discomfort (due to tremor, test anxiety, etc) were addressed by the test administrator, a psychologist in training who has had intervention experience with cognitive and behavioral management o f physical a nd psychological difficulties.

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60 An overview of the study design, which total ed approximately two hours (Study 1: 30 minutes; Study 2: 1.5 hours) in d uration over the course of either one or two sessions, is provided in Figure 41 Study 1: Psy chometric Characterization of PD Depression Screening. The screening process was conducted to ensure that PD patients and healthy controls met inclusion criteria and no exclusion criteria. It included administration of commonly used measures of general cognition and psychiatric status. After informed consent was obtained from the patient, dementia was screened with the widely used MMSE (Folstein, Folstein, & McHugh, 1975). Study 2 participants were further screened with the DRS 2 ( Mattis, 2001) at the Cognitive Neuroscience Laboratory. Exclusion from the study by failing the dementia screen was determined by a score on the MMSE < 26 (Dubois et al., 2007) or a score on the DRS 2 < 124 (Mattis, 2001; Porto, Caramelli & Nitrini, 2007). (2) Psychiatric disorder s were screened using an abbreviated version of the SCID ( First, Spitzer, Gibbon, & Williams, 1997). The presence of severe psychiatric disturbance (e.g., schizophrenia, bipolar disorder), which merited exclusion from the study, was not identified in any o f the participants. Next, a medical history was taken to verify and determine significant changes from any registered data (e.g., medication change, recent stroke, subjective memory complaints) and to determine whether the patient was in sufficient physical health to complete the study. Information gathered during this process merited exclusion from the study if exclusion criteria were met. For PD patients, information on motor functioning was obtained from the UF INFORM clinical research database.

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61 Psychological measures. Psychological symptoms of interest were quantified using well validated self report or structured interview measures. General information about these scales and their subscales is displayed in Table 42. Multiple measures were chosen to index each of the three constructs in order to allow for an examination of latent factors. Apathy measures. The Apathy Scale (AS; Starkstein et al., 1992) was chosen to measure apathy in this study due to its being the only scale recommended for use in PD b y a Movement Disorder Society (MDS) task force on apathy and anhedonia rating scales in PD (Leentjens et al., 2008b). The AS was developed for use in PD patients as an abridged and modified version of the Apathy Evaluation Scale (Marin, Biedrzycki, & Firin ciogullari, 1991). It has been shown to have good face validity, internal consistency, inter rater reliability and test retest reliability, although the latter two characteristics were originally assessed in a sample of only 11 PD patients (Starkstein et al., 1992). The Lille Apathy Rating Scale (LARS; Sockeel et al., 2006) was also chosen due to its being suggested for use in PD by a MDS task force (Leentjens et al., 2008b). The LARS has been shown to exhibit good convergent validity with the Apathy Ev aluation Scale, good internal consistency, four month test retest reliability, and good inter rater reliability (Sockeel et al., 2006). The sole reason why the LARS was not classified as recommended by the MDS task force was that it had not been used in PD beyond its original developers. Since the publication of these task force recommendations, Zahodne, et al. (2009) reported that the LARS demonstrated good convergent and divergent validity, as defined as significantly greater convergence with the AS than with the BDI ( Intraclass Correltion Coefficient [ICC] = .75 vs. .62; p <.05)

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62 respectively). Compared to the AS, the LARS may also be more sensitive to change (Fernandez et al., 2010). Anhedonia measures. The SnaithHamilton Pleasure Scale (SHPS; Snaith et al., 1995) was chosen due to its recently being suggested for use in PD by a MDS task force on apathy and anhedonia rating scales in PD (Leentjens et al., 2008b). While there has not been an explicit validation study of the SHPS in a PD population, it has been shown to have good face validity, internal consistency, item total correlation, and test retest correlation in nonPD samples (Snaith et al., 1995). It is the most widely used measure of anhedonia in PD, and it has be en shown to be sensitive to changes in hedonic tone in that population (e.g., Lemke, Brecht, Koester, Kraus & Reichmann, 2005; Witt et al., 2006). The only other anhedonia scales assessed by the Movement Disorder Society (MDS) task force on apathy and anhe donia rating scales in PD were the Chapman Scales for Physical and Social Anhedonia (Chapman, Chapman, & Raulin, 1976). These scales were not suggested or recommended for use in PD because of low face validity, high overlap with the construct of apathy, and the sensitivity of many items to personal opinions, preferences and habits (Leentjens et al, 2008). Furthermore, they were found be impractical in the only study cited as having used them in PD (Isella et al., 2003). For these reasons, the Chapman scales were not used in this study. The Temporal Experience of Pleasure Scale (TEPS; Gard et al., 2006) was chosen for use in this study based on its having exhibited good i nternal consistency

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63 Consummatory subscale, respectively), good test retest reliability (r = .81, .80, and .75 for total score, Anticipatory subscale, and Consummatory subscale, r espectively), and good convergent and divergent validity when compared with multiple measures (Gard et al., 2006). Further, the TEPS demonstrated a clear, twofactor structure in factor analyses conducted on separate samples (Gard et al., 2006). Because the TEPS was validated in collegeaged samples, it was modified in a recent study involving PD patients and healthy older adults (Jordan et al., 2010). In that study, three of the 18 items were changed in order to ensure that all items would be relatable for older adults living in Florida. These changes were also upheld in the present study. Specifically, item 11 from the Anticipatory subscale (i.e., When Im on my way to an amusement park, I can hardly wait to ride the roller coaster) was changed to When Im on my way to my grandchildrens house, I can hardly wait to see them. Items 9 and 13 from the Consummatory subscale (i.e., I love it when people play with my hair and I appreciate the beauty of a fresh snowfall) were changed to I love it when peo ple rub my back and I appreciate the beauty of a colorful sunset, respective Negative affect measures. Watson and Clark (1984) define the construct of negative affect as the disposition to experience aversive emotional states. Negative affect encompas ses dysphoria, anxiety, and irritability, among others. In the present study, three measures of negative affect were chosen in order to broadly capture all of these components of negative affectivity. The Negative subscale of the Positive and Negative Affe ct Schedule (PANAS; Watson, Clark & Tellegen, 1988) was chosen due to its having been extensively employed previously and its purported ability to index the

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64 subjective components of the general biobehavioral system of withdrawal (i.e., the behavioral inhibition system) (Watson et a l., 1999). While there has not been an explicit validation study of the PANAS in a PD population, the Negative subscale of the PANAS with measures of depression, stress and anxiety, and high construct validity, as assessed with factor analysis (e.g., Crawford & Henry, 2004). The revised Spielberger State Trait Anxiety Inventory (STAI Y; Spielberger, 1983) was chosen to index anxiety based on its recommendation for use in PD by a MDS task force on anxiety rating scales in PD (Leentjens et al., 2008a). While there has not been an explicit validation study of the STAI Y in a PD population, it has been shown to have good internal consistency, satisfactory test retest reliability for the trait questionnaire, and concurrent validity with multiple anxiety scales (Spielberger, 1983). The Beck Depression Inventory, Second Edition (BDI II; Beck, Steer & Brown, 1996) was chosen to measure depressive symptoms based on its recent rec ommendation for use in PD by a MDS task force on depression rating scales in PD (Schrag et al., 2007). That review reported that the BDI exhibited good sensitivity and specificity as well as sensitivity to change in PD. Unlike other recommended scales (i.e ., Hamilton Depression Scale, Montgomery Asberg Depression Rating Scale), the BDI was reported to be weighted more toward psychological symptoms of depression, as opposed to somatic symptoms. This property was desirable, as the present study was interested in parsing cognitiveaffective symptoms of depression rather than physical symptoms. The BDI has been widely used in PD, and it has been shown to demonstrate good internal consistency, test retest reliability, concurrent and discriminant validity, and

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65 sen sitivity and specificity in PD (see Schrag et al., 2007 for a review). Furthermore, its reliability and validity compared to a DSM IV diagnosis of major depression is superior to that of the Hamilton Depression Scale in PD (Schrag et al., 2007). Because the BDI II includes items assessing symptoms of apathy and anhedonia, the total score was not used as an indicator of negative affect in the present study. Rather, a subscore calculated as the total of 11 items indexing dysphoric mood (i.e., items 2, 3, 5, 6 7, 8, 9, 10, 12, 14, 17) was used. This subscore reflecting dysphoria and negativity was identified in a recent confirmatory factor analysis of items from the AS and the BDI II that included 161 nondemented patients with idiopathic PD (KirschDarrow, 2009). Study 2: Psychophysiology General procedure Participants were seated in a straight backed, cushioned chair with armrests that was located in a soundattenuated and electrically shielded 12 x 12 room in the Cognitive Neuroscience Laboratory locat ed within the McKnight Brain Institute. Standardized lighting was ensured with a dimmer switch, which was used to light the room to the same level (40 watts) across all participants. Located on a table approximately two feet in front of the seated participant was a 21 inch video monitor on which visual stimuli were displayed. During the testing session, the experimenter monitored the participant via audio monitor. Each experimental session began with presentation of 12 unprimed startle trials (see below), f ollowed by the emotionmodulated startle task (see below). The latter task involved presentation of a visual cue stimulus that was presumed to modify motivational state by indicating the valence of an

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66 upcoming picture stimulus. Startle eyeblink responses w ere elicited during the anticipation period (immediately following the cue) or during actual picture viewing. Stimuli. Standardized emotional and neutral pictures were taken from the International Affective Picture System (IAPS; Lang, Bradley & Cuthbert, 2001). Pictures were chosen on the basis of their published affective valence and arousal ratings. Positive and negative pictures were selected on the basis of extreme normative ratings of valence separately for male and female participants. Average normati ve valence and ar ousal ratings of the selected I A P S pictures are shown separately for male and female picture sets in Table 4.3. Note that for valence ratings, one corresponds to extremely unpleasant and nine corresponds to extremely pleasant. Normative valence ratings of neutral pictures are approximately midway between unpleasant and pleasant pictures. There were no differences between the 18 positive and 18 negative pictures in normative ratings of valence intensity or arousal for either the male pictur e set (absolute valence: t (34) = 1.36; p = .18; arousal: t (34) = 0.24; p = .81) or the female picture set (absolute valence: t (34) = 1.35; p = .19; arousal: t (34) = 0.07; p = .94). In addition, there were no differences in normative ratings of valence i ntensity or arousal for negative pictures used in the male and female picture sets (absolute valence: t (34) = 0.21; p = .84; arousal: t (34) = 0.56; p = .54) or for positive pictures used in the two picture sets (absolute valence: t (34) = 0.36; p = .72; a rousal: t (34) = 0.88; p = .38). S tartle paradigm Two surface Ag AgCl electrodes were positioned under each of the participants eyes to record electromyography (EMG) activity from the orbicularis oculi muscles. Startle eyeblink responses were elicited by single, 50ms bursts of white noise (95db, instantaneous rise time) delivered binaurally through stereo headphones.

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67 Digital sampling of the EMG signals occurred at the rate of 1000 Hz and began at offset of the white noise (startle stimulus) and continued for 500ms. Physiologic signals were amplified (30,000 gain), and frequencies < 90 and > 1000 Hz were filtered using Coulbourn bioamplifiers. The raw signal was rectified and integrated using a Coulbourn Contour Following Integrator with a time constant of 200ms. This information was sent to a Coulbourn A/D board interconnected with a computer. Baseline session Each session began with a baseline session, during which 12 acoustic startle probes were delivered in the absence of any visually presented stimuli (unprimed startles). Inter trial intervals during the baseline session were random and ranged from six to eight seconds. Participants were instructed to remain relaxed but alert with their eyes open throughout the duration of the baseline session, which lasted approximately two minutes. Emotionmodulated startle session Immediately following the baseline session, task instructions were read from a standardized script, and all participants were further familiarized with the task in a brief, standardized, three trial practice session with no acoustic startle probes. Additional explanation from the experimenter was provided when requested by the participant. During the experimental task, motivational state was manipulated by presenting a valence cue (i.e., plus sign, minus sign, or open circle) followed by an emotional or neutral picture. During the experiment, the experimenter transcoded participants verbal responses (i.e., valence and arousal ratings) and then immediately initiated a new trial. No motor r esponses were required during this task. As shown in Figure 42, each trial began with the twosecond presentation of a cue indicating the valence of the forthcoming picture. A plus sign indicated positive

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68 valence, a minus sign indicated negative valence, and an open circle indicated neutral valence. After cue offset, there was a fixed, four second inter stimulus interval ( anticipation phase) that preceded onset of the picture stimulus. The picture stimulus remained on the screen for six seconds ( perceptio n phase). Of note, the valence of the picture content always corresponded to the valence of the cue. Two seconds following picture offset, a static picture version of the self assessment manikin (SAM; Bradley & Lang, 1994) was presented, which participant s used to separately rate valence and arousal ratings on 19 scales. Participants spoke their valence and arousal ratings aloud, and ratings were recorded by the experimenter, who was listening from another room via audiomonitor. No motor responses were required of participants. The experiment consisted of 54 total trials. One acoustic startle probe was delivered during each of 48 trials. Startle probes were delivered during the anticipation phase on 24 trials and the perception phase on 24 different trials No trial featured more than one startle probe. Of the 24 trials per temporal phase, eight featured positive cues and pictures, eight neutral, and eight negative. Thus, each of the six cells produced by crossing the three valence conditions (i.e., positiv e, negative, neutral) by the two phases (i.e., anticipation, perception) contained eight trials. Due to gender differences in normative valence and arousal ratings, slightly different collections of picture were used with male and female participants to ensure comparable valence and arousal ratings across participants. The trials were presented in one of two, counterbalanced orders, randomized across participants. Thus, males were presented with one of two picture sets, and females were presented with one o f two slightly different picture sets, for a total of four possible picture set/order combinations. Male and female versions of each

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69 order (1 or 2) were matched for valence and viewing conditions. To diminish the predictability of the procedures, six of the 54 trials did not contain acoustic startle probes. In addition, startle probes were randomly delivered at 1800, 2000 or 2200ms into the anticipation phase or 3,500, 4000 or 4500ms into the perception phase in order to prevent participants from developing expectancy to the white noise burst. Psychophysiology Data Reduction: Data from each participant was examined visually, and trials with clear artifacts (e.g., gross distortion of waveform) were removed from subsequent analysis. An inhouse, customized Exc el macro was used to determine amplitude (i.e., peak EMG value) and latency (i.e., time between startle probe onset and peak EMG value) within 50140ms after startle probe onset and to discard trials with a peak latency outside of this range, as prior work in our laboratory and others suggests that peaks occurring outside of this time window typically reflect blinks unrelated to the startle probe itself (Miller et al., 2009). Trials with a peak amplitude more than three standard deviations above or below each participants mean magnitude for a given behavioral condition were excluded. Raw scores were converted into T scores for each participants left and right eyes separately in order to reduce inter subject variability. If no significant differences emerg ed between right and left eye startle eyeblink responses, data were combined into an average value that was weighted to reflect which eye contributed a greater number of valid trials, and this composite startle eyeblink score was used in subsequent analyses. If data from one eye were found to be invalid (e.g., in the case of equipment malfunction), only data from the valid eye were used. Only participants who had at least two valid trials for each condition were retained so that means and standard deviations

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70 could be computed separately for each condition. Critical dependent variables (DVs) were startle eyeblink amplitudes during: (1) Baseline (12 unprimed trials measured in the absence of the behavioral manipulation), (2) Anticipation (18002200ms following cue offset; 3 valence conditions), and (3) Perception (35004500ms following picture onset; 3 valence conditions). These DVs were standardized to T score metric withinpersons separately during each of these three epochs of interest. Data Analyses Specif ic Aim 1 The first specific aim sought to describe PD depression in terms of its components: apathy, anhedonia and negative affect. To address this aim, we compared a series of confirmatory factor analyses (CFAs) using maximum likelihood estimation in Mpl us Version 6.11 (Muthen & Muthen, 1998) to establish the differentiation of the three proposed depression components. Unique variances associated with each of these three components were compared by building a secondorder CFA in which a single second order factor (global affective disturbance) was allowed to predict the three first order factors (apathy, anhedonia, negative affect). Model fit was assessed with the following, commonly used statistics: chi square, A kaike Informtion Criterion ( AIC ) Root Mean Square Error of Approximation ( RMSEA ) Comparative Fit Index ( CFI ) and Tucker Lewis Index ( TLI ) Non significant and/or smaller values of chi square, AIC, and RMSEA indicate better fit. Values of RMSEA above .1 indicate poor fit, and values below .06 indicate best fit. Values of CFI and TLI that are close to 1 (particularly values above .9) indicate better fit. The relative fits of nested models were assessed using the chi square test. Full information maximum likelihood was employed to manage missing

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71 dat a, which ranged from 0% to 4% for the 11 continuous variables. Complete data were available for 84 (88%) PD participants. Using factor coefficients from the CFA, three factor scores corresponding to the three depression components (apathy, anhedonia, negat ive affect) were computed for each participant. We next evaluated the relative abilities of these three components to accurately classify individuals with PD as depressed and nondepressed using discriminant function analysis (DFA), in which depression (pr esent vs. absent) was the logistic dependent variable, and the three factor scores were continuous independent variables. Consistent with the componential view of affective disturbance in PD and our hypothesis that apathy is the core neuropsychiatric feat ure of PD a CFA with three first order factors was predicted to have the best fit, with apathy emerging as the core feature of global affective disturbance. This was expected in the form of significant improvements in model fit with the addition of second and third first order factors as well as a relatively higher factor loading of the apathy factor on the secondorder factor of global affective disturbance, as compared to the other first order factors. Further, it was predicted that negative affect would contribute most to the discrimination of PD depression, followed by anhedonia and apathy This was expected in the form of decreasing magnitudes of standardized canonical discriminant function coefficients across the three components of negative affect, anhedonia and apathy. Specific Aim 2 The second specific aim of this study was to characterize the chronometric affective responding of PD patients with depression using psychophysiology. First,

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72 participants were stratified into groups based on the presenc e or absence of PD and depression. The PD D group comprised depressed PD patients. The PD ND group comprised nondepressed PD patients. Separate group (PD D, PDND, control) x valence (negative, neutral, positive) analyses of variance (ANOVAs) were conducted for anticipation and perception phases. In each omnibus test, the dependent variable was startle eyeblink magnitude, standardized within subjects to T score metric. To test the a priori hypotheses regarding patterns of responding expected within eac h of the three groups (reiterated below), separate repeated measures (RM) ANOVAs were conducted for the anticipation and perception phases within each group. In all RM ANOVAs, the dependent variable was startle eyeblink magnitude, standardized within subjects to T score metric, and the withinsubjects variable was affect condition (negative, neutral, positive). For the anticipation phase, a quadratic contrast tested whether each group exhibited the typical curvilinear pattern of startle modulation across th e three picture types. For the perception epoch, a linear contrast tested whether each group exhibited the typical linear pattern of startle modulation across the three picture types. To further characterize response patterns within groups, pairedsample t tests were conducted, in which mean eyeblink magnitudes for the differently valenced pictures were compared separately within each group. The predicted results for each participant group can be reviewed in Figure 31. In line with previous findings, healt hy control participants were predicted to show quadratic modulation of startle during the anticipation phase and linear modulation during the perception phase. This was expected in the form of significant quadratic and linear contrasts in the anticipation and perception RM ANOVAs, respectively.

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73 Based on previous findings by Tomarken and Dichter (2008) it was predicted that PD patients with depression would exhibit muted modulation of the startle eyeblink reflex during both anticipation and perception phases. This was expected to be reflected in a nonsignificant quadratic contrast in the anticipation RM ANOVA and a nonsignificant linear contrast in the perception RM ANOVA within the depressed group. Based on our hypothesis that nondepressed PD participants possess some neuropathology in the two regions implicated in mediating startle potentiation during anticipation (i.e., amygdala, VTA), it was predicted that non depressed PD participants would exhibit mildly muted quadratic modulation during the anticipation phase (i.e., moderately elevated startle responses during both positive and negative anticipation conditions) This was expected to be reflected in a small but significant quadratic contrast within the non depressed PD group and a significant group by affect interaction in a 3 x 2 mixed ANOVA comparing startle modulation between control and PD ND groups. Based on previous research studies in our lab, n ondepressed PD participants were predicted to demonstrate blunted startle potentiation during the negative perception condition. This was expected to be reflected in a nonsignificant linear contrast in the perception RM ANOVA within the PD nondepressed group. Specific Aim 3 The third specific aim was to investigate the unique relationships between th e three depression components (apathy, anhedonia, negative affect) and emotionmodulated startle in PD. To address this aim, associations between the psychophysiology variables and the self report instruments administered to all PD participants in Study 1 were explored. In addition to variables reflecting startle eyeblink

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74 magnitude during the various conditions, we calculated indices of emotionmodulation of startle separately for positive and negative conditions at each epoch (anticipation, perception). For anticipation, these indices were calculated as the absolute value of the difference between startle eyeblink magnitudes in emotional vs. neutral conditions (i.e., positive minus neutral, negative minus neutral). For perception, this index was calculated as the absolute value of the difference between startle eyeblink magnitudes in negative vs. positive conditions. Three variables were created: positive anticipation, negative anticipation, and perception. These indices were calculated slightly differently for anticipation and perception because of different normative response patterns (i.e., quadratic modulation during anticipation, linear modulation during perception). Thus, the emotional conditions minus the neutral condition yielded the clearest index of emotionmodulated startle during anticipation, while the negative condition minus the positive condition yielded the clearest index of emotionmodulated startle during perception. We first examined correlations between scores on the psychological instrum ents and the psychophysiology variables. We next examined correlations between the three factor scores created through Aim 1 and the psychophysiology variables. Finally, to minimize expected collinearity between psychological constructs, we entered the thr ee factor scores created through Aim 1 as independent variables into four separate regression analyses, in which the dependent variables were startle eyeblink magnitudes (T scores) during each of the conditions of interest: positive anticipation, negative anticipation, positive perception, and negative perception. Consistent with previous research, it was predicted that (1) A pathy would be associated with smaller positive and negative startle eyeblink magnitudes during

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75 anticipation; (2) A nhedonia would be a ssociated with smaller positive startle eyeblink magnitudes during anticipation and larger positive startle eyeblink magnitudes during perception; and (3) N egative affect would be associated with larger startle eyeblink magnitudes in all conditions.

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76 Tab le 4 1 Characteristics of the total Parkinson patient sample Mean Standard Deviation Demographics Age 66.24 9.89 Sex (% male) 68.40 Education 15.53 2.99 Disease characteristics Years with symptoms 8.68 5.72 Years since diagnos is 6.53 4.96 UPDRS on medication 29.06 9.79 Cognitive MMSE 28.11 1.48 Psychiatric (% yes) Apathetic a 46.30 Antidepressant use b 31.60 Anxiolytic use c 21.30 History of depression d 53.68 a Defined as a score above 13 on the Apathy Scale. b Antidepressants included: selective serotonin reuptake inhibits, serotoninnorepinephrine reuptake inhibitors, bupropion, mirtazepine, trazodone, and tricyclic antidepressants. c Anxiolytics included: benzodiazepenes, meprobamate, and trazodone. Anxiolytics did not include selective serotonin reuptake inhibitors, mirtazepine, or betablockers prescribed for cardiac indications. d Here, history of depression was defined as the occurrence of a depressive episode either presently or at some point in the past. Note. UPDRS: Unified Parkinsons Disease Rating Scale; MMSE: Mini Mental State Exam.

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77 Table 42. Psychological measures Instrument Construct Description of Scale and Dependent Variables Apathy Scale (Starkstein et al., 1992) Apathy Self report questionnaire of 14 items rated on a 4point Likert type scale. Scores range from 0 to 42 Lille Apathy Rating Scale (LARS; Sockeel et al., 2006) Apathy Semi structured interview of 33 items scored yes/no or rated on a 5point Likert type scale Scores range from 36 to +36 Intellectual Curiosity Apathy (cognitive) All subscale scores range from 4 to +4 Action Initiation Apathy (behavioral) Emotion Apathy (affective) Self Awareness Apathy (social) Snaith Hamilton Plea sure Scale (SHPS; Snaith et al., 1995) Anhedonia Self report questionnaire of 14 items rated on a 4point Likert type scale. Scores range from 14 to 56 Temporal Experience of Pleasure Scale (TEPS; Gard et al., 2006) Self report questionnaire of 18 items rated on a 4point Likert type scale Consummatory Pleasure Anhedonia Subscale of 8 items. Scores range from 8 to 48 Anticipatory Pleasure Anhedonia Subscale of 10 items. Scores range from 10 to 60 Positive and Negative Affect Schedule (Watson, Clark, & Tellegen, 1988) Affect Self report questionnaire consisting of 20 affect adjectives rated on a 5point Likert type scale Positive Affect Subscale of 10 items. Scores range from 10 to 50 Negative Affect Subscale of 10 items. Scores range from 10 to 50 State Trait Anxiety Inventory (Spielberger, 1983) Affect Self report questionnaire consisting of 40 statements rated on a 4point Likert type scale State Subscale of 20 items. Scores range from 20 to 80 Trait Subscale of 20 items. Scores range from 2 0 to 80 Beck Depression Inventory II (BDIII; Beck, Steer & Brown, 1996) Depression Self report questionnaire of 21 items rated on a 4point Likert type scale. Total scores range from 0 to 63

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78 Table 4 2. Continued. Instrument Construct Description of Scale and Dependent Variables Dysphoria Affect Eleven items indexing dysphoric mood based on a confirmatory factor analysis in a sample of 161 nondemented PD patients (KirschDarrow, 2009). Total scores range from 0 to 33 Table 43 Normative ratings for selected pictures Negative Neutral Positive Male Picture Set Valence 2.25 (0.68) 4.75 (0.29) 7.48 (0.45) Arousal 6.31 (0.66) 2.47 (0.33) 6.37 (0.60) Female Picture Set Valence 2.21 (0.58) 4.93 (0.38) 7.61 (0.45) Arousal 6.19 (0 .70) 2.58 (0.34) 6.20 (0.73) Note. Ratings can range from 1 to 9.

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79 Recruitment Study 1 Procedure A. Screening Screen for dementia (DRS 2 and/or MMSE) and mood disorders (abbreviated SCID) Gather/update history and clinical data B. Psychological Measures Beck Depression Inventory, Second Edition (BDI II), Apathy Scale (AS), Lille Apathy Rating Scale (LARS), SnaithHamilton Pleasure Scale (SHPS), Temporal Experience of Pleasure Scale (TEPS), Positive and Negative Affect Schedule ( PANAS), State Trait Anxiety Inventory (STAI) Study 2 Procedure Psychophysiology: EMG measurement of startle eyeblink responses during anticipation and perception of emotional (positive and negative) and neutral pictures from the International Affective Picture System (IAPS; Lang, Bradley & Cuthbert, 1997) Figure 41. Study flow PD: Parkinson disease; MMSE: Mini Mental State Exam; DRS 2: Dementia Rating Scale, Second Edition; SCID: Structured Clinical Interview for the DSM IV axis 1; EMG: E lectromyography. 10 PD Patients with depression agreed to participate in Study 2 20 PD Patients without depression agreed to participate in Study 2 22 Healthy Controls from community advertisements, ongoing research studies, and patient spouses matched to PD patients. 110 PD Patients from outpatient Neurology Clinic of UF Center for Movement Disorders and Neurorestoratio n. 20 Healthy Controls agreed to participate in Study 2 20 Controls met inclusion/no exclusion criteria. Two excluded for medical conditions N=20. Data from controls was NOT used in Aim 1. 96 PD Patients met inclusion/ no exclusion criteria One did not complete questionnaires; 10 excluded for cognitive impairment; 4 excluded for neurological disorder other than PD. N=95.

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80 Figure 42. Trial schematic. Each trial featured either one (48 trials) or no (6 trials) acoustic startle probes. SAM: Self Assessment Mannikin; ITI: Inter trial interval

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81 CHAPTER 5: RESULTS Aim 1: Characterization of Depression i n PD Frequency of Depression Initial analyses examined the frequency of mood symptoms in the PD sample. Of the 95 patients surveyed, 27 (28%) met DSM IV criteria for either major or minor depression and were classified as belonging to the PD Depressed (P D D) group. Table 5 1 depicts how each depressed participant met diagnostic criteria for depression. For the 27 depressed participants, the distribution of sad mood or loss of interest/pleasure as a primary depression symptom was as follows: two with s ad mood only, 12 with loss of interest/pleasure only, and 13 with both sadness and loss of interest/pleasure. Three of the 27 depressed patients were characterized as having minor depression, defined using DSM IV research criteria, due to reporting only 1 3 features in addition to a primary symptom of either sad mood or loss of interest/pleasure. In all three cases of minor depression, the primary symptom was loss of interest/pleasure. The differential frequency of the presence of sad mood in cases of minor (0/3; 0%) and major (15/24; 63% 2(1) = 4.22; p < .05). Due to the lack of formal diagnostic criteria for apathy in PD, clinically significant apathy symptoms were defined as a score greater than 13 on the AS and were found in 46% of the total PD sample. Twenty three depressed (85%) and 21 nondepressed (31%) patients exhibited clinically significant apathy. Of the total PD sample (N = 95), 32% were taking an antidepressant at the time of assessment.

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82 Demographics and Disease Characteristics Table 52 presents demographic and disease information for the 95 PD patients, separated into PD D and PD ND groups. Inferential tests revealed that groups did not significantly differ on age, sex, education, disease duration, disease severity, or global cognition (MMSE). The depressed group was more likely to be taking an antidepressant and more likely to report having at least one depressive episode (i.e., feeling sad or experiencing a loss of interest/pleasure most of the day more days than not for at least two weeks) prior to their current episode (for PD D patients) or at some point in the past (for PD ND patients). There was a trend for the depressed group to be more likely to be taking an anxiolytic. Psychological Scores of Depressed and NonDepressed Patients Table 53 presents means and standard deviations for each psychological instrument separately for PD D and PD ND groups. Bolded rows represent scores or subscores for which lower scores indicate greater psychopathology. For all other tests, higher scores correspond to greater psychopathology. Compared to the PD ND group, the PD D group reported greater psychopathology across most instruments. Notably, depressed and nondepressed patients did not differ significantly on measures of emotional apathy (LARS Emotion subscale), social apathy (LARS Self Awareness subscale), or anticipatory anhedonia (TEPS Anticipatory subscale). Confirmatory Factor Analysis To determine whether the instruments indexed different psychological constructs representing apathy, anhedonia, and negative affect, we built a series of four CFAs of increasing complexity and compared the fit of these nested models using chi square

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83 tests. As shown in Table 54, the eleven psychological variables were forced to load on one, two or three factors, respectively, in the three first order models examined. Model fit was significantly improved with each subsequent model allowing for an additional factor (see Table 54 notes). Fit statistics of the final, three factor model met standard criteria for good fit: 2( 40) = 66.33 ( p = .0 06) ; AIC = 5276.89; CFI = .95 ; TLI = .93 RMSEA = 08 ( p = .0 7 ) ; standardized RMSEA = .09. Note that the AS was not used in these CFA models because including it in the secondorder model, which is described below, resulted in negative residual variance in a latent factor. Specifically, the AS loaded so highly on the global affective disturbance factor that the residual variance of the apathy factor could not be estimated. The next phase involved examining the relative associations betw een the three psychological constructs and overall affective disturbance. To do so, a secondorder model was built in which the three first order factors (i.e., apathy, anhedonia, negative affect) were allowed to load on a single secondorder factor (i.e. global affective disturbance). A schematic of this model with resultant standardized factor loadings for the three first order factors is presented in Figure 51. As shown in Table 55, all three first order factors loaded significantly on the secondord er global affective disturbance factor. As indexed by the standardized factor loadings, apathy loaded most highly on this factor, followed by negative affect and anhedonia. After allowing for the secondorder factor, significant residual variance remained in both negative affect (standardized estimate = .492; p < .001) and anhedonia (standardized parameter estimate = .730; p < .001) factors, but not in the apathy factor (standardized parameter estimate = .044; p < .867).

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84 Discriminant Function Analysis In order to determine the relative abilities of apathy, anhedonia and negative affect to discriminate PD depression, a discriminant function analysis (DFA) was conducted. The independent variables were the factor scores computed using factor score coefficien ts from the best fitting CFA model, and the binary dependent variable was group membership (depressed versus nondepressed PD). As shown in Table 56, the factor scores were moderately to highly correlated. Depressed patients obtained significantly higher factor scores than nondepressed patients on all three psychological constructs: apathy ( F (1, 82) = 65.76; p < .001); anhedonia: ( F (1, 82) = 8.49; p = .005); and negative affect: ( F (1, 82) = 75.19; p < .001). The DFA produced a single significant function ( 2(3) = 59.35; p < .001). Note that the separategroups covariance matrix was analyzed due to nonhomogeneity of variance/covariance (Boxs M = 16.54; F [6, 10910.17] = 2.61; p = .02) in order to minimize the risk of overclassification in to groups with greater dispersion. Examination of the standardized canonical discriminant function coefficients revealed that the negative affect component contributed most to the function (estimate = .628), followed by apathy (estimate = .512) and anhedonia (estimate = .048). Classification accuracy of the discriminant function was well above chance (89.3%). As calculated from the classification table (see Table 57), sensitivity and specificity were .87 and .96, respectively. Summary of Aim 1 Results T aken together, the results from Aim 1 best supported a componential model in which affective disturbance in PD is separated into three distinct components indexing

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85 apathy, anhedonia and negative affect. This componential model had better statistical fit th an more simplified models. The apathy factor exhibited the highest loading on the second order global affective disturbance factor. In a DFA in which factor scores representing apathy, anhedonia and negative affect were used to discriminate PD depression, it was negative affect that contributed most to the discrimination. These results supported our a priori hypotheses that affective disturbance in PD can result in separable components of apathy, anhedonia and negative affect and that while apathy is the core feature of general affective disturbance in PD, negative affect is most specific to PD depression. Aim 2: Startle Psychophysiology Participant Characteristics Table 5.8 compares characteristics of the three groups of participants healthy controls, PD ND and PD D in the psychophysiology paradigm (Study 2). As shown, all three groups were well matched for age, education, cognitive status and sex distribution. Nondepressed PD patients did not differ from healthy controls in the proportion of indivi duals in each group who were apathetic (i.e., AS > 14) or reporting a past depressive episode (i.e., previous twoweek period of sadness or loss of interest/pleasure not attributable to bereavement). Nondepressed PD participants were more likely to be tak ing an antidepressant medication than were control participants, and there was a trend for nondepressed PD participants to be more likely to be taking an anxiolytic medication. Depressed and nondepressed PD patients were well matched for self reported duration of PD symptoms and time since PD diagnosis. There were no significant differences in the proportions of patients in each group taking an

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86 antidepressant or anxiolytic medication. Compared to nondepressed patients, depressed PD patients were more lik ely to be apathetic and to have reported a past depressive episode. Table 59 presents participants scores on the psychological measures. As shown, nondepressed PD patients did not differ from healthy controls in severity of depressive symptoms (i.e., B DI II), apathy (i.e., AS), trait anxiety (i.e., STAItrait), anticipatory or consummatory anhedonia (i.e., TEPS), or negative affect (i.e., PANAS Negative). Compared to healthy controls, non depressed PD patients evidenced greater cognitive apathy (i.e., LARS Intellectual Curiosity subscale), state anxiety (i.e., STAI state), and gl obal anhedonia (i.e., SHPS), as well as less positive affect (i.e., PANAS positive). Compared to nondepressed PD patients, depressed patients exhibited greater psychopathology on all instruments except emotional apathy (i.e., LARS Emotion subscale), social apathy (i.e., LARS Self Awareness subscale), and anhedonia (i.e., TEPS). There were trends for depressed PD patients to report more global anhedonia (i.e., SHPS) and less posit ive affect (i.e., PANAS Positive), as compared to nondepressed PD patients. Startle Eyeblink Responses on Baseline (Unprimed) T rials Valid t rials Fewer than the predetermined minimum number of two (out of twelve possible) valid trials during the unpr imed period were identified for one eye of two control participants, four PD ND participants, and one PD D participant. For these participants, mean amplitudes and latencies for this period were calculated using data from one eye only. For all other partic ipants, these variables were calculated as the weighted average of data from both right and left eyes. Table 510 presents the mean

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87 numbers of valid trials for each group separately for each condition. A oneway ANOVA revealed no significant differences in the number of valid unprimed trials between the groups ( F (2,47) = 2.40; p = .102). Results. Table 511 displays mean latencies (in milliseconds) and mean raw amplitudes (in microvolts) on valid trials for each of the three groups. Two separate oneway AN OVAs, in which the dependent variable was either latency or amplitude and the independent variable was group (Control, PD ND, PDD), revealed no significant differences in mean amplitude or latency between the groups during the unprimed trials (latency: F ( 2,47) = 0.05; p = .95; amplitude: F (2,47) = 0.01; p = .99). Startle Eyeblink Responses on Emotion Picture Trials Valid t rials A maximum number of eight trials was available for each affect condition (negative, neutral, positive) during each of the two phases (anticipation, perception). During the a nticipation phase, three Control participants and one PD ND participant had fewer than the predetermined minimum number of valid trials per affect condition for the left eye. For these participants, mean star tle eyeblink amplitudes and latencies were calculated for the right eye only. For all other participants, these variables were calculated as the weighted average of activity from the left and right eyes. During the p erception phase, two Control participants and three PD ND participants evidenced fewer than two valid trials per affect condition with the left eye, resulting in use of right eyeblink data only. Two additional PD ND participants were completely excluded from analyses during the perception phase due to neither eyes displaying an adequate number of valid trials. Table 510 displays the mean number of

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88 valid trials for each affect condition during the anticipation and perception phases separately for the three groups. Six separate oneway ANOVAs re vealed that the groups did not differ significantly in the number of valid trials for any condition ( all p s > .06 ). Table 511 displays mean latencies (in millivolts) and raw amplitudes (in microvolts), separated by group and condition. There were no significant differences in raw eyeblink amplitudes between groups during any condition (all p s > .1). However, control participants demonstrated significantly longer latencies during the perception of negative pictures than did PD participants ( p = .03). Ant icipation phase r esults A 3 x 3 mixed ANOVA, in which the dependent variable was mean eyeblink amplitude (T score), the withinsubjects variable was affect condition (negative, neutral or positive), and the betweensubjects variable was group (Control, PD ND, PDD), revealed only a main effect of affect ( F (2,94) = 4.47; p < .0 5; p 2 = .09). This effect reflected a significant quadratic contrast ( F (1,47) = 4.21; p < .05; p 2 = .08). There was also a significant linear contrast, as the largest eyeblink responses were exhibited during the anticipation of negative pictures ( F (1,47) = 4.671; p < .05; p 2 = .09). There was no significant main effect of group ( F (2,47) = 0.21; p p 2=.01) or a group by affect interaction ( F (4,94) = 0.73; p p 2 = .03). Despite the lack of a group by interaction in the omnibus test involving all three groups, specific patterns of startle reactivity within each group were examined in order to investigate a priori predictions (see Figure 31). To do so, separate RM ANOVAs were conducted for each group. In each analysis, affect (negative, neutral positive) was the withinsubjects variable, and startle eyeblink amplitude in T score metric was the

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89 dependent variable. Mean T scores and the results from these analyses are displayed in Table 512. Results are displayed graphically in Figure 52. Cont rol participants In line with previous studies of healthy individuals, we predicted that control participants would evidence a curvilinear pattern of startle eyeblink responding during the anticipation phase. Consistent with this prediction (see Table 51 2), the quadratic contrast was significant for the control group. On average, control participants evidenced larger startle eyeblink responses during the anticipation of negative and positive pictures than during the anticipation of neutral pictures. Eleven (55%) of the 20 participants in the control group evidenced numerically larger startle eyeblink responses during both negative and positive conditions, compared to the neutral condition. Follow up pairedt tests revealed that compared to the neutral con dition, startle eyeblink responses were significantly larger during the anticipation of negative pictures ( t (19) = 3.03; p = .007 ). There was a trend for startle eyeblink responses to be larger during the anticipation of negative pictures, as compared to positive pictures ( t (19) = 2.00 ; p = .0 60). The difference between startle eyeblink responses during the anticipation of positive versus neutral pictures was not significant ( t (19) = 0.83; p = .42). Thus emotional potentiation of startle during anticipati on was more prominent for negative pictures than for positive pictures. Non depressed PD participants. Because it was predicted that nondepressed PD participants would evidence a curvilinear pattern of startle eyeblink responding during the anticipation phase that was less robust than that shown in healthy adults, a 3 x 2 mixed ANOVA was conducted. The dependent variable was mean eyeblink

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90 amplitude (T score), the withinsubjects variable was affect condition (negative, neutral or positive), and the betweensubjects variable was group (Control, PD ND). This analysis revealed only a main effect of affect ( F (2,76) = 7.09; p p 2 = .16). This effect reflected a significant quadratic contrast ( F (1,38) = 8.32; p < .01; p 2 = .18). There was also a significant linear contrast, as the largest eyeblink responses were exhibited during the anticipation of negative pictures ( F (1 ,38) = 6.15; p < .05; p 2 = .14). There was no significant main effect of group ( F (1,38) = 0.12; p p 2=.00) or a group by affect interaction ( F (2,76) = 0.07; p p 2 = .00). Within the PD ND group, there was a trend for a quadratic contrast, as shown in Table 512. Specifically, PD ND participants tended to have larger startle eyeblink responses during the anticipation of negative and positive pictures than during the anticipation of neutral pictures. Follow up pairedt tests revealed that the a mplitude of startle eyeblink responses did not differ significantly during the anticipation of negative versus positive pictures ( t (19) = 1.53 ; p = 143). Compared to the neutral condition, startle eyeblink responses were significantly larger during the anticipation of negative pictures ( t (19) = 2.57; p = .02). Sta rtle eyeblink responses were not significantly different during the anticipation of positive versus neutral pictures ( t (19) = 0.59; p = .56). Thus emotional potentiation of startle during antici pation was more prominent for negative pictures than for positive pictures. Nine (45%) of the 20 participants in the PD ND group evidenced numerically larger startle eyeblink responses during both negative and positive conditions, compared to the neutral c ondition. Depressed PD participants. Based on a previous study of startle responding during the anticipation of emotional pictures in a sample of depressed adults without PD

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91 (Dichter & Tomarken, 2008), we predicted that depressed PD participants would not evidence a curvilinear pattern of startle eyeblink responding during the anticipation phase. This prediction was supported (See Table 512). Specifically, startle eyeblink magnitude was similar during the anticipation of emotional (positive, negative) and neutral pictures. Only three (30%) of the 10 participants in the PD D group evidenced numerically larger startle eyeblink responses during both negative and positive conditions, as compared to the neutral condition. Follow up pairedt tests revealed that compared to the neutral condition, startle eyeblink responses did not differ during the anticipation of negative ( t (9) = 0.11; p = .92) or positive ( t (9) = 0.70; p = .50) pictures. Thus, depressed PD participants demonstrated emotional context insensitivi ty during the anticipation phase. Summary of anticipation phase As predicted, the PD D group evidenced an overall flattened pattern of acoustically elicited startle eyeblink responses during the anticipation phase. In contrast, quadratic patterns of s tartle responding were observed in both control and PD ND groups, though the latter was at trend level. Both groups exhibited larger acoustically elicited startle eyeblink responses during the anticipation of negative pictures, as compared to neutral pictures, and startle responses did not differ significantly during the anticipation of negative versus positive pictures. Perception phase r esults A 3 x 3 mixed ANOVA, in which the dependent variable was mean eyeblink amplitude (T score), the withinsubjects variable was affect condition (negative, neutral or positive), and the betweensubjects variable was group (Control, PD ND, PDD), revealed only a main effect of affect ( F (2,90) = 6.45; p < .01; p 2 = .13). This effect reflected a significant linear contrast ( F (1,45) = 13.13; p = .001; p 2

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92 = .23). There was no significant main effect of group ( F (2,45) = 0.09; p p 2=.00) or a group by affect interaction ( F (4,90) = 0.98; p p 2 = .04). Despite the lack of a group by interaction in the omnibus test involving all three groups, specific patterns of startle reactivity within each group were examined in order to investigate a priori predictions (see Figure 31). To do so, separate RM A NOVAs were conducted for each group. In each analysis, affect condition (negative, neutral, positive) was the withinsubjects variable, and startle eyeblink amplitude in T score metric was the dependent variable. Mean T scores and the results from these analyses are displayed in Table 512. Results are displayed graphically in Figure 53. Control participants In line with previous studies, we predicted that control participants would evidence a linear pattern of startle eyeblink responding during the perception phase. Consistent with this prediction (see Table 512), the linear contrast was significant for the control group. Specifically, control participants had larger startle eyeblink responses during the perception of negative pictures and smaller startl e eyeblink responses during the perception of positive pictures, as compared to neutral pictures, on average. Five (25%) of the 20 participants in the control group evidenced largest startle eyeblink responses during the perception of negative pictures and smallest startle eyeblink responses during the perception of positive pictures. Follow up pairedt tests revealed that startle eyeblink responses were significantly larger during the perception of negative pictures than during the perception of positive pictures ( t (19) = 2.47; p = .02). Comparisons involving neutral condition were not significant.

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93 Non depressed PD participants. Based on previous findings from our laboratory it was predicted that PD ND participants would not evidence startle potentiation to negative pictures during the perception phase. This prediction was supported in that there was a nonsignificant linear contrast (See Table 512). Specifically, there were no differences in the size of startle eyeblink responses during the perception of emotional and neutral pictures. Three (17%) of the 18 participants in the PD ND group evidenced largest startle eyeblink responses during the perception of negative pictures and smallest startle eyeblink responses during the perception of positive pict ures. Depressed PD participants. We predicted that PD D participants would evidence emotional context insensitivity during the perception phase. This prediction was not supported. As shown in Table 512, the linear contrast was significant for the PD D gro up. Specifically, PD D participants evidenced larger startle eyeblink responses during the perception of negative pictures and smaller startle eyeblink responses during the perception of positive pictures, as compared to neutral pictures. Five (50%) of the 10 participants in the PD D group evidenced largest startle eyeblink responses during the perception of negative pictures and smallest startle eyeblink responses during the perception of positive pictures. Follow up pairedt tests revealed that startle ey eblink responses were significantly larger during the perception of negative pictures than during the perception of positive pictures ( t (9) = 3.98; p < .01). There was also a trend toward larger startle eyeblink responses to negative pictures compared to neutral pictures ( t (9) = 1.86; p = .10). Startle eyeblink responses were not significantly smaller during the perception of

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94 positive pictures, as compared to neutral pictures ( t (9) = 1.65; p = .13). An exploratory t test compared startle eyeblink responses among depressed versus nondepressed PD patients during the perception of negative pictures. There was a trend for the depressed group to exhibit larger startle eyeblink responses in the negative condition ( t (26) = 1.97; p = .06). Summary of perception phase. Results provide evidence for linear startle responding in both control and PD D groups. On average, individuals in these groups exhibited largest acoustically elicited startle responses during the perception of negative pictures and smallest acoustic ally elicited startle responses during the perception of positive pictures, as compared to neutral pictures. In contrast, the PD ND group evidenced an overall flattened pattern of startle responding and no evidence for modulation by emotional context. Subjective Ratings of Pictures Group differences in valence and arousal ratings. In order to determine whether there were differences between the groups in subjective ratings of the valence or arousal of the pictures, separate oneway ANOVAs were conducted for each of the picture types (negative, neutral, positive). In each analysis, the betweensubjects variable was group, and the dependent variable was either trial by trial valence or arousal ratings. Due to computer error, arousal data were not available for three control participants, five PD ND participants, and one PD D participant. Table 513 presents average valence and arousal ratings for the three affect conditions separately by group. As shown, there were no significant differences between the groups in subjective ratings of valence or arousal for any of the three affect conditions.

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95 Subjective classification of pictures. In order to explore whether differences in participants subjective experiences of the pictures affected the results, the stimulus pictures were re classified into the three affective categories using a participants unique valence ratings. Specifically, valence ratings of one to three corresponded to negative, four to six corresponded to neutral, and seven to nine corresponded to positive. The overlap between normative and subjective classifications can be observed in Table 514. Valid trials. The number of trials av ailable for each affect condition (pleasant, unpleasant, neutral) depended on individual participants ratings. Three control participants, nine PD ND participants, and one PD D participant had fewer than two valid trials per affect condition for one eye, and mean startle eyeblink amplitudes and latencies were calculated for the valid eye only. An additional two participants in each of the three groups were excluded from these analyses due to a lack of the minimum number of valid trials per affect condition for both eyes. For all other participants, startle eyeblink variables were calculated as the weighted average of acti vity from the left and right eyes in T score met ric. Table 5 15 displays the number of valid trials in each affect condition separately for the three groups. Startle eyeblink responses to subjectively classified pictures. Because we had no a priori hypotheses about group differences in patterns of startle responding during subjectively classified pictures, a single 3 [Affect condition ] x 3 [Group] mixed ANOVA was conducted, and both linear and quadratic contrasts were examined. The dependent variable was m ean startle eyeblink amplitude (T score) during the perception of subjectively rated pictures The analysis revealed a significant linear contrast ( F (1,39)

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96 = 3.92; p = p 2 = .09) and a trend for an affect by group quadratic contrast ( F (2,39) = 3.10; p p 2 = .14), which can be appreciated in Figure 5 4. Mean startle eyeblink responses in each of the three conditions as well as the results from separate withinsubjects linear contrasts are shown in Table 516. Pairedsamples t tests revealed that control participants exhibited larger startle eyeblink responses during the viewing of negative pictures, as compared to both positive ( t (15) = 2.29; p = .04) and neut ral (t (16) = 2.18; p = .04) pictures. Control participants did not exhibit significantly different startle eyeblink responses during the viewing of subjectively classified positive pictures, as compared to neutral pictures ( t (15) = 0.03; p = .98). Neither PD D n or PD ND groups demonstrated differences in startle eyeblink magnitudes during the perception of negative pictures, as compared to positive or neutral pictures. However, there was a trend for the PD ND group to display smaller startle eyeblink response s during the viewing of positive pictures, as compared to neutral pictures ( t (17) = 1.79; p = .09). This comparison was not significant for the PD D group, which actually demonstrated numerically larger startle eyeblink responses during the viewing of s ubjectively classified positive pictures, as compared to neutral pictures. Effects of Antidepressants on Physiologic Reactivity in PD Depression Group As shown in Table 58, 50% of PD D participants were taking an antidepressant at the time of this study Exploratory analyses were conducted to learn whether the five individuals taking antidepressants within the PD D group differed from the five who were not taking antidepressants. Given the extremely small sample size in these analyses, results must be in terpreted with caution. Table 517 displays mean startle eyeblink responses during anticipation and perception separately for depressed PD patients

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97 taking or not taking antidepressants. Also see Figure 55 for graphical depictions. Results of 3 [Affect con dition] X 2 [Group On antidepressants, not on antidepressants] ANOVAs revealed no significant effects or interaction during the anticipation phase (i.e., affect condition: F (2,16) = 0.23; p p 2 = .03; group: F (1,8) = 1.40; p p 2 = .15; affect condition by antidepressant group: F (2,16) = 0.10; p p 2 = .08). During perception, there was a significant main effect of affect ( F (2,16) = 6.26; p p 2 = .44), reflecting a linear contrast ( F (1,8) = 14.10; p p 2 = .64). There was no main effect of group ( F (1,8) = 1.24; p p 2 = .14) or affect by antidepressant group interaction ( F (2,16) = 0.37; p p 2 = .04). Effects of Sad Mood on Physiologic Reactivity in PD Depression Group Additional exploratory analyses were carried out to investigate whether the presence of sad mood within the PD D group affected the results. As shown in Table 5.1, six PD D participants demonstrated sad mood as a primary symptom. Exploratory 3 [Affect condition] x 2 [Group Sad mood, no sad mood] ANOVAs were conducted to learn whether the six individuals reporting sad mood within the PD D group differed from the four who did not. Given the extremely small sample size in these analyses, results must be interpreted with caution. Table 517 displays mean startle eyeblink magnitudes during anticipation and perception separately for depressed PD patients with and without sad mood, which can be appreciated visually in Figure 56.There were no significant effects during anticipation (affect condition: F (2,16) = 0.12; p p 2 = .02; group: F (1,8) = 0.29; p p 2 = .04); affect condition by sad mood group: F (2,16) = 0.48; p p 2 = .06). During perception, there was a significant main effect of affect condition ( F (2,16) = 5.93; p p 2 = .43), reflecti ng a linear contrast ( F (1,8) = 13.99;

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98 p p 2 = .64). There was no main effect of group ( F (1,8) = 0.11; p p 2 = .01) or affect condition by antidepressant group interaction ( F (2,16) = 0.03; p p 2 = .00). Summary of Aim 2 Results Control participants exhibited the predicted patterns of quadratic and linear responding during the anticipation and perception phases, respectively, of the emotion psychophysiology task. Nondepressed PD patients exhibited a similar quadratic pattern of responding during anticipation but blunted startle potentiation during the perception of negative pictures. Depressed PD patients exhibited emotional context insensitivity during the anticipation phase (i.e., no emotion modulation of startle) and a linear pattern of responding during perception. Groups did not differ in subjective ratings of valence and arousal or in startle eyeblink magnitudes on unprimed trials. Aim 3: Relating Psychophysiology Variables to Depression Components The purpose of this aim was to determine whether specific depression components (apathy, anhedonia, negative affect) were differentially related to psychophysiology variables during anticipation versus perception. Our overall hypothesis was that the different components of depression al ter different aspects of emotionmodulated startle psychophysiology. We predicted that (1) Apathy would be associated with smaller positive and negative eyeblink amplitudes during anticipation; (2) Anhedonia would be associated with smaller positive eyebli nk magnitudes during anticipation and larger positive eyeblink magnitudes during perception; and (2) Negative affect would be associated with larger startle eyeblink magnitudes in all conditions.

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99 Apathy Because apathy has been linked to reductions in ar ousal and motivation, which are both necessary for the initiation of elaborative working memory rehearsal involved in generating emotional expectancy, it was hypothesized that apathy would associate with blunted startle eyeblink responding during the antic ipation of both positive and negative stimuli. This hypothesis was also consistent with evidence that the same cortical regions activated during emotional expectancy (e.g., ACC) also exhibit hypometabolism among individuals with apathy. ( Craig et al., 1996 ; Lavretsky et al., 2007; Bermpohl et al., 2006; Ueda et al., 2003). Associations involving the apathy factor score. As shown in Table 518, a medium sized (i.e., r = .30) correlation in the expected direction was not significant for the anticipation of negative pictures ( p = .11). Correlations between the apathy factor score and startle eyeblink responses in all other conditions were also nonsignificant. Table 519 presents the results from separate linear regressions in which the dependent variables wer e startle eyeblink responses (T scores) during the anticipation or perception of emotional pictures, and the independent variables were the three factor scores. As shown, none of the regressions was significant. Further, the apathy factor score was not independently associated with startle eyeblink responses in any condition. Associations involving individual psychological measures Scores on individual psychological measures of apathy (rather than factor scores) were also examined in relation to absolute and relative startle amplitudes (Tables 520 5 22). Table 520 presents a matrix of correlations between scores on the individual

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100 psychological measures and the startle eyeblink T scores (i.e., absolute and relative startle amplitudes) in the three affect conditions during the anticipation phase. As shown, one subscale score reflecting apathy was associated with several psychophysiology variables during anticipation. Reduced emotion modulation, as indexed by a smaller difference between the two affect conditions (negative and positive) and the neutral condition, was associated with higher (worse) scores on the LARS Self Awareness subscale. Scores on individual psychological measures of apathy were also examined in relation to absolute and relative startle amplitudes during perception. These correlations are shown in Tables 521 and 522. Table 21 (normative) presents a matrix of correlations when the IAPS pictures were classified into negative, neutral and positive conditions based on normative ratings. Tab le 22 (idiographic) presents this same information when the pictures were classified based on the participants own subjective ratings. As shown in Table 521, higher (worse) scores on the AS were associated with enhanced blunting of the startle eyeblink r eflex during the viewing of normatively classified positive pictures ( p = .03). As shown in Table 522, higher scores on the AS were also associated with exaggerated potentiation of the startle eyeblink reflex during the viewing of subjectively classified negative pictures ( p = .05). These associations correspond to greater emotion modulation. In contrast, higher (worse) scores on the LARS Self Awareness subscale were associated with larger startle eyeblink responses during the viewing of positive pictures ( p < .01), which corresponds to less emotion modulation.

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101 Anhedonia Unlike apathy, which refers to a motivational deficit, anhedonia refers to a hedonic deficit. Because anhedonia is characterized by abnormal neural responses to pleasant stimuli, but no t negative stimuli (Keedwell et al., 2005), it was hypothesized that anhedonia would associate with abnormal startle eyeblink responses in both anticipation and perception conditions involving positive stimuli, but not negative stimuli. Associations invol ving the anhedonia factor score. As shown in Table 518, the anhedonia factor was not significantly correlated with any of the psychophysiology variables. As shown in Table 519, linear regressions in which startle eyeblink responses in each condition were regressed on the three factor scores were also not significant. In these regressions, the anhedonia factor score was not independently associated with startle eyeblink responses during the anticipation or perception of positive pictures, or during any other condition. Associations involving individual psychological measures. Scores on individual psychological measures of anhedonia (rather than factor scores) were also examined in relation to absolute and relative startle amplitudes (Tables 520 5 22). A s shown in Table 520, none of the individual psychological measures of anhedonia were significantly correlated with startle eyeblink responses during the anticipation phase. Similarly, as shown in Table 521, none of these measures were significantly corr elated with startle eyeblink responses during the perception phase when pictures were classified as negative, neutral or positive based on normative ratings. In contrast, and as shown in Table 522, lower (worse) scores on TEPS Anticipatory subscale were significantly correlated with enhanced blunting of the startle eyeblink reflex during the

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102 perception of subjectively classified positive pictures ( p = .01), which corresponds to greater emotion modulation. Negative Affect Based on previous research linking negative affect (e.g., dysphoria, anxiety) to enhanced psychophysiologic reactivity during both the anticipation and perception of affective stimuli regardless of valence (e.g., Kaviani et al., 2004, Seignourel et al., 2007; Sabatinelli et al, 2001), it was hypothesized that negative affect would associate with hyper startle responding across conditions. Associations involving the negative affect factor. As shown in Table 518, the negative affect factor was positively correlated with the size of the dif ference in startle responding during negative versus positive picture viewing (i.e., negative positive) ( p = .04). Thus, larger differences in the extent of emotional reactivity (as indexed by this difference score) were associated with greater negative affect. The negative affect factor was also significantly associated with greater startle potentiation during the viewing of subjectively classified negative pictures ( p = .03), reflecting exaggerated reactivity during the perception of negative stimuli. As shown in Table 519, linear regressions in which startle eyeblink responses in each condition were regressed on the three factor scores were not significant. The negative affect factor score was not independently associated with startle eyeblink resp onses in any condition. Associations involving individual psychological measures. Scores on individual psychological measures of negative affect (rather than factor scores) were also examined in relation to absolute and relative startle amplitudes (Tables 5 20 5 -

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103 22). More striking relationships involving negative affect measures were noted when the affective pictures were classified based on the participants own valence ratings into negative, neutral and positive categories (Table 522). For subjectiv ely classified pictures (Table 522), larger startle eyeblink responses during negative and neutral picture viewing were associated with greater trait anxiety (i.e., STAITrait score; p = .02 and .04, respectively), higher levels of overall depression (BDI II total score; p < .01 and p = .01, respectively), and higher levels of dysphoria (BDI dysphoria subscore, see Table 42; p = .03 and p = .01, respectively). For normatively classified pictures (Table 521), there were fewer relationships involving indi vidual measures of negative affect. Greater startle reactivity (an indexed by the difference in startle amplitude during negative versus positive picture viewing) was associated with higher levels of trait anxiety (STAI Trait, p = .03). Summary of Aim 3 Results In brief, the results indicated the following: a) No relationship between the derived apathy construct and startle eyeblink responses during the anticipation phase of the psychophysiology task. However, turning to individual measures, there were negative associations between scores on the Self Awareness subscale of the LARS and the magnitude of startle eyeblink responses during the anticipation of emotional pictures, as compared to neutral pictures. Mixed results were found for the relationship b etween individual measures of apathy and emotionmodulated startle during perception; b) No relationship between the derived anhedonia construct and startle eyeblink responses involving positive stimuli; and c) No relationship between the derived negative affect construct and the absolute size of startle eyeblink responses

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104 during the psychophysiology task. However, when examining the range of startle reactivity (i.e., difference in startle magnitude between negative and positive conditions), there was a sig nificant positive relationship with negative affect, in line with predictions. Turning to individual psychological measures, evidence was found for associations between individual measures of negative affect (i.e., trait anxiety and dysphoria) and enhanced emotion modulation of startle during the perception of emotional pictures, particularly negative pictures.

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105 Table 51. Diagnostic features of depressed patients Major or minor Sad mood Loss of interest/ pleasure Weight/ appetite Sleep Psychomotor ag itation/ retardation Fatigue Worthlessness/ guilt Concentration difficulties/ indecisiveness Thoughts of death 1 Major X X X X X X 2 Major X X X X X X 3 Minor X X X 4 Major X X X X X X 5 Major X X X X X X X X 6 Major X X X X X X 7 Major X X X X X X 8 Major X X X X X X X 9 Major X X X X X X 10 Major X X X X X X X X 11 Major X X X X X X 12 Major X X X X X 13 Major X X X X X 14 Major X X X X X X X X 15 Major X X X X X X 16 Major X X X X X 17 M inor X X X X 18 Major X X X X X X X 19 Major X X X X X 20 Major X X X X X X X 21 Major X X X X X X 22 Major X X X X X X 23 Major X X X X X X X X 24 Minor X X X X 25 Major X X X X X X X X 26 Major X X X X X X X 27 Major X X X X X X X Note Bolded rows correspond to the ten participants in Study 2 (psychophysiology session).

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106 Table 52. Characteristics of depressed and nondepressed PD patients Depressed (N=27) Non depressed (N=68) p a Demographics Age 66.55 (1 0.12) 66.12 (9.87) .73 Sex (% male) 63.0 71.0 .47 Education 14.42 (3.29) 15.96 (2.78) .04 Disease characteristics Years with symptoms 8.97 (5.83) 8.56 (5.72) .70 Years since diagnosis 6.70 (4.72) 6.46 (5.08) .70 UPDRS on medication 33.59 (10.95) 27.37 (8.85) .01 Cognitive MMSE 28.12 (1.66) 28.11 (1.42) .82 Psychiatric (% yes) Apathetic b 85.2 30.9 <.001 Antidepressant use c 59.3 20.6 <.001 Anxiolytic use d 34.6 16.2 .051 History of depression 77.8 e 35.3 <.001 a Comparison carried out using the chi square test for categorical variables. b Defined as a score above 13 on the Apathy Scale. c Antidepressants included: selective serotonin reuptake inhibits, serotoninnorepinephrine reuptake inhibitors, bupropion, m irtazepine, trazodone, and tricyclic antidepressants. d Anxiolytics included: benzodiazepenes, meprobamate, and trazodone. Anxiolytics did not include selective serotonin reuptake inhibitors, mirtazepine, or betablockers prescribed for cardiac indications e For currently depressed patients, history of depression was defined as the occurrence of a depressive episode prior to the present episode. Note. PD: Parkinson disease; UPDRS: Unified Parkinsons Disease Rating Scale; MMSE: Mini Mental State Exam.

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107 Ta ble 53. Scores on the psychological scales for depressed and nondepressed PD patients Range of possible scores PD D (N=27) PD ND (N=68) p BDI II 0 to 63 19.22 (7.31) 6.15 (4.66) <.001 BDI II Dysphoria 0 to 33 7. 74 (3.91) 1.57 (2.17) <.001 AS 0 to 42 19.70 (4.73) 10.38 (5.35) <.001 LARS Total 36 to +36 12.69 (9.87) 22.42 (5.14) <.001 LARS Intellectual Curiosity 4 to 4 0.93 (1.26) 2.47 (0.74) <.001 LARS Emotion 4 to 4 1.62 (1.77) 1.99 (1.10) 551 LARS Action Initiation 4 to 4 1.48 (1.89) 2.79 (1.09) .002 LARS Self Awareness 4 to 4 2.77 (1.37) 2.97 (1.24) .514 STAI State 20 to 80 44.78 (10.17) 32.15 (9.22) <.001 STAI Trait 20 to 80 47.73 (7.16) 31.31 (8.69) <.001 TEPS Anticipa tory a 8 to 48 42.81 (8.41) 46.44 (7.28) .060 TEPS Consummatory a 10 to 60 34.85 (6.98) 39.53 (6.41) .003 SHPS 14 to 56 25.58 (4.53) 22.03 (7.39) <.001 PANAS Positive a 10 to 50 30.77 (6.45) 38.87 (6.83) <.001 PANAS Negative 10 to 50 27.69 (6.71) 17.67 (6.94) <.001 a L ower scores indicate greater psychopathology. For all other scales, higher scores indicate greater psychopathology. Note. PD: Parkinson disease; PD D : Depressed Parkinson disease group; PD ND: Non depressed Parkinson disease group; BDI I I: Beck Depression Inventory, 2nd Edition; AS: Apathy Scale; LARS: Lille Apathy Rating Scale; STAI: StateTrait Anxiety Inventory; TEPS: Temporal Experience of Pleasure Scale; SHPS: SnaithHamilton Pleasure Scale; PANAS: Positive and Negative Affect Schedule.

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108 Table 54. Standardized factor loadings in the nested first order models Model 1: 1 factor Model 2 a : 2 factors Model 3 b : 3 factors a 2(1)=85.407; p <.001 b 2(1)=41.925; p <.001 Note. LARS: Lille Apathy Rating Scale; TEPS: Temporal Experience of Pleasure Scale; SHPS: Snaith Hamilton Pleasure Scale; PANAS: Positive and Negative Affect Schedule; STAI: State Trait Anxiety Inventory; BDI I I: Beck Depression Inventory, 2nd Edition. Global affective disturbance Apathy/ Anhedonia Negative affect Apathy Anhedonia Negative affect Apathy LARS Intellectual Curiosity .644 .465 .861 LARS Action Initiation .484 .387 .613 LARS Emotion .060 .270 .242 LARS Self Awareness .092 .295 .213 Anhedonia TEPS Consummatory .400 .923 .962 TEPS Anticipatory .370 .728 .709 SHPS total .318 .770 .762 Negative Affect PANAS Negative .705 .704 .715 BDI II Dysphoria .802 .813 .814 STAI State .847 .838 .847 STAI Trait .9 61 .976 .968

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109 Table 55. Standardized factor loadings in the secondorder model Estimate SE p Global affective disturbance Apathy .989 .139 <.001 Anhedonia .514 .104 <.001 Negative affect .701 .102 <.001 Apat hy LARS Intellectual Curiosity .856 .081 <.001 LARS Action Initiation .609 .088 <.001 LARS Emotion .236 .120 <.05 LARS Self Awareness .231 .116 <.05 Anhedonia TEPS consummatory .949 .037 <.001 TEPS anticipatory .721 .057 <. 001 SHPS total .797 .049 <.001 Negative Affect PANAS Negative .701 .057 <.001 BDI II Dysphoria .816 .039 <.001 STAI State .847 .021 <.001 STAI Trait .962 .039 <.001 Note. SE: Standard Error; LARS: Lille Apathy Rating Scale; TEPS: T emporal Experience of Pleasure Scale; SHPS: Snaith Hamilton Pleasure Scale; PANAS: Positive and Negative Affect Schedule; STAI: StateTrait Anxiety Inventory; BDI II: Beck Depression Inventory, 2nd Edition. Table 56. Correlation matrix of factor scores Apathy Anhedonia Negative affect Apathy Anhedonia .517** Negative affect .776** .355* ** p <.001 p <.01 T able 57. Classification accuracy in the discriminant function analysisa Predicted Group Membership a Due to missing data, only 84 (88%) participants were classified. Original Group Membership PD D PD ND Total PD D 53 8 61 PD ND 1 22 23

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110 Table 58. Characteristics of Study 2 participantsa Control (N=20) PD ND (N=20) PD D (N= 1 0) Control v PD ND ( p) PD ND v. PD D ( p ) Demographics Age 71.35 (8.96) 67.78 (8.64) 70.06 (5.52) .208 .441 Sex (% male) 60 70 70 .507 1.00 Education 16.05 (3.03) 16.65 (2.64) 15.10 (3.60) .509 .278 Disease Years with symptoms 9.24 (6.44) 10.00 (5.55) .741 Years since diagnosis 6.09 (5.02) 9.12 (5.74) .179 UPDRS on medications 27.56 (10.35) 33.88 (15.26) .270 Cognitive MMSE 28.65 (1.39) 28.06 (1.26) 28.22 (1.86) .177 .543 DRS 2 139.65 (2.83) 13 7.09 (6.02) 138.14 (4.02) .117 .856 Psychiatric (% yes) Apathetic b 10 20 90 .376 <.001 Antidepressant use c 5 3 0 50 037 284 Anxiolytic use d 5 25 33 .077 .770 History of depression 25 35 80 e .490 .020 a Comparisons carried out usi ng chi square tests for categorical variables. b Defined as a score above 13 on the Apathy Scale. c Antidepressants included: selective serotonin reuptake inhibits, serotoninnorepinephrine reuptake inhibitors, bupropion, mirtazepine, trazodone, and tricyc lic antidepressants. d Anxiolytics included: benzodiazepenes, meprobamate, and trazodone. Anxiolytics did not include selective serotonin reuptake inhibitors, mirtazepine, or betablockers prescribed for cardiac indications. e For currently depressed patients, history of depression was defined as the occurrence of a depressive episode prior to the present episode. Note. UPDRS: Unified Parkinsons Disease Rating Scale; MMSE: Mini Mental State Exam.

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111 Table 59. Group differences on the psychological measures Control (N=20) PD ND (N=20) PD D (N=10) Control v. PD ND ( p) PD ND v. PD D ( p ) BDI II 3.03 (3.06) 4.45 (3.93) 20.90 (6.94) .308 <.001 BDI II Dysphoria 0.75 (1.12) 1.00 (1.59) 8.70 (4.06) .568 <.001 AS 7.84 (3.79) 9.35 (5.65) 19.20 (3.99) .343 <.001 LARS Total 26.65 (3.51) 23.60 (4.24) 14.80 (9.09) .018 .006 LARS Intellectual Curiosity 3.03 (0.41) 2.61 (0.64) 1.10 (1.42) .021 .003 LARS Emotion 2.20 (1.06) 1.93 (1.09) 2.00 (1.60) .423 .625 LARS Action Initiation 3.20 (0.6 2) 3.00 (0.99) 1.55 (1.86) .448 .038 LARS Self Awareness 3.75 (0.72) 3.30 (0.98) 3.30 (0.82) .106 .825 STAI State 25.00 (6.25) 30.20 (8.02) 44.80 (11.18) .028 .002 STAI Trait 27.45 (5.35) 28.75 (7.06) 47.30 (7.17) .516 <.001 TEPS Anticipat ory a 48.65 (6.73) 45.80 (5.82) 43.20 (7.98) .160 .343 TEPS Consummatory a 41.80 (6.78) 39.00 (4.91) 36.20 (5.16) .143 .133 SHPS 17.85 (3.98) 20.85 (4.39) 23.80 (4.24) .029 .073 PANAS Positive a 41.90 (3.95) 38.60 (5.42) 33.20 (6.73) .034 .074 PANA S Negative 14.25 (3.55) 16.85 (6.17) 25.80 (6.53) .111 .002 a L ower scores indicate greater psychopathology. For all other scales, higher scores indicate greater psychopathology. Note. BDI II: Beck Depression Inventory, 2nd Edition; AS: Apathy Scale; LAR S: Lille Apathy Rating Scale; STAI: StateTrait Anxiety Inventory; TEPS: Temporal Experience of Pleasure Scale; SHPS: SnaithHamilton Pleasure Scale; PANAS: Positive and Negative Affect Schedule.

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112 Table 510. Number of valid trials during the psychophysiol ogy startle task Control PD ND PD D Unprimed a 9.8 (2.6) 11.1 (1.2) 10.9 (1.6) Anticipation b Negative 5.6 (1.9) 6.0 (1.5) 6.9 (0.8) Neutral 5.4 (1.9) 6.0 (1.5) 6.9 (1.1) Positive 5.4 (2.0) 6.2 (1.6) 6.9 (0.9) Perception b Negativ e 5.9 (1.7) 5.5 (1.6) 6.5 (1.4) Neutral 5.5 (1.9) 6.0 (1.5) 6.4 (1.5) Positive 6.1 (1.6) 5.9 (1.6) 6.4 (1.4) a Out of twelve possible valid trials b Out of eight possible valid trials Table 511. Mean latencies and raw amplitudes Latencies in milliseconds Amplitudes in microvolts Table 512. Startle amplitudes in T score metric Negative Neutral Po sitive Results of planned contrast Anticipation Control 52.2 (3.6) 48.4 (3.5) 49.4 (3.3) Quadratic: F (1,19) = 5.21; p p 2 =.22 PD ND 51.8 (3.5) 48.6 (3.4) 49.5 (4.0) Quadratic: F (1,19) = 3.25; p p 2 =.15 PD D 50.4 (2.6) 50.2 (2.1) 49.6 (1.6) Quadratic: F (1,9) = 0.05; p p 2 =.01 Perception Control 52.1 (4.9) 50.0 (4.6) 48.0 (3.6) Linear: F (1,19) = 6.08; p p 2 =.24 PD ND 50.4 (3.2) 50.2 (3.2) 49.5 (3.3) Linear: F (1,17) = 0.05; p p 2 =.03 PD D 52.8 (2.9) 49.7 (2.8) 47.7 (1.9) Linear: F (1,9) = 15.84; p p 2 =.64 Note: T scores were calculated by standardizing amplit udes separately for each participant. T score mean = 50; standard deviation = 10. Control PD ND PD D Control PD ND PD D Unprimed 86.6 (8.3) 86.0 (4.7) 86.1 (7.7) 84.6 (62.8) 84.0 (42.7) 86.4 (65.5) Anticipation Negative 90.5 (10.1) 83.4 (6.9) 83.5 (7.1) 41.8 (44.4) 50.3 (35.6) 41.0 ( 22.9) Neutral 85.1 (15.7) 80.4 (9.5) 84.8 (7.1) 39.4 (45.3) 46.9 (38.1) 41.8 (21.4) Positive 91.3 (17.6) 83.8 (10.4) 83.4 (6.2) 40.9 (43.7) 49.6 (39.7) 40.7 (20.3) Perception Negative 89.7 (16.2) 83.8 (9.3) 86.7 (10.5) 42.1 (43.4) 37.7 (26.6) 44.7 (21.9) Neutral 89.8 (12.4) 83.9 (7.6) 84.0 (4.9) 37.6 (40.9) 38.4 (25.6) 39.7 (16.6) Positive 87.5 (9.2) 81.0 (7.5) 82.0 (15.7) 36.6 (39.6) 36.6 (24.7) 38.9 (19.1)

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113 Table 513. Subjective ratings of valence and arousal by group and picture type Control PD ND PD D One way ANOVA results Valence Negative 2.45 (0.98) 2.28 (1.09) 2.38 (0.94) F (2,48)=0.14; p =.87 Neutral 4.89 (0.61) 4.81 (0.87) 5.03 (0.42) F (2,48)=0.34; p =.72 Positive 6.61 (0.65) 6.65 (1.01) 6.68 (0.71) F (2,48)=0.03; p =.97 Arousal Negative 6.65 (1.10) 6.57 (1.34) 6.47 (1.62) F (2,40)=0.06; p =.94 Neutral 2.98 (1.44) 2.89 (1.07) 3.13 (1.47) F (2,40)=0.10; p =.91 Positive 5.40 (1.19) 5.46 (1.34) 5.21 (1.51) F (2,40)=0.11; p =.90 Note. ANOVA: Analysis of variance. Table 514. Percentages of normatively classified pictures Normative classificatio n Table 515. Number of valid trials for analyses using subjective picture classificationa Control P D ND PD D Negative 5.5 (2.5) 6.4 (1.9) 5.4 (2.5) Neutral 8.8 (5.1) 6.5 (2.3) 8.6 (3.4) Positive 3.7 (2.5) 3.9 (1.9) 4.7 (2.3) a Number of available trials depended on individual participants subjective valence ratings. Subjective classification Negative Neutral Positive Control Negative 80.3 10.6 1.4 Neutral 18.3 82.5 40.8 Positive 1.4 6.9 57.8 PD ND Negative 82.5 15.1 6.1 Neutral 11.6 75.4 32.4 Positive 5.8 9.5 61.5 PD D Negative 79.9 12.4 3 .4 Neutral 18.4 75.8 37.1 Positive 1.7 11.8 59.4 Totals Negative 81.1 12.8 3.7 Neutral 15.6 78.3 36.6 Positive 3.3 9.0 59.6

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114 Table 516. Startle amplitudes during the perception of subjectively classified pictures Negative Neutral Positive Results of linear contrast Control 52.97 (5.64) 48.30 (4.24) 48.37 (5.87) F (1,15)=5.26; p p 2 =.26 PD ND 49.83 (3.18) 51.49 (3.15) 48.88 (4.87) F (1,17)=0.29; p =.60 p 2 =.02 PD D 52.41 (4.06) 48.24 (2.71) 50.45 (5.09) F (1,7)=0.52; p p 2 =.07 Note. T scores were calculated by standardizing amplitudes separately for each participant. T score mean = 50; standard deviation = 10. Table 517. Startle eyeblink respo nses in T score metric in exploratory analyses with depressed patients Negative Neutral Positive Anticipation On antidepressants (N=5) 52.2 (3.6) 48.4 (3.5) 49.4 (3.3) Not on antidepressants (N=5) 51.8 (3.5) 48.6 (3.4) 49.5 (4.0) Perception On antidepressants (N=5) 52.1 (4.9) 50.0 (4.6) 48.0 (3.6) Not on antidepressants (N=5) 52.8 (2.9) 49.7 (2.8) 47.7 (1.9) Anticipation Sad mood (N=6) 50.9 (2.4) 50.1 (2.3) 49.1 (1.5) No sad mood (N=4) 49.6 (3.0) 50.3 (2.3) 50.3 (1.7) Perception Sad mood (N=6) 52.7 (1.9) 49.7 (2.4) 47.9 (2.3) No sad mood (N=4) 53.1 (4.3) 49.7 (3.6) 47.6 (1.5) Note. T scores were calculated by standardizing amplitudes separately for each participant. T score mean = 50; standard deviation = 10.

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115 Table 518. Correlations between factor scores and startle eyeblink responses during the anticipation and perception of negative, neutral and positive pictures Negative Affect Anhedonia Apathy Anticipation Negative .236 .055 .297 Neutra l .116 .089 .207 Positive .155 .009 .140 Negative Neutral .211 .085 .301 Positive Neutral .030 .044 .030 Perception (normative) Negative .323 .113 .346 Neutral .032 .122 .098 Positive .339 .321 .256 Negative Positive .390* .250 .356 Perception (subjective) Negative .430* .191 .372 Neutral .384 .004 .258 Positive .073 .337 .092 Negative Positive .222 .304 .244 Note. LARS: Lille Apathy Rating Scale; AS: Apathy Scale; TEPS: Temporal Ex perience of Pleasure Scale; SHPS: SnaithHamilton Pleasure Scale; BDI II: Beck Depression Inventory, 2nd Edition; STAI: State Trait Anxiety Inventory; PANAS: Positive and Negative Affect Schedule. p < .05

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116 Table 519. Results from separate linear regress ions in which apathy, anhedonia and negative affect factor scores were regressed on startle eyeblink responses (T score) in each condition B Standard Error Beta p Negative Anticipation a Apathy 1. 58 1.29 .45 .23 Anhedonia 0.15 0.19 .18 .43 Negative Affect 0.03 0.18 .05 .88 Positive Anticipation b Apathy 0.40 1.40 .11 .78 Anhedonia 0.09 0.21 .11 .66 Negative Affect 0.06 0.19 .11 .74 Negative Perception (normative) c Apathy 1.19 1.30 .34 .37 Anhedonia 0.11 0.20 .13 .58 Negative Affect 0.06 0.18 .10 .76 Positive Perception (normative) d Apathy 0.89 1.17 .28 .45 Anhedonia 0.23 0.18 .29 .22 Negative Affect 0.22 0.16 .44 .19 Negative Perce ption (idiographic) e Apathy 0.36 1.48 .08 .81 Anhedonia 0.00 0.21 .00 .99 Negative Affect 0.23 0.20 .37 .26 Positive Perception (idiographic) f Apathy 0.89 2.09 .15 .68 Anhedonia 0.50 0.29 .41 .10 Negative Affect 0.02 0 .28 .03 .94 a R2 = .11, p = .38 b R2 = .03, p = .84 c R 2= .14, p = .31 d R2 = .17, p = .20 e R 2= .19, p = .20 f R2 = .13, p = .39

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117 Table 520. Correlations between individual psychological measures and startle eyeblink responses during the anticipation of negative, neutral and positive pictures Negative Neutral Positive Negative Neutral Positive Neutral LARS Intellectual Curiosity .276 .200 .126 .284 .034 Emotion .067 .263 .311 .111 .335 Action Initiation .237 .202 .066 .261 .072 Self Awareness .356 .608** .195 .568** .456* Total .339 .195 .188 .319 .006 AS .116 .044 .096 .096 .034 TEPS Anticipatory .027 .232 .202 .150 .252 Consummatory .062 .114 .005 .104 .066 SHPS .0 16 .103 .105 .050 .121 BDI II Dysphoria .318 .253 .120 .340 .318 Total .282 .206 .134 .291 .282 STAI State .100 .045 .097 .087 .100 Trait .246 .094 .178 .204 .246 PANAS Positive Negative .047 .1 04 .109 .032 .047 Note. LARS: Lille Apathy Rating Scale; AS: Apathy Scale; TEPS: Temporal Experience of Pleasure Scale; SHPS: SnaithHamilton Pleasure Scale; BDI II: Beck Depression Inventory, 2nd Edition; STAI: State Trait Anxiety Inventory; PANAS: Pos itive and Negative Affect Schedule. ** p <.01; p <.05

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118 Table 521. Correlations between individual psychological measures and startle eyeblink responses during the perception of negative, neutral and positive pictures Note. LARS: Lille Apathy Rating Scale; AS: Apathy Scale; TEPS: Temporal Experience of Pleasure Scale; SHPS: SnaithHamilton Pleasure Scale; BDI II: Beck Depression Inventory, 2nd E dition; STAI: State Trait Anxiety Inventory; PANAS: Positive and Negative Affect Schedule. p < .05 Negative Neutral Positive Negative Positive LARS Intellectual Curiosity .297 .133 .160 .284 Emotion .068 .162 .033 .111 Action Initiation .345 .009 .281 .261 Self Awareness .039 .202 .279 .181 Total .345 .168 .169 .319 AS .369 .036 .413* .096 T EPS Anticipatory .190 .087 .341 .309 Consummatory .087 .160 .337 .243 SHPS .084 .160 .029 .035 BDI II Dysphoria .286 .186 .092 .227 Total .325 .196 .147 .283 STAI State .199 .096 .331 .309 Trait .345 .031 .370 .420* PANAS Positive Negative .002 .079 .140 .080

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119 Table 522. Correlations between individual psychological measures and startle eyeblink responses during the perception of subjectively classified pictures Note. LARS: Lille Apathy Rating Scale; AS: Apathy Scale; TEPS: Temporal Experience of Pleasure Scale; SHPS: SnaithHamilton Pleasure S cale; BDI II: Beck Depression Inventory, 2nd Edition; STAI: State Trait Anxiety Inventory; PANAS: Positive and Negative Affect Schedule. ** p <.01; p <.05 Negative Neutral Positive Negative Positive LARS Intellectual Curiosity .304 .197 .105 .220 Emotion .238 .108 .280 .303 Action Initiation .216 .098 .137 .066 Self Awareness .131 .269 .506** .365 Total .332 .228 .04 5 .218 AS .394* .151 .186 .358 TEPS Anticipatory .114 .203 .488* .386 Consummatory .197 .011 .335 .299 SHPS .026 .006 .090 .108 BDI II Dysphoria .419* .498** .092 .115 Total .523** .499** .075 .275 STAI State .213 .149 .065 .112 Trait .463* .409* .105 .260 PANAS Positive Negative .140 .142 .101 .048

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120 Figure 51. Schematic model of the secondorder confirmatory factor analysis

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121 F igure 52. Standardized startle eyeblink responses (T score) by group and affect condition during the anticipation period. T scores were calculated by standardizing amplitudes separately for each participant. T score mean = 50; standard deviation = 10. Error bars: 95% confidence intervals. Control Non depressed Parkinson Depressed Parkinson

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122 Figure 53. Standardized startle eyeblink responses (T score) by group and affect condition during the perception period. T scores were calculated by standardizing amplitudes separately for each participant. T sco re mean = 50; standard deviation = 10. Error bars: 95% confidence intervals. Control Non depressed Parkinson Depressed Parkinson

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123 Figure 54. Standardized startle eyeblink responses during the perception period using subjective classification of pictures. T scores were calculated by standardizing am plitudes separately for each participant. T score mean = 50; standard deviation = 10. Error bars: 95% confidence intervals. Control Non depressed Parkinson Depressed Parkinson

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124 A B Figure 55. Standardized startle magnitudes in PD Depressed patients as a function of antidepressant usag e A) Anticipation. B) Perception. Note. PD: Parkinson disease patients T scores were calculated by standardizing amplitudes separately for each participant. T score mean = 50; standard deviation = 10. Error bars: 95% confidence intervals. Currently on an antidepressant Not currently on an antidepressant

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125 A B Figure 56. Standardized startle magnitudes in PD Depressed patients as a function of presence/absence of sad mood. A) Anticipation. B) Perception. Note. PD: Parkinson disease. T scores were calculated by standardizing amplitudes separately for each participant. T score mean = 50; standard deviation = 10. Error bars: 95% confidence intervals. Sad moo d No sad mood

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126 CHAPTER 6: DISCUSSION The overall goal of the present study was to better understand depression in patients with Parkinson disease (PD) and to learn w hether certain depression components would differentially map onto patterns of physiologic responding during the anticipation and perception phases of an emotional picture viewing paradigm. To accomplish this goal, there were three specific aims. The first aim sought to determine whether affective disturbance in PD produces separate components (i.e., apathy, anhedonia, negative affect) and to learn which of these components, if any, best discriminates between PD patients who meet DSM IV criteria for depress ion from those who do not. The working hypothesis was that the three depression components are separable in PD and that apathy is the core affective deficit of PD that is not specific to depression. However, it was predicted that negative affect would best discriminate between patients with and without depression. The second aim was to determine whether depressed PD patients would exhibit a pattern of muted emotion modulation of the startle eyeblink reflex during the anticipation and perception phases of an emotional pictureviewing psychophysiology task, similar to that recently described in a sample of depressed patients without PD (Dichter & Tomarken, 2008). Building on these anticipated findings, the third aim was to learn how specific depression components (i.e., apathy, anhedonia, negative affect) relate to psychophysiologic responding during the anticipation versus the perception of differently valenced emotional pictures. Based on views regarding both the phenotypic characteristics and the putative neuroanatomic correlates of apathy, anhedonia and negative affect, it was hypothesized that the apathy construct (as derived from Aim 1)

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127 would be associated with deficient startle reactivity during the anticipation of emotional events (both positive and n egative), while responses during perception would be relatively unaffected. In contrast, it was predicted that the anhedonia construct would be associated with a lack of startle modulation during the anticipation and perception of positive stimuli, but not negative stimuli. Finally, it was predicted that the negative affect construct would be associated with exaggerated startle eyeblink respon ding in all conditions Prevalence of Depression The current sample of 95 nondemented PD patients was comparable to that of others described in the literature in terms of depression prevalence (Brown & Jahanshahi, 1995; Slaughter et al., 2001; Tumas, Rodrigues, Farias & Crippa, 2008; Reijnders et al.., 2008; Starkstein et al., 2008; Marsh et al., 2006). Specifically, a quarter of the sample met DSM IV criteria for major depression, and an additional 3.2% met DSM IV research criteria for minor depression. The latter requires only one (as opposed to four) features in addition to the primary symptom of sad mood or loss o f interest/pleasure. Individuals identified as having minor depression were more likely to report loss of interest/pleasure without sad mood as their primary symptom, as compared to individuals identified as having major depression. These findings are cons istent with those of Starkstein et al. (2008) and are supportive of the possibility that a diagnosis of minor depression is less specific for the presence of sad mood than is major depression in PD. Fewer depressed participants in this study reported classical depressive symptoms such as sad mood, worthlessness/guilt, and suicidal thoughts (19 56% of

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128 sample), as compared to cognitive or somatic symptoms such as reduced concentration, appetite or sleep changes, and fatigue (59 93% of sample). This phe nomenologic pattern is consistent with prior research suggesting that somatic and cognitive symptoms are more typical of PD depression than are classical depressive symptoms (Gotham, Brown, & Marsden, 1986; Schiffer, Kurlan, Rubin, & Boer, 1988; Starkste in, Preziosi, Forrester, & Robinson, 1990; Ehmann, Beninger, Gawel, & Riopelle, 1990; Erdal, 2001; Merschdorf et al., 2003). In this study, PD patients with depression were comparable to those without depression in terms of age and sex, though depressed patients were slightly less educated (i.e., approximately 2.5 years of college versus almost four years for nondepressed PD). Depressed PD patients also exhibited worse motor functioning, as defined by UPDRS scores obtained while patients were on their antiparkinsonian medications. These findings correspond to previous studies reporting greater disease severity in point comparisons of depressed and nondepressed PD patients (e.g., Palhagen et al., 2008). There are at least two nonmutually exclusive int erpretations of the relationship between depression and PD motor disease severity: 1) Depression represents an adjustment reaction to living with debilitating symptoms of PD, and/or 2) Greater overall neurodegeneration leads to both motor and depressive sy mptoms. The argument against the depressive reaction interpretation is that there were no differences between depressed and nondepressed groups in terms of motor disability, defined by Hoehn and Yahr stage, or in disease duration, defined as either years since symptom onset or years since diagnosis. An alternative view is that patients with depression may suffer

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129 from a more aggressive neurodegenerative process. However, previous studies have suggested that neurodegenerative changes underlying motor and depressive symptoms may not be identical. Specifically, motor symptoms are most closely linked to dopaminergic neurodegeneration (Gibb et al., 1997), whereas depressive symptoms may be more closely linked to neurodegeneration in other neurotransmitter systems (e.g., serotonin, norepinephrine; Mayeux, Stern, Cote & Williams, 1984, Becker et al., 1997; Walter, Skoloudik & Berg, 2009). Despite correlations between motor and depressive symptoms in cross sectional studies of PD, different findings emerge in longitu dinal studies. Namely, a linear relationship did not appear to exist between motor severity and depression in a longitudinal study of patient with PD (Zahodne, Marsiske, Okun, & Bowers, 2011). As such, the exact relationship between depression symptoms and motor symptom severity remains unclear, but likely involves several levels of complexity. Of the total sample of 95 PD patients, 54% reported experiencing at least one depressive episode in their lifetime, which is in line with lifetime prevalence rat es of 4070% reported in other studies of PD (Cummings, 1992; Brooke & Doder, 2001; Slaughter, Slaughter, & Nichols, 2001). Lifetime prevalence of depression in PD is considerably greater than the estimated 16% lifetime prevalence of depression in the general population (Kessler et al., 2003). It is also greater than that reported in a variety of other chronic medical conditions (Massie & Popkin, 1998). One hypothesis for this greater lifetime prevalence of depression in PD is that depression may be a prodr omal indicator of PD (Leentjens, Van den Akker, Metsemakers, Lousberg & Verhey, 2003). Consistent with this view is the observation in the present sample that of the 51 PD

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130 patients with a history of depression and/or current depression, 67% reported that t heir first depressive episode occurred prior to their diagnosis of PD. However, this self report data should be interpreted with caution, as it is not accompanied by historical clinical documentation. Notably, a substantial proportion (31%) of PD patient s who did not meet criteria for major or minor depression reported clinically significant levels of apathy, defined as a score > 14 on the AS. This proportion is similar to those (1229%) reported by other studies that have differentiated apathy and depres sion in PD (Starkstein et al., 1992; Isella et al., 2002; KirschDarrow et al., 2006; Zgaljardic et al., 2007). Aim 1: Characterizing Depression in PD Factor Structure of Psychological Symptoms in PD Overall findings from Aim 1 supported the working hypothesis that affective disturbance in PD can be separated into three components (i.e., apathy, anhedonia, negative affect), with apathy being a core feature of this disturbance. In brief, t he hypothesized threefactor model fit the data better than alternative nested models that allowed the psychological variables to load on only one (global affective disturbance) or two (negative affect and apathy/anhedonia) factors. These results support the choice of these psychological variables based on their purported ability to index the different constructs. Importantly, while the constructs of apathy, anhedonia, and negative affect can be separated in PD (based on support for separate latent factors), they nevertheless overlapped (based on correlations among factor scores). In fact, affective disturbance in PD appeared to involve changes in all three symptom types based on the finding that all

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131 three components loaded significantly onto a single, global factor. However, the strongest factor loading on this global fac tor was found for apathy, relative to anhedonia or negative affect That apathy loaded most highly on the global affective disturbance factor is consistent with the view that apathy may be a core neuropsychiatric symptom of PD A similar view has previousl y been argued based on the higher prevalence rates of apathy compared to other mood symptoms in PD (e.g., Kirsch Darrow et al., 2006). Discriminating Depression in PD The hypothesis that negative affect would best discriminate between PD patients with and without depression was supported. Together, t he three components identified through CFA ( i.e., apathy, anhedonia, negative affect) were effective in discriminating between patients with and without DSM IV defined minor or major depression. A single discri minant function accurately classified 89% of patients originally stratified using an abbreviated SCID interview and it demonstrated sensitivity of .87 and specificity of .96. Depressed patients exhibited greater psychopathology on each of the three compon ents, but negative affect contributed most to classification (standardized canonical discriminant function coefficient = .628) followed by apathy (coefficient = .512) and anhedonia (coefficient = .048) The current findings have several implications. Fi rst, while apathy may be the most sensitive indicator of affective disturbance in PD, negative affect is the most specific indicator of depression per s. Negative affect was defined in the current study with measures of dysphoria, anxiety, and a variety of traits associated with negative affectivity such as irritability and hostility. The finding that negative affect best discriminated PD depression is consistent with the contemporary conceptualization of a

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132 distinction between apathy and depression (Mimur a, 2007; KirschDarrow et al., 2006; Kirsch Darrow, 2009). Specifically, the symptomatic dysphoria seen in depression is absent in an apathy syndrome, while a lack of strong emotional responses, regardless of valence, is symptomatic of apathy. Second, anh edonia was least discriminating of PD depression. This was based on the observation that anhedonia factor scores exhibited the lowest standardized canonical discriminant function coefficient, as compared to negative affect and apathy. This finding does not support the recent NINDS recommendation that anhedonia may be more specific to PD depression than is loss of interest (Marsh et al., 2006). In the present study, apathy contributed more strongly to the discriminant function than did anhedonia. However, apathy factor scores were highly correlated with negative affect factor scores ( r = .78), which may have buttressed their prominence in the DFA. Aim 2: Startle Psychophysiology Hypotheses regarding patterns of emotionmodulated startle psychophysiology in the three participants groups were partially supported. During the anticipation phase, both healthy control and nondepressed PD participants demonstrated the predicted quadratic pattern of startle eyeblink responding, although the effect was at trend level for PD participants. In contrast, and as predicted, the depressed PD patients did not exhibit emotionmodulation of the startle eyeblink reflex during anticipation. This finding corresponds to that previously reported by Tomarken and Dichter (2008) in a group of 27 patients with major depressive disorder. During the perception phase, healthy controls demonstrated the predicted linear pattern of startle eyeblink responding, while nondepressed PD participants did not. This

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133 latter finding was primarily dr iven by a lack of startle potentiation during the viewing of negative pictures and corresponds to previous findings in the literature (Bowers et al, 2006; Miller et al., 2009). The most striking deviation from predicted outcomes occurred within the depress ed PD group. Contrary to our predictions, depressed PD participants exhibited a clear linear pattern of startle eyeblink responding during picture viewing. In fact, compared to their nondepressed counterparts, their startle reactivity tended to be elevated during the perception of negative pictures. The observed differences in patterns of startle reactivity were not due to differences in demographic or disease characteristics between the groups. Nor were they due to differences in the basic mechanics of t he startle eyeblink response, given the similarity of startle amplitudes during the baseline (unprimed) startle trials exhibited by the three participant groups. Nor were differences in patterns of startle reactivity due to a failure of participants to appreciate the emotional meaning of the picture stimuli, as the groups did not differ in their subjective ratings of valence or arousal. Overall, these findings are consistent with previous research indicating that neither the Parkinson disease state (Bowers et al., 2006: Miller et al., 2009) nor the disorder of depression ( Dichter & Tomarken, 2008; Dichter Tomarken, Shelton, & Sutton, 2004) significantly interferes with the basic integrity of the startle eyeblink reflex. Nor do these conditions alter ratings of the emotional content of pictures from the IAPS. Thus, any differing patterns of emotionmodulated startle psychophysiology found in the present study cannot be interpreted as stemming from a failure of a particular group to rate or appreciate the emot ional stimuli.

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134 Startle Psychophysiology in Healthy Controls Anticipation. At least two interpretations have been posited for findings that healthy adults exhibit a quadratic pattern of startle eyeblink responding during the anticipation of emotional ma terials, similar to that observed in the present study. Sabatinelli et al. (2001) suggested that enhanced startle eyeblink responding during the anticipation of emotional pictures reflects a generalized mobilization for action that is driven by arousal rat her than valence. A signal indicating a chance to obtain a pleasurable reward or an unpleasant punishment may induce arousal due to feelings of excitement, uncertainty, and/or anxiety (Lipp, Siddle, & Dall, 19 97). Alternatively, Dichter and Tomarken (20 08) suggested that the quadratic pattern of emotion modulated startle during anticipation results from participants engagement in spontaneous elaboration during this period of expectancy. These authors cite only mental imagery as an example of this cognit ive elaboration, but one could speculate that elaboration might also involve associative memory processing (i.e., recalling past encounters with emotional images). Indeed, quadratic modulation of startle has been documented during tasks involving mental im agery of pleasant and unpleasant events (Miller, Patrick, & Levenston, 2002; Witvliet & Vrana, 1995, 2000). During the anticipation phase of the current paradigm, participants must: 1) Understand the meaning of the valence cue, and 2) Maintain a representation of that meaning in working memory throughout the duration of the anticipation phase. Maintaining that representation may involve simple rehearsal and/or elaborating on that representation via imagery and associative memory processing. In the current

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135 p aradigm, the latter process could involve recalling previously presented negative or positive IAPS pictures. Given these task demands, a potential framework for conceptualizing the component processes involved in the anticipation phase of this study might involve a hierarchy of processing levels. At the most basic level, participants must achieve a general state of arousal sufficient to allow them to activate anticipatory processing in the first place. Next, participants must process the valence cues. As n oted above, processing the valence cues involves both appreciating the meaning of the valence cues and maintaining a representation of that meaning through elaborative working memory rehearsal. The latter process of elaborative rehearsal requires two basic elements: 1) Working memory capacity and 2) Motivation to engage in rehearsal. Finally, participants must translate this effortful cognitive activity into a state of enhanced physiologic arousal (i.e., emotional expectancy). While the cognitive processi ng involved in emotional expectancy is known to involve activation of the frontal lobes (i.e., dorsolateral prefrontal and anterior cingulate cortices), the specific neuronal pathways by which these regions might modulate startle potentiation during the anticipation of emotional material are unknown. However, it has been suggested that this neurophysiological translation of cortically generated emotional expectancy into heightened arousal may involve activation of the amygdala and/or the ventral tegmental area (Borowski & Kokkinidis, 1996; Rosen & Davis, 1990). Perception. Studies reporting a linear pattern of emotionmodulated startle eyeblink responding during picture viewing, as exhibited by the healthy control group in the present study, are numerous (s ee Bradley, Codispoti, Cuthbert & Lang, 2001 for a

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136 review). This pattern of responding is thought to reflect the activation of separate motivational systems (i.e., defensive versus appetitive) by negative and positive stimuli, respectively. Specifically, engagement of the defense system by the perception of a negative stimulus is believed to prime defensive reflexes. In contrast, engagement of the appetitive system by the perception of a positive stimulus concomitantly inhibits defensive reflexes. Startle potentiation during the perception of negative material is mediated by amygdalar modulation of brainstem nuclei (Rosen & Davis, 1990; Hitchcock, Sananes, & Davis, 1989). Startle attenuation during the perception of positive material is likely mediated by mesoaccumbal pallidal circuitry (Koch, Schmidt, & Schnitzler, 1996; Panagis, Miliaressis, Anagnostakis, & Spyraki, 1995). The specific neuronal pathways by which these mesoaccumbal pallidal regions interact with the brainstem startle response circuit are cur rently unknown, but they may involve a relay through the pedunculopontine tegmental nucleus (Steidl, Li, & Yeomans, 2001). Divergent patterns in the affective chronometry of startle modulation. The divergent patterns of startle reactivity shown by the healthy controls during the anticipation and picture viewing phases correspond to those previously observed by other researchers (Dichter, Tomarken, & Baucom, 2002). Moreover, these findings support the view that separate mechanisms underlie emotionmodulation of the startle eyeblink reflex during the two temporal phases. Importantly, anticipating and perceiving emotional material involve distinctly different processing demands that could be conceptualized as top down and bottom up, respectively. Anticipa ting emotional pictures is largely a cognitive task. It involves understanding the meaning of a valence cue and maintaining that meaning in working

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137 memory throughout the anticipation period. This maintenance could be achieved through active sensory disengagement, rote rehearsal, and/or mental elaboration via imagery and associative memory processing (e.g., recalling previous pictures). This internal, topdown activity drives physiologic arousal during the anticipation period. Stimuli used in most studies examining the effects of internal processing of affective stimuli on physiologic arousal were emotional words (Herbert, Junghfer, & Kissler, 2008; Kissler, Herbert, Peyk, & Junghfer, 2007). Presumably, emotional words evoke an emotional response by their semantic content rather than their perceptual features (Koban, Ninck, Li, Gisler, & Kissler, 2010). In one functional magnetic resonance imaging (fMRI) study, participants were instructed to evaluate the valence of emotional and nonemotional words (Maddock, Garrett, & Buonocore, 2003). These participants exhibited increased blood oxygen level dependent (BOLD) signaling in various subregions of the prefrontal cortex (i.e., anteromedial orbital, left inferior, middle), subgenual cingulate, and posterior cingulate cortex. In addition to this enhanced brain activation, processing of emotional words has also been shown to enhance potentiation of the startle eyeblink reflex (Herbert, Kissler, Junghfer, Peyk & Rockstroh, 2006; Herbert & Kissler, 2010). In contr ast, picture viewing is largely a perceptual task. It involves deriving meaning from a complex visual array in a hierarchical manner (Marr, 1982). Specifically, basic features are derived from a visual scene, these features are further processed in order t o identify forms, and then these forms are matched to stored semantic information (Peissig & Tarr, 2007). In the special case of emotional facilitation of visual processing, activation of either the appetitive or defensive motivation system results in

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138 enhanced processing at both early and later stages of this hierarchical sensory processing, as indexed by separate event related potential (ERP) components (Schupp, Junghfer, Weike, & Hamm, 2003). In fMRI studies, visual perception of emotionally arousing sti muli has also been associated with enhanced BOLD signaling across large portions of the ventral visual system (e.g., Bradley et al., 2003). Further, this enhanced activation has been shown to result from reentrant feedback from the amygdala to rostral vent ral visual cortex (Sabatinelli, et al., 2009). This bottom up perceptual processing, combined with reentrant feedback, drives physiologic arousal during the perception phase of emotional picture viewing. In summary, increased arousal is associated with different enhancements during anticipation versus perception. During anticipation, arousal is associated with enhanced internally focused (i.e., nonperceptual) processing primarily in the frontal lobes (Miller, Patrick, & Levenston, 2002; Herbert & Kissler, 2010). This valencenonspecific activation leads to startle eyeblink potentiation (Dichter, Tomarken, & Baucom, 2002; Sabatinelli et al., 2001). During perception, arousal is associated with enhanced perceptual processing, as evidenced by greater activati on in an extended visual network (Bradley et al., 2003). The specific effect of emotional arousal on startle eyeblink responding during perception depends on valence. Startle Psychophysiology in Depressed PD The primary participant group of interest in the present study included depressed PD patients. This group exhibited muted reactivity during the anticipation of emotional pictures but strong emotion modulation of the startle eyeblink reflex during the perception of emotional pictures. This latter finding contradicts the view that depression,

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139 at least in PD, is characterized by broad emotional context insensitivity throughout the time course of an affective response, as suggested by Dichter and Tomarken (2008) in their study of depressed individuals wit hout PD. Anticipation. What is the basis for the blunted reactivity during the anticipation phase that was unique to the PD depressed group? There are at least four potential interpretations: a general arousal deficit, deficient processing of the valence cues, deficient maintenance of valence information throughout the duration of the anticipation period, and/or an inability to translate cognitive processing of valence cues into physiologic activation. The first possibility relates to a general arousal deficit Because depressed PD patients in the current study demonstrated strong emotional reactivity when viewing emotional pictures during the perception phase, such a generalized arousal deficit hypothesis does not easily fit these data. In other words, a generalized arousal deficit cannot account for the dissociation between patterns of psychophysiologic responding during anticipation versus perception of emotional stimuli in the depressed PD group. Another possibility relates to a decreased capacity to process the valence cues As described earlier, the generation of emotional expectancy during anticipation requires: 1) Understanding of the meaning of the valence cues, and 2) Maintenance of a representation of that meaning in working memory throughout the duration of the anticipation period. In the present study, all participants demonstrated an understanding of the three valence cues following a period of practice and instruction, and none exhibited signs of dementia. Therefore, it is unlikely that depres sed participants failed to understand the meaning of the valence cues.

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140 A third possibility relates to deficient working memory Depressed PD participants may have been less able to maintain a representation of valence in working memory. Turning to the lit erature, it is well known that individuals with depression exhibit deficits in effortful working memory tasks (Rose & Ebmeier, 2006; Gotlib & Joorman, 2010). As described above, the anticipation phase of the present study involved maintaining the meaning o f valence cues in working memory over a four second period. This maintenance would potentially be achieved through rote rehearsal and/or mental elaboration (e.g., spontaneous mental imagery, associative memory processing). To examine the possibility of a w orking memory explanation, we conducted a post hoc examination of the cognitive screening data (i.e., serial 7s from the MMSE). Indeed, there were trends for individuals who successfully completed a simple working memory task involving serial subtraction of 7s from 100 to exhibit greater startle potentiation during both negative ( p = .07) and positive ( p = .08) conditions, as compared to the neutral condition. These trends provide some indirect support for the hypothesis that depressed individuals muted psychophysiologic reactivity during anticipation resulted from deficient working memory. The cognitive basis for reduced elaborative working memory in PD patients with depression is unclear. However, there are several potential mechanisms that might under lie a deficiency in elaborative working memory processes during the anticipation phase of the present study. These potential mechanisms include reduced motivation, impersistence, and/or excessive rumination. Reduced motivation in the PD depressed group could underlie a working memory deficit during the effortful task of maintaining valence representations during the

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141 anticipation phase. In healthy individuals, these valence representations are what generate the state of emotional expectancy in the topdo wn anticipation phase of the emotional pictureviewing task. Reduced motivation in the PD depressed group may relate to apathy, which is a core symptom of depression. For example, Seligman (1992) describes an absence of volitional responses (behavioral or cognitive) as an aspect of helplessness in depression. Indeed, depressed PD participants in this study exhibited significantly higher levels of apathy than did nondepressed PD participants, as measured with both the LARS and the AS. It may also be the case that depressed participants were able to generate emotional expectancy initially, but were unable to maintain this state of expectancy through sustained elaborative rehearsal throughout the duration of the anticipation phase (i.e., impersistence). Alt ernatively, excessive rumination in the depressed PD group might underlie deficient elaborative working memory rehearsal during the anticipation phase. Consistent with the dual process model of cognitive vulnerability in depression (Beevers, 2005), Hertel (1998) proposed that ruminative thought processes decrease cognitive performance by capturing cognitive resources and preventing their allocation to task relevant processes. In one study, rumination (as measured with the Response Style Questionnaire) was highly correlated with impairment on a challenging working memory paradigm requiring conflict resolution (Levens, Muhtadi, & Gotlib, 2009). While rumination is a prominent feature of metacognitive models of depression (Wells, 2000), levels of rumination wer e not explicitly measured in the present study. Thus, it is not possible to fully assess the potential relationship between depressive rumination and

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142 muted psychophysiology reactivity during anticipation in this sample of depressed PD patients. Finally, a fourth potential explanation for depressed participants blunted reactivity during the anticipation phase is a specific translational deficit That is, participants may have been able to maintain a representation of valence in working memory but were unab le to become physiologically aroused by this mental representation. Note that this account implies a specific translational deficit, rather than a generalized arousal deficit. Therefore, it is not incompatible with the finding that depressed patients exhibited an intact ability to translate visual processing of emotional pictures into physiologic arousal during the perception phase. This interpretation suggests that PD depression may be associated with impaired topdown arousal but intact bottom up arou sal. Such a view is compatible with findings suggesting that depressed individuals have a decreased capacity for volitional emotion regulation (Johnstone, van Reekum, Urry, Kalin & Davidson, 2007). Indeed, a primary focus of many psychotherapeutic interventions for depression lies in modifying attentional and memory processes in order to promote better regulation of emotional state and concomitant physiologic arousal. From a neural systems perspective, the lack of emotion modulated startle during the antici pation of pictures in the PD depressed group may reflect depressionrelated dysfunction within the neural circuitry involved in generating emotional expectancy. As described above, such dysfunction would most likely be due to a working memory deficit (rela ted to reduced motivation and/or rumination) and/or a deficit in topdown generation of arousal. Some evidence suggests that the neural network underlying emotional

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143 expectancy involves the dorsolateral prefrontal cortex (DLPFC) and the anterior cingulate c ortex (ACC) (Bermpohl et al., 2006; Ueda et al., 2003). In one fMRI study of healthy adults the left DLPFC was strongly activated between the presentation of a symbolic valence cue and a pleasant picture from the IAPS (Ueda et al. 2003) In contrast, the left ACC was strongly activated between the presentation of a symbolic valence cue and a negative picture from the IAPS These findings suggest that different subregions of the frontal region may be involved in valencespecific emotional expectancy. That depressed PD patients in the present study demonstrated deficient startle potentiation during the anticipation of both positive and negative pictures suggests that both subregions (i.e., DLPFC and ACC) may be compromised by PD depression. Of particular rel evance to the present study, reduced functional activity in both DLPFC and ACC have been described in PD patients with depression. For example, Cardoso, et al. (2008) reported that PD patients with depression showed significantly reduced BOLD signaling in the left prefrontal cortex, as compared to healthy controls. Similarly, Ring, et al. (1994) reported that PD patients with depression showed significantly less regional cerebral blood flow (rCBF) in the ACC, as compared to PD patients without depression. T hough these studies were purely descriptive, they provide a basis for a hypothesis that reduced functional brain activity among depressed PD patients may underlie our finding of deficient emotional expectancy as indexed by startle eyeblink psychophysiology. Of note, the precise mechanism by which cortical activity interacts with the brainstem mediated startle eyeblink reflex is currently unknown.

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144 Perception. The present study did not replicate the findings of Dichter and Tomarken (2008), who reported that depressed individuals without PD did not show emotion modulation of the startle eyeblink reflex during the viewing of emotional pictures. Instead, this study found evidence for heightened psychophysiologic sensitivity to aversive stimuli among depressed P D patients. Compared to their nondepressed counterparts, depressed PD patients tended to exhibit exaggerated startle potentiation to negative pictures. Such hyper reactivity to aversive stimuli has been reported in studies using startle eyeblink psychophy siology to study depressed individuals The idea that individuals with depression are more sensitive to aversive stimuli is long standing (e.g., Lewinsohn, Lobitz & Wilson, 1973) and remains a core component of contemporary cognitive and physiological theories of depression. As one example, the mood state dependent hypothesis suggests that heightened sensitivity or responsiveness to mood induction procedures might be an indicator of increased vulnerability to depression (Miranda & Gross, 1997). Given the s imilarity of the paradigms involved in this and the study reported by Dichter and Tomarken (2008), what might account for our discrepant results? One obvious explanation relates to the patient populations under study (PD patients versus healthy adults). Co mpared to the primary affective disturbance, depression in PD appears to differ in the localization, distribution and severity of neurotransmitter disturbances (Mayeux, Stern, Sano, Williams, & Cote, 1988). Phenomenologically, PD depression has been associ ated with fewer classical depressive symptoms such as guilt and suicidal ideation, and more somatic and cognitive symptoms (Gotham, Brown, & Marsden, 1986; Schiffer, Kurlan, Rubin, & Boer, 1988; Starkstein, Preziosi, Forrester,

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145 & Robinson, 1990; Ehmann, Beninger, Gawel, & Riopelle, 1990; Erdal, 2001; Merschdorf et al., 2003). Anxiety, dysphoria, and irritability may also be more prominent in PD depression (Schiffer et al., 1988; Menza, RobertsonHoffman, & Banapace, 1993; Henderson, Kurlan, Kersun, & Como, 1992; Gotham, Brown, & Marsden, 1986; Brown, MacCarthy, Gotham, Der, & Marsden, 1988; Huber, Freidenberg, Paulson, & Shuttleworth, 1990). Thus, neurophysiological and/or phenomenological differences between depression in PD versus healthy adults could result in different patterns of psychophysiologic responding. Compared to the study conducted by Dichter and Tomarken (2008), the present study also featured a smaller sample of depressed participants (10 versus 27). However, the fact that this study detecte d a significant effect of affect condition in such a sample size while those authors did not would suggest that sample size differences do not explain our differing patterns of results. A likely potential explanation for these discrepant results relates to the fact that depressed participants in the current study reported less severe depressive symptoms ( mean BDI II total score of 20) than did participants in that study (mean BDI II total score above 30). It has been suggested that mild or moderate depressi on results in broad defense system sensitization, while severe depression involves a shift from hyper reactivity to a generalized inhibitory physiologic mode (Vaidyanathan, Patrick, & Cuthbert, 2009; Cuthbert et al., 2003; Seligman, 1975). Indeed, Kaviani, et al. (2004) reported deficient emotionmodulated startle during perception only in a subgroup of severely depressed individuals Severely depressed individuals were under represented in the present study, as only one of the 10 participants in the depres sed group had a BDI II score above 30.

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146 In summary, depression in our PD sample did not seem to be characterized by broad emotional context insensitivity throughout the time course of affective responding Rather, it was associated with deficient anticipati on of emotional material. Additionally, PD depression was associated with enhanced startle potentiation during the viewing of negative pictures. The latter finding is consistent with the notion that mild to moderate depression is associated with hyper resp onsiveness to aversive stimuli. Startle Psychophysiology in Non depressed PD Non depressed PD patients in the present study exhibited intact emotionmodulated startle during the anticipation phase and blunted startle potentiation during the viewing of negative pictures during the perception phase. The finding of appropriate reactivity during the anticipation phase is important for at least two reasons. First, it implies that the reduced capacity to generate emotional expectancy seen in depressed PD rela tes to depression rather than PD itself. Second, it supports the view that separate mechanisms underlie emotion modulation of the startle eyeblink reflex during anticipation versus perception. This is because nondepressed PD patients were able to demonstr ate startle potentiation during anticipation but not during the perception of negative pictures. The amygdala, which is tonically inhibited by the prefrontal cortex, becomes activated when healthy individuals enter an aversive context (Inglis & Moghaddam, 1999; Lang & Par, 1998; Rosenkranz & Grace, 1999, 2002; Quirk et al., 2003). Importantly, this amygdalar activation triggered by a heightened emotional state is mediated by dopamine induced disinhibition of the basolateral and central amygdala via D1 receptor activation (Marowsky et al., 2005). In PD, dopamine depletion may prevent

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147 adequate disinhibition of the amygdala in emotional contexts, resulting in diminished startle reactivity during an aversive motivational state (Bowers et al., 2006). Indeed, t he amygdala exhibits numerous abnormalities in PD, including reduced neuronal density in the basolateral amygdalar group, 3045% reductions in amy g dalar dopamine agonist binding, increased presynaptic axonal pathology and increased occurrence of amygdalar L ewy body pathology ( Harding, Stinson, Henderson, & Halliday 2002; Ouchi et al., 1999; Bertrand et al., 2003; Braak et al., 1993). Since nondepressed PD patients exhibited intact startle potentiation during anticipation, this proposed model of deficient dopaminergic modulation of the amygdala must not apply to this earlier temporal phase. In other words, facilitation of the startle eyeblink reflex during anticipation must be possible despite deficient dopaminergic gating of the amygdala. This finding suggests that startle potentiation due to emotional expectancy occurs via a nondopaminergic mechanism, perhaps one involving GABA or glutamate. For example, emotional expectancy may involve cortical disinhibition of the amygdala (i.e., reduced GABAergic input) and/or known excitatory (i.e., glutamatergic) afferents from prefrontal cortex to the VTA (Geisler, Derst, Veh & Zahm, 2007). Of note, different mechanisms may underlie expectancy related startle potentiation in positive and negative conditions, as sugges ted by neuroimaging findings discussed above (Bermpohl et al., 2006; Ueda et al., 2003). The finding of divergent patterns of emotionmodulated startle psychophysiology in depressed and nondepressed PD suggests that during picture viewing, depression may restore the excitability of the amygdala by negative emotional material that is deficient in PD. Indeed, depression is associated with increased resting blood flow in

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148 the amygdala (Drevets et al., 1992) and increased BOLD signaling in response to negativ e emotional stimuli, which is eliminated with antidepressant treatment (Sheline et al., 2001). This depressionrelated amygdalar hyperactivity may result from reduced inhibition from the prefrontal cortex. In one study using fMRI, nondepressed adults disp layed a negative association between activity in the amygdala and the ventrolateral prefrontal cortex (VLPFC) during an emotional reappraisal task, and this association was mediated by the VLPFC (Johnstone, van Reekum, Urry, Kalin & Davidson, 2007). Import antly, this putative demonstration of normal prefrontal inhibition of the amygdala was absent in a group of depressed individuals. Increased coupling between the amygdala and the prefrontal cortex with selective serotonin reuptake inhibitor treatment provi des further evidence for reduced frontal inhibition of the amygdala in depression (Chen et al., 2008). While nondepressed PD patients did not exhibit startle potentiation during the viewing of negative pictures, there was some evidence of startle attenuat ion during the viewing of subjectively classified positive pictures. Specifically, when pictures were reclassified according to participants subjective valence ratings, there was a trend for smaller startle eyeblink responses during the viewing of positi ve versus neutral pictures in the non depressed PD group. These results support previous reports that PD related disruption of emotionmodulated startle psychophysiology during emotional picture viewing is limited to the viewing of negative pictures (Bower s et al., 2006). Modulation of Startle Eyeblink Psychophysiology by Negative Versus Positive Material In the present study, startle eyeblink modulation was more consistently observed in conditions involving negative stimuli, as compared to positive stim uli. A verage startle

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149 eyeblink responses elicited during the viewing of positive pictures were numerically smaller than those elicited during the viewing of neutral pictures in all three groups (healthy control, nondepressed PD, depressed PD). However, non e of these differences was statistically significant, perhaps due to limited power It is not surprising that response differences involving positive stimuli were harder to detect. Human responses to negative stimuli are consistently greater in magnitude t han responses to positive stimuli across a wide variety of behavioral paradigms, and this phenomenon has been referred to as the negativity bias (Rozin & Royzman, 2001) The negativity bias has also been explicitly documented in psychophysiology paradigms (Taylor, 1991). The greater difficulty documenting differences involving the positive condition in this study may also relate to differing personal preferences for pleasurable pictures. Specifically, p ictures classified as positive by their normative rati ngs were more likely to be classified as neutral, as compared to pictures classified as negative by their normative ratings This finding was true for participants in all three groups. Overlap between subjective and normative ratings ranged from 80 to 83% across groups for negative pictures, 75 to 83% for neutral pictures, but only 58 to 62% for positive pictures. These differences emerged even though negative and positive pictures were not significantly different in average normative ratings of arousal or absolute valence. Thus, there seemed to be more subjective variability in what participants considered positive images than in what participants considered negative images. This may relate to differences in the proportion of negative versus positive images relating to primary versus secondary motivators. Specifically, many of the negative pictured referenced

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150 primary motivators (e.g., aggression), while many of the positive pictures referenced secondary motivators (e.g., achievement). Another reason for diff ering strengths in effects involving negative and positive conditions may relate to differing neural circuitry involved in processing negative versus positive stimuli. Ueda et al. (2003) showed that different subregions of the prefrontal cortex (i.e., DLPF C and ACC) are involved in the emotional expectancy of positive and negative pictures, respectively. Similarly, amygdalar activation is presumed to underlie startle potentiation during the viewing of negative pictures, while mesoaccumbal pallidal circuitry is presumed to underlie startle attenuation during the viewing of positive pictures (Davis, 1998; Koch, Schmidt, & Schnitzler, 1996). These divergent neural networks may be differentially sensitive to behavioral paradigms intended to influence motivational state. Aim 3: Relating Psychophysiology Variables to Depression Components The third aim of this study explored how different depression components would relate to the affective chronometry of emotion modulated startle in PD. Namely, it was predicted t hat the apathy construct (from Aim 1) would correspond to deficient startle reactivity during the anticipation (but not the perception) of emotional pictures, whereas anhedonia would be associated with deficient modulation by pleasant pictures (across anti cipation and perception). Finally, negative affect would be associated with heightened startle reactivity across all conditions. Overall, these predictions were not supported. The relationship between the apathy construct and anticipatory responding was not observed, though one specific apathy subscale indexing social apathy was associated with blunted potentiation during

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151 the anticipation of both negative and positive pictures. The relationship between the derived negative affect factor and startle hyper r eactivity was observed, but only in analyses involving the negative perception condition. Finally, anhedonia was not consistently related to any of the psychophysiology variables. In the section below, obtained findings will be discussed. Apathy Anticipa tion. The predicted relationship between the apathy construct and diminished anticipatory responding was not observed. As described earlier, this prediction was made because apathy has been associated with reductions in arousal and motivation which are bo th necessary for the generation of emotional expectancy. One reason why associations were not significant is that these factor scores may reflect more than just apathy. In the CFA, the apathy factor loaded extremely highly on the global affective disturbance factor (standardized factor loading = .98), and it was highly correlated with the negative affect factor ( r = .78). Despite the lack of a relationship between the apathy construct and anticipatory responding, there were unexpected relationships involv ing individual measures of apathy. Specifically, diminished startle potentiation during the anticipation phase was correlated with higher (worse) scores on the LARS Self Awareness scale. This subscale has been viewed as reflecting social apathy. It inclu des four items that pose questions such as: after having made a decision, do you sometimes think that youve made the wrong choice? and when youve been unpleasant to someone, do you sometimes feel guilty afterwards? Social apathy is a more abstract, m eta cognitive form of apathy than is behavioral, cognitive or affective apathy (Dujardin et al., 2007; Stuss, Van Reekum &

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152 Murphy, 2000). It has been described as lacking a mental model of ones self that organizes perceptions and actions (Stuss, Van Reekum, & Murphy, 2000). From this perspective, one might consider whether social apathy corresponds to some aspect of self monitoring. The basis for the relationship between social apathy and reduced anticipatory startle reactivity is unknown. One highly speculative explanation is that both the metacognitive act of creating a mental model of ones self and the act of engaging in elaborative working memory rehearsal require sophisticated cognitive resources. Thus, the association between social apathy and reduced startle potentiation during anticipation may reflect a working memory deficit related to cognitive impairment. Indeed, one study examining the LARS subscales in a sample of 159 PD patients (39 with DSM IV dementia) found that Self Awareness scores were mainly determined by cognitive status (Dujardin et al., 2007). In the present study, if participants with worse scores on the LARS Self Awareness subscale were more cognitively impaired, then the relationship between this subscale and reduced psychophysiologic reactivity during the anticipation could be driven by working memory impairment. In the present study, we did not find a significant relationship between LARS Self Awareness and a global dementia screening measure (DRS 2). However, it is possible that more specific cognitive indices of frontal executive function may have been more sensitive to such a relationship. Perception. As predicted, the apathy construct was not associated with startle modulation during the perception period. However, there was an unexpected relationship involving a specific test that was excluded from the factor analysis due to its

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153 extremely high relationship with global affective disturbance. Specifically, the AS was associated with enhanced startle modulation during the perception of normatively classified positive pictures. This relationship was not present for negative pictures. Turning to subjectively classified pictures, there was an association between AS scores and enhanced startle reactivity during negative pictur e viewing. The basis for these unexpected results is unclear and should be interpreted with caution due to the exploratory nature of these correlational analyses. One potential explanation for this unexpected association between AS scores and enhanced startle modulation during perception is that the AS is highly sensitive to general affective disturbance in PD and is therefore not a pure measure of apathy. Indeed, the AS was not included in the CFA analyses because its inclusion produced errors in the mo del. Specifically, its inclusion rendered the latent apathy factors loading on the global affective disturbance factor so high that negative residual variance in the apathy factor was produced. The AS correlated very highly with negative affect factor sco res (r = .74, p < .001) and all of the individual scores that composed that factor ( r s from .46 for PANAS Negative to .74 for STAI trait, all p s < .001). Supportive of this interpretation is the fact that LARS Self Awareness, which was least correlated with indicators of negative affect, exhibited the opposite relationship with a psychophysiology variable during perception, as compared to the AS. Specifically, higher (worse) scores on LARS Self Awareness were associated with reduced emotion modulation during the viewing of subjectively classified positive pictures Although also unexpected, this finding is similar to that observed during

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154 anticipation, in which worse scores on this subscale were also correlated with reduced emotion modulation. Again, the b ases for these unexpected and somewhat varying relationships between apathy scores and different components of startle responding are unknown. Whether they reflect some meaningful relationships (i.e., cognitive sensitivity) or is merely a set of spurious f indings is unclear. For example, no evidence for the construct of social apathy/self awareness was found in a recent factor analysis of the AS (Kay et al., 2010). Instead, the typical three factors (i.e., behavioral, cognitive, affective) were obtained. Similarly, the LARS Self Awareness subscale had the lowest loading (though significant) on the apathy latent factor in Aim 1. In addition, this subscale exhibited the lowest overall correlation (though significant) with total LARS score and the other three subscales in a study examining the psychometric properties of the LARS in PD (Zahodne et al., 2009). A recent study conducted in our lab did not find significant differences on LARS subscale scores of Emotion or Self Awareness between individuals classifi ed as apathetic or not based on AS scores (Ferencz, Bogorodskaya, Okun, & Bowers, submitted). In addition, neither of these subscales correlated with an objective, behavioral measure of apathy (i.e., Novelty Toy Task). Summary. In summary, the predicted relationship between apathy and diminished anticipatory responding was not observed. However, there were unexpected relationships involving individual scores in exploratory correlational analyses. These individual scores included the LARS Self Awareness subscale, which demonstrates low convergent and external validity, and the AS, which demonstrates low divergent validity with negative affect and was excluded from the initial CFA due to its extremely high

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155 relationship with global affective disturbance. Addi tional research is needed to determine whether these associations reflect meaningful or spurious relationships. Anhedonia Contrary to our predictions, there were no significant relationships between the anhedonia construct and psychophysiology variables d uring the anticipation or perception of positive pictures. Turning to individual tests, there was an unexpected association between anticipatory anhedonia (i.e., TEPS Anticipatory subscale) and enhanced psychophysiologic blunting during the viewing of pict ures that were subjectively classified as positive. The basis for this unexpected association is unclear and should be interpreted with caution due to the exploratory nature of these correlational analyses. Since the relationship was only observed for pict ures that were subjectively classified as positive, it may relate to differing subjective experiences of positive pictures. Negative Affect Negative affect factor scores computed using factor coefficients from the CFA were correlated with enhanced emotio n modulated startle during perception as well as startle potentiation during the viewing of subjectively classified negative pictures. These associations between negative affect and greater emotionmodulated startle during perception, particularly during t he viewing of negative pictures, was the only finding to emerge from the more robust Aim 3 correlations between the three factor scores and the psychophysiology variables. A dditional analyses using scores on individual scales and subscales revealed that this association was driven by positive correlations among trait anxiety, dysphoria,

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156 and startle potentiation to negative pictures. These findings provide support for the interpretation that exaggerated startle potentiation to negative pictures found in the depressed PD group is likely related to heightened sensitivity to aversive stimuli Further, this effect is likely mediated by negative affect (particularly dysphoria and anxiety) rather than other components of depression. Overall Conceptual Perspective This study provides strong psychometric support for separate components of PD depression. Specifically, latent constructs of apathy, anhedonia and negative affect (as measured with a large battery of psychological instruments) were viable in this sample. However, validation of these constructs using separate samples of depressed individuals with PD is needed. It should be noted that the clinical administration of the full battery of instruments used in this study is not practical. An initial clinical appr oach to assessing these depression components is to specifically query a patient about symptoms related to each component during a diagnostic interview. Given that each of the psychological instruments used in this study loaded significantly on its proposed latent factor, a clinician may also be able to index each of the three depression components with only one instrument per component (e.g., BDI II dysphoria subscale, SHPS and LARS). Assessing the relative prominences of these depression components is im portant for clinicians attempting to treat the specific affective disturbance of an individual patient with PD. For example, selective serotonin reuptake inhibitors (SSRIs), which are the class of antidepressants most commonly prescribed for PD depression (Chen et al., 2007), address symptoms of general distress and anxiety, but not motivation and

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157 hedonic responding (Shelton & Tomarken, 2001). Furthermore, SSRIs may actually induce apathy in 2040% of adult patients (Sansone & Sansone, 2010). At this point there are no specific evidence based treatments for apathy in PD per s. This is unfortunate given its high occurrence in PD and the resulting negative consequences. These consequences can include physical deconditioning, worse performance on activities of daily living, reduced quality of life, uncooperativeness with care, social isolation, adverse interpersonal interactions, and caregiver distress (van Reekum, Stuss, & Ostrander, 2005). The affective chronometric pattern of psychophysiologic responding identified in this group of depressed PD patients does not support a conceptualization of PD depression as characterized by broad emotional context insensitivity. Rather, it suggests that mild to moderate PD depression involves: 1) A reduction in the abil ity to generate emotional expectancy and 2) Hyper responsiveness to negative emotional stimuli. These findings can be considered in light of recent evidence for muted psychophysiologic reactivity during both anticipation and perception among more severely depressed individuals without PD (Dichter & Tomarken, 2008). Together, these results are consistent with a conceptualization of depression as involving a shift from broad defense system sensitization in the mild to moderate stages to generalized inhibitory physiologic mode in the severe stages (Vaidyanathan, Patrick, & Cuthbert, 2009; Cuthbert et al., 2003; Seligman, 1975). A future study in which a larger sample of depressed individuals exhibiting a range of symptom severities is required to test this mode l. Demonstration of differing physiologic signatures in mild/moderate versus severe depression would have important implications for treatment planning.

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158 The componential framework for PD depression did not fully map onto patterns of psychophysiological responses in the present anticipation/perception pictureviewing paradigm. Specifically, there was minimal evidence that a derived apathy construct was related to blunted startle modulation during anticipation, but there was good evidence that a derived negative affect construct was related to hyper reactivity to negative material during perception. While it was predicted that negative affect would be related to hyperstartle responding in all conditions, negative affect was only related to hyperstartle responding during a single condition (i.e., perception of negative pictures), which suggests that the effect of negative affect on psychophysiologic responding is context specific. Also contrary to our expectations was the finding that the anhedonia component was not consistently related to any of the psychophysiology variables. Thus, the componential framework only partially explained patterns of emotionmodulated startle psychophysiology in the present study. One potential explanation for the lack of overlap between the depression components and emotionmodulated startle psychophysiology relates to the fact that emotional experience involves more than just physiological responses. The components of PD depression studied here may differentially map onto variables reflecting cognitive appraisal, subjective experience, and/or decisionmaking. For example, even though the anhedonia scales were not correlated with physiological variables in the current study, they were the only psychological measures to correlate with subjective ratings of picture valence in the positive condition in post hoc analyses. Thus, this component may be more strongly linked to the cognitive/interpretative aspect of emotional experience than to the physiological aspect. This study provides str ong psychometric support for the

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159 existence of separate components of affective disturbance that can differentially discriminate PD depression. Future studies may benefit from exploring relationships between these components and other outcome variables. Li mitations The major limitation of the present study lies in the small size of the subset of individuals who participated in the psychophysiology paradigm, particularly in the depressed PD group. Unfortunately, the majority of PD patients who met DSM IV criteria for depression in Study 1 were unwilling to participate in Study 2, which required a visit to another location (i.e., McKnight Brain Institute). Overall, small sample size may have contributed to our inability to document group by affect condition interactions in the omnibus ANOVAs conducted in Aim 2. Because we had specific a priori predictions regarding the expected patterns of startle psychophysiology within each of the three participant groups, withinsubjects effects were examined. Because onl y 10 depressed PD patients participated in the psychophysiology paradigm, our sample size was too small to explore potential differences between depressed participants with and without sad mood or on versus off antidepressant medications. Finally, the relatively small sample size of the overall PD group participating in Study 2 (N = 30) also limited the power of analyses intended to explore relationships between the psychological and psychophysiological variables. For example, a larger sample size may have rendered the medium sized negative correlations between apathy factor scores and startle potentiation during anticipation significant. Another limitation is the use of factor scores to index the depression components. While factor scores were presumably more reliable indices of the

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160 depression components than were individual scores on the self report measures, they were still derived from these scores. Therefore, they still contained measurement error that could have diluted the results. A larger sample si ze could have allowed for Aim 3 analyses to be carried out entirely within a structural equation modeling framework. By virtue of constructs being free of measurement error in such a framework, more precise quantification of relationships between the psychological constructs and the psychophysiology variables may have been achieved. A related limitation worth noting relates to overlapping variance of the factor scores. While commonly used collinearity diagnostics computed for the Aim 3 regressions did not indicate gross violations of the independence assumption, factor scores were highly correlated nonetheless. Therefore, multicollinearity may have limited our ability to extract unique relationships between the psychological constructs and the psychophysiol ogy variables. This issue of multicollinearity is most problematic for analyses involving apathy factor scores, which were highly correlated with factor scores of negative affect. Conclusions and Directions for Future Research This study supports the concept that affective disturbance in PD is heterogeneous and can produce symptoms of apathy, anhedonia, and negative affect. Apathy appears to be the core neuropsychiatric feature of PD in general, while negative affect (e.g., dysphoria, anxiety) is most pat hognomic of PD depression. Practically, these findings suggest that clinicians should be mindful of apathy among their PD patients, as this symptom is likely to be the most sensitive indicator of general affective disturbance and may be accompanied by other psychological symptoms. In addition,

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161 the presence of negative affect, not apathy, should be considered stronger evidence for the presence of depression. This latter point is particularly important given that antidepressant medications may ameliorate symptoms of depression related to negative affect, but not to apathy. An interesting finding of this study was a strong, positive association between apathy and negative affect. Such an association seems counterintuitive, as the former is thought to reflect di sengagement and a lack of extreme emotionality, while the latter is thought to reflect enhanced emotionality in the form of anxiety, worry, and dysphoria. While there was a strong correlation between negative affect and apathy factor scores in the total gr oup of 95 PD patients ( r = .78) and in the subgroup of 15 depressed PD patients with complete data who reported sad mood as a primary depressive symptom ( r = .60), this correlation was entirely absent in the subgroup of 8 depressed PD patients with complet e data who did not report sad mood as a primary depressive symptom ( r = .00). Levels of apathy did not differ between depressed patients with and without sad mood. These findings are consistent with those of KirschDarrow (2009), who reported that in a sam ple of 161 nondemented PD patients, pure apathy was rarely associated with clinical elevations in anxiety, while mixed apathy and depression was associated with high anxiety. Apathy can be understood both as a neuropsychiatric syndrome, associated wit h neurological damage due to disease or injury, and as a psychological reaction, associated with uncontrollable stress. Marins (1991) description of apathy is of a neuropsychiatric syndrome, while other authors describe reactive apathy as a core feature o f helplessness associated with depression (Seligman, 1992). These two

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162 potential types of apathy (i.e., neuropsychiatric versus psychological) may produce different psychophysiologic signatures. Indeed, denial of symptoms in nonneurological, traumatized subjects is associated with elevated autonomic reactivity (Pennebaker, Hughes & OHeeron, 1987; Hughes, Uhlmann, & Pennebaker, 1994). In contrast, reduced self awareness in the context of a neuropsychiatric syndrome of apathy following traumatic brain injury is associated with reduced autonomic reactivity (Andersson, Gundersen, & Finset, 1999). Similarly, aged rats have been shown to exhibit reduced exploratory behaviors due to either increased arousal (i.e., neophobia) or decreased arousal (i.e., apathy ) (Lalonde & Badescu, 1995). However, the idea of different types of apathy may be a false dichotomy, as clinical apathy likely involves both neurophysiologic and reactive components in most patients. Future studies should explore whether apathy scales are measuring slightly different underlying constructs in different subsets of PD patients (e.g., those with and without comorbid anxiety/depression). It should also be explored whether different apathy domains (e.g., behavioral apathy) are more sensitive or specific to reactive distress versus neuropathology. As the first examination of startle psychophysiology in PD depression, this study adds to the current literature by showing that depressed patients with PD exhibit reduced emotional expectancy and exaggerated physiologic threat responses. Depressed PD patients lack of emotionmodulated startle during anticipation may reflect a working memory deficit (due to reduced motivation and/or rumination) and/or a deficit in top down generation of arousal. In contrast, exaggerated responses during the perception of negative material may reflect hyper responsivity to an aversive context

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163 due to negative affect. That our understanding of the phenomenology and psychophysiologic response patterns associated with PD depression was enhanced by the applying the componential approach is supportive of its utility in the study of depression. As the heterogeneity of depression is more systematically recognized and researched, better models of its neuropathophysiology and more effective treatments can be designed.

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190 BIOGRAPHICAL SKETCH Laura Beth Zahodne was born in Royal Oak, Michigan. She earned a Bachelor of Science with high distincti on in biopsychology and cognitive s cience from the Univer sity of Michigan, where she served as manager of the Cognitive and Affective N europsychology Laboratory following graduation. She earned a Master of Science in clinical psychology from the University of Florida in 2008. As a doctoral student in the Departm ent of Clinical and Health Psychology at the University of Florida, she received a predoctoral T32 fellowship from the National Institute on Aging and specialized in neuropsychology She completed her predoctoral residency in clinical psychology at the A lpert Medical School of Brown University in 2012. Laura is currently completing a post doctoral research fellowship at the Taub Institute for Research on Alzheimers Disease and The Aging Brain in the Columbia University College of Physicians and Surgeons. She lives in New York City.