## Abstract

Impairments in executive functioning are commonly found in Parkinson's disease (PD); however, the research into risky decision making has been mixed. The present study sought to investigate three potential hypotheses: difficulty learning the task probabilities, levodopa equivalent dose (LED), and the presence of apathy. Twenty-four individuals with idiopathic PD and 13 healthy controls completed the Frontal Systems Behavior Scale to assess current apathy, the Iowa Gambling Task, and the Balloon Analog Risk Task (BART). Results indicated that individuals with PD selected more from Deck B, a disadvantageous deck. However, with an additional set of trials, participants with PD and apathy selected more from the most risky deck (Deck A). Apathy was not related to the BART, and LED was not related to either task. Results indicate that apathy is associated with decision-making in PD, and providing additional learning trials can improve decision-making in PD without apathy.

## Introduction

Parkinson's disease (PD) is a chronic neurological disorder associated with the depletion of dopamine in the substantia nigra and associated structures. Prominent executive dysfunction is the most common cognitive correlate in the disorder (Daum et al., 1995; Dubois, Pillon, Lhermitte, & Agid, 1990; Lees & Smith, 1983). Risky decision-making is one area of executive functioning that has gained recent research interest in PD, likely due to reports of increased impulse control disorders and risk-taking behavior in PD and the use of dopamine agonist medications (Dodd et al., 2005; Weintraub et al., 2006, 2010). As individuals with PD face numerous important decisions regarding treatment, work, and other aspects of life, it is important for clinicians and researchers alike to understand the nature of decision-making impairments that accompany PD.

Risky decision-making is typically assessed through lab-based behavioral tasks, such as the Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994). On the IGT, participants select cards one at a time from one of four decks, learning the relative risks and benefits associated with each deck during the course of the 100 selections. Two decks are disadvantageous (i.e., higher immediate rewards but long-term negative outcomes) and two decks are advantageous (i.e., lower immediate rewards but long-term positive outcomes; Bechara et al., 1994). Impaired performance on the IGT has been linked to prefrontal cortex functioning such as focal frontal lobe damage, damage to the amygdala and frontotemporal dementia (seeBuelow & Suhr, 2009, for a review).

To date, research into IGT performance in PD has been mixed. Of the published studies, nine have shown riskier performance in PD versus age-matched controls (Delazer et al., 2009; Gescheidt et al., 2012; Ibarretxe-Bilbao et al., 2009; Kawamura & Kobayakawa, 2009; Kobayakawa, Koyama, Mimura, & Kawamura, 2008; Kobayakawa, Tsuruya, & Kawamura, 2010; Mimura, Oeda, & Kawamura, 2006; Pagonabarraga et al., 2007; Perretta, Pari, & Beninger, 2005). In contrast, four studies showed no significant between-group differences (Czernecki et al., 2002; Euteneuer et al., 2009; Stout, Rodawalt, & Siemers, 2001; Thiel et al., 2003). Two additional studies compared subgroups of PD participants: individuals post-Deep Brain Stimulation (DBS) surgery (with no statistically significant change in medication dose post-surgery) showed improved decision-making on the IGT in comparison with matched-PD participants without DBS surgery (Oyama et al., 2011), and those with a diagnosis of PD with pathological gambling made riskier decisions on the task than those with PD only (Rossi et al., 2010). Of note, the examination of the patterns of performance in these two studies indicated that the DBS group would likely still be categorized as showing risky decision-making on this task in comparison with healthy controls (HCs), whereas the performance of those in the PD without the pathological gambling group would likely be consistent with HC performance. In sum, significant variability exists between studies in the pattern of performance on the IGT and in the relationship of risky decision-making with PD status.

It is unclear why there are such discrepant findings in studies of the IGT in PD. Both depression and dementia would not account for discrepancies, since they were exclusion criteria in several studies (Czernecki et al., 2002; Euteneuer et al., 2009; Ibarretxe-Bilbao et al., 2009; Kobayakawa et al., 2008; Mimura et al., 2006; Pagonabarraga et al., 2007; Perretta et al., 2005; Stout et al., 2001; Thiel et al., 2003) Also, no correlations were found between IGT performance and performance on other executive function measures (Mimura et al., 2006; Oyama et al., 2011; Rossi et al., 2010), so impaired executive functioning cannot alone account for this discrepancy on the IGT. There is some evidence that dopamine dosage levels can affect risk-taking behaviors (Frank, 2005; Frank, Seeberger, & O'Reilly, 2004), and thus further examination of the potential relationship between dopamine dosage and decision-making task performance is needed.

Risky decision-making and risk-taking have been investigated in PD utilizing another behavioral measure, the Balloon Analogue Risk Task (BART; Lejuez et al., 2002). On the BART, participants earn money by pumping up a balloon, but the earned money is lost if the balloon pops. Thus, participants have to weigh the relative risks and benefits of each successive pump. No differences were found in level of risk-taking on the BART when individuals with PD were compared with HC participants (Simioni, Dagher, & Fellows, 2012), but on a variation of the BART with 50 extra trials, Claasen and colleagues (2011) found that individuals with PD and an impulse control disorder performed riskier on the BART than those with PD but no impulse control disorder. Thus, it may be the presence of an impulse control disorder, not the presence of PD per se, that affects decision-making on this task. In sum, inconsistencies have been seen in performance on the IGT, and results with the BART have shown that impulse control disorders, not PD itself, may affect decision-making.

Apathy could also be affecting risky decision-making. Apathy can be defined as a loss of motivation and difficulty with initiation, persistence, and social engagement (Dujardin et al., 2007; Marin, 1991) and is associated with frontal lobe dysfunction (Cummings, 1993; Levy & Dubois, 2006). Prevalence of apathy in PD is difficult to assess, but estimates place it between 16.5% and 70% (Aarsland et al., 1999; Isella et al., 2002; Pluck & Brown, 2002). Apathy can occur in the absence of depression (Kirsch-Darrow, Fernandez, Marsiske, Okun, & Bowers, 2006), which supports the hypothesis that apathy and not depression affected performance on the IGT and BART. In addition, high levels of apathy can negatively affect performance on cognitive tasks among individuals with PD (Dujardin et al., 2007; Pluck & Brown, 2002), including on other measures of executive functions (Isella et al., 2002; Pessiglione et al., 2005). Good decision-making on the IGT and BART requires understanding of and sensitivity to rewards and punishments, and the presence of apathy in PD may help to explain the previous inconsistencies.

A final hypothesis is that individuals with a diagnosis of PD are experiencing difficulties learning the relative risks/benefits of each deck on the IGT, which would mimic impaired performance on the typical 100 trial IGT. In fact, several studies showed a pattern of performance among PD participants that could potentially reflect this slowed learning (i.e., switching to advantageous selections after 80 trials instead of 40–60 trials; Delazer et al., 2009; Ibarretxe-Bilbao et al., 2009; Oyama et al., 2011; Perretta et al., 2005). Individuals with PD may need additional trial-and-error attempts to learn from both positive and negative outcomes. Poorer outcomes have been shown on other cognitive tasks when individuals with PD must utilize trial-and-error feedback to learn (Ashby, Alfonso-Reese, Turken, & Waldron, 1998; Knowlton, Mangels, & Squire, 1996; Shohamy et al., 2004); thus, it is possible that risky decision-making in PD may disappear when additional learning trials are administered.

The present study sought to examine risky decision-making in PD as a function of levodopak equivalent dose (LED), apathy, and additional learning trials. The first study aim was to examine performance on the IGT and BART as a function of PD diagnosis, in order to attempt to clarify the discrepant findings on previous studies of the IGT and BART in PD. The second aim was to examine the effect of apathy on IGT and BART performance. It was hypothesized that individuals with PD and high levels of apathy would exhibit riskier performance on the tasks than individuals with PD but low levels of apathy and HCs. The third aim was to examine whether difficulties learning the relative risks and benefits on the IGT were due to a slowed rate of learning. It was hypothesized that performance on the IGT among individuals with PD would not be significantly different from performance on the IGT among controls during an additional 100 trials of the task. The final aim was to examine whether LED was associated with decision-making.

## Method

### Participants

PD patients were recruited from the Movement Disorders Clinic at a local hospital. Interested patients at the clinic completed a contact form to allow for telephone screening. Inclusion criteria included: (a) diagnosis of idiopathic PD made by movement disorders neurologist using UK Brain Bank criteria; (b) aged 45–79; and (c) stable on medication regimen for the previous 30 days. Participant age was restricted to 45–79 due to age-related changes on the IGT (Denburg, Recknor, Bechara, & Tranel, 2006; Denburg, Tranel, & Bechara, 2005; Fein, McGillivray, & Finn, 2007). Exclusion criteria included: (a) clinically significant depressive symptoms on the Geriatric Depression Scale, Short Form (GDS-S; total score greater than 7 for adequate sensitivity and specificity per Sheikh & Yesavage, 1986a, 1986b); (b) previous diagnosis of dementia or mild cognitive impairment (as indicated by patient or neurologist report); (c) history of heavy substance abuse/dependence; (d) history of pathological gambling (due to effects on the IGT; Buelow & Suhr, 2009); (e) history of significant head injury (i.e., loss of consciousness greater than 10 min); or (f) Mini-Mental Status Examination (MMSE) score less than 25.

An a priori power analysis for an analysis of variance (ANOVA) comparing three groups to detect a medium effect size with α = 0.05 indicated that a sample size of 12 participants per group was needed to obtain a power of 0.95. Inclusion and exclusion criteria, with the exception of MMSE score, were assessed via a preliminary telephone screening. Of the 37 PD patients who completed the telephone screening, 11 had one or more exclusion criteria (n = 5 over age 79, n = 4 with history of head injury, n = 1 with clinically significant depression, n = 1 with a diagnosis of dementia). In addition, two eligible participants declined to participate, leaving a final sample of 24 PD patients. All but two patients were currently treated with levodopa or a dopamine agonist, with an average LED across participants (calculated according to Pahwa et al., 1997) of 468.35 (SD = 319.74). Disease severity was in Hoehn and Yahr stages II–IV (n = 21 Stages II and III; n = 1 Stage IV).

Ten of the PD participants either self-reported or a family member or friend reported, a clinically significant level of current apathy (“PD with apathy” group) as assessed with the Frontal Systems Behavior Scale (FrSBe; Grace & Malloy, 2001). An additional 14 HC subjects were recruited from the friends and family members of PD participants. Participants in the HC group had no history of neurological disorder, and the exclusion criteria for the PD group were also applied to the HC group. One HC participant endorsed a significant level of apathy and was removed from further analysis.

### Data Analysis

Data were first examined for between-group differences in the demographic variables. One-way ANOVA, independent-samples t-tests, and Pearson's chi-square tests were used as appropriate, with Tukey's HSD post hoc comparisons used for any significant omnibus tests. In order to test the first aim of the study, independent-samples t-tests were conducted comparing the HC with the combined PD group on the IGT and BART. To test the second aim, one-way ANOVAs were conducted comparing performance on the IGT and BART in the HC, PD-apathy, and PD-no apathy groups. To test the third aim, one-way ANOVAs were conducted on the extra 100 trials of the IGT. In addition, learning scores were calculated by subtracting the percentage of selections from each IGT deck during Trials 61–100 from the percentage of selections from each IGT deck during Trials 161–200 (thus, positive scores indicated increased selections from the deck during the additional trials and vice versa). One-way ANOVAs were then used to assess for between-group differences on IGT learning. Finally, correlations were found between LEDs and performance on the IGT and BART.

## Results

### PD Status

#### Demographics

There were no significant differences between the control and the combined PD group in terms of age (p = .540), educational attainment (p = .748), gender (p = .217), or estimated premorbid verbal intellectual level (p = .244). No differences emerged between groups on the MMSE (p = .063), but individuals with PD had lower scores on the MoCA than HCs, t(35) = 1.990, p = .054 (Table 1). In addition, individuals in the PD group had greater GDS-S scores than those in the HC group, t(35) = −2.169, p = .037. No significant correlations were found between MoCA, MMSE, GDS-S, and the percentage of deck selections on the IGT (both Trials 61–100 and 161–200) and the average number of adjusted pumps on the BART (ps > .164), and thus these variables were not included as covariates in remaining analyses. PD participants had higher self-reported, t(35) = –2.043, p = .049, and informant-reported apathy, t(29) = –2.199, p = .036, than controls.

Table 1.

PD and HC study variables presented as mean (SD)

HC (n = 13) PD-combined (n = 24) PD-apathy (n = 10) PD-no apathy (n = 14)
Age 69.62 (6.36) 68.04 (7.86) 66.70 (9.96) 69.00 (6.19)
Education 15.92 (2.25) 15.63 (2.87) 14.50 (2.95) 16.43 (2.62)
Gender 6 men 13 men 7 men 6 men
H&Y — 2.36 (0.54) 2.56 (0.73) 2.23 (0.33)
UPDRS — 29.73 (9.62) 29.89 (13.14) 29.62 (6.85)
MMSE 29.31 (1.11) 28.33 (1.63) 27.80 (1.87) 28.71 (1.38)a
MoCA 27.77 (1.48) 26.33 (2.35)b 26.00 (2.31) 26.57 (2.44)
NART 119.54 (7.29) 116.92 (5.93) 116.90 (6.15) 116.93 (5.99)
GDS-S 1.15 (1.57) 2.50 (1.91)c 3.00 (2.45) 2.14 (1.41)
FrSBe-S 50.46 (10.39) 59.25 (13.46)c 68.60 (14.68) 52.57 (7.49)d
FrSBe-I 50.23 (10.32) 59.78 (12.95)c 70.86 (12.90) 52.73 (6.66)d
HC (n = 13) PD-combined (n = 24) PD-apathy (n = 10) PD-no apathy (n = 14)
Age 69.62 (6.36) 68.04 (7.86) 66.70 (9.96) 69.00 (6.19)
Education 15.92 (2.25) 15.63 (2.87) 14.50 (2.95) 16.43 (2.62)
Gender 6 men 13 men 7 men 6 men
H&Y — 2.36 (0.54) 2.56 (0.73) 2.23 (0.33)
UPDRS — 29.73 (9.62) 29.89 (13.14) 29.62 (6.85)
MMSE 29.31 (1.11) 28.33 (1.63) 27.80 (1.87) 28.71 (1.38)a
MoCA 27.77 (1.48) 26.33 (2.35)b 26.00 (2.31) 26.57 (2.44)
NART 119.54 (7.29) 116.92 (5.93) 116.90 (6.15) 116.93 (5.99)
GDS-S 1.15 (1.57) 2.50 (1.91)c 3.00 (2.45) 2.14 (1.41)
FrSBe-S 50.46 (10.39) 59.25 (13.46)c 68.60 (14.68) 52.57 (7.49)d
FrSBe-I 50.23 (10.32) 59.78 (12.95)c 70.86 (12.90) 52.73 (6.66)d

Notes: HC = healthy control; PD = Parkinson's disease; H&Y = Hoehn and Yahr staging; UPDRS = Unified Parkinson's Disease Rating Scale; MMSE = Mini-Mental Status Examination; MoCA = Montreal Cognitive Assessment; NART = American National Adult Reading Test; GDS-S = Geriatric Depression Scale, Short Form; FrSBe = Frontal Systems Behavior Scale, Self- (S) or Informant (I) Apathy subscale T score.

aHC > PD-apathy, p < .05.

bHC > PD, p < .05.

cHC < PD, p < .05.

dHC and PD-no apathy < PD-apathy, p < .01.

#### IGT analyses

No significant correlations emerged between LED and IGT deck selections (ps > .159). The PD group selected significantly more from Deck B than did the HC group (p = .017, d = 0.86; Table 2). No significant differences emerged for selections from Decks A (p = .491), C (p = .223), or D (p = .142).

Table 2.

Decision-making results: HC and PD-combined

HC (M [SD]) PD-combined (M [SD]) t p
BART-NA 36.38 (10.89) 28.03 (13.30) 1.912 .065
IGT
A61–100 12.50 (8.48) 10.65 (7.16) 0.696 .491
B61–100 21.15 (21.33) 38.48 (19.12) −2.505 .017
C61–100 20.19 (8.87) 16.41 (8.72) 1.242 .223
D61–100 45.19 (25.11) 33.70 (20.18) 1.503 .142
A161–200 7.12 (4.06) 15.22 (13.08) −2.164 .038
B161–200 31.15 (20.73) 33.70 (19.38) −0.369 .715
C161–200 28.27 (24.95) 22.83 (15.27) 0.815 .421
D161–200 33.46 (17.61) 28.15 (21.12) 0.767 .448
HC (M [SD]) PD-combined (M [SD]) t p
BART-NA 36.38 (10.89) 28.03 (13.30) 1.912 .065
IGT
A61–100 12.50 (8.48) 10.65 (7.16) 0.696 .491
B61–100 21.15 (21.33) 38.48 (19.12) −2.505 .017
C61–100 20.19 (8.87) 16.41 (8.72) 1.242 .223
D61–100 45.19 (25.11) 33.70 (20.18) 1.503 .142
A161–200 7.12 (4.06) 15.22 (13.08) −2.164 .038
B161–200 31.15 (20.73) 33.70 (19.38) −0.369 .715
C161–200 28.27 (24.95) 22.83 (15.27) 0.815 .421
D161–200 33.46 (17.61) 28.15 (21.12) 0.767 .448

Notes: HC = healthy control; PD = Parkinson's disease; BART = Balloon Analogue Risk Task, average number of adjusted pumps; IGT = Iowa Gambling Task (A, B, C, D = percentage of cards selected from the individual deck on Trials 61–100 or Trials 161–200).

On the additional 100 trials, participants in the PD group selected significantly more from Deck A than participants in the HC group (p = .038, d = 0.84). No differences emerged for selections from Decks B (p = .715), C (p = .421), or D (p = .448).

#### BART analyses

No significant between-groups differences emerged (p = .065), and LEDs were not correlated with performance (p = .159).

### Effect of Apathy

#### Demographics

Comparing the HC, PD-apathy, and PD-no apathy groups, no significant differences emerged with regard to age (p = .630), educational attainment (p = .204), gender (p = .380), NART score (p = .512), or performance on cognitive screening (MMSE: p = .059, MoCA: p = .131; Table 1). Self- and informant-reported apathy was significantly higher in the PD-apathy group compared with the PD-no apathy and HC groups—self: F(2,34) = 9.218, p = .001; other: F(2,28) = 10.773, p < .001. Due to the small size of the PD-apathy and PD-no apathy groups, the following analyses should be considered preliminary.

#### IGT analyses

There was a trend toward the HC group selecting significantly less from Deck B than the PD-apathy group (p = .059, partial η2 = .16; Table 3). No significant differences emerged for selections from Decks A (p = .410), C (p = .294), or D (p = .163).

Table 3.

Decision-making results: Apathy analyses

HC (M [SD]) PD-apathy (M [SD]) PD-no apathy (M [SD]) F p
BART-NA 36.38 (10.89) 30.09 (16.06) 26.32 (10.94) 2.046 .146
IGT
A61–100 12.50 (8.48) 12.75 (9.24) 9.04 (4.85) 0.916 .410
B61–100 21.15 (21.33) 39.75 (22.16) 37.50 (17.32) 3.087 .059a
C61–100 20.19 (8.87) 18.50 (8.91) 14.81 (8.57) 1.272 .294
D61–100 45.19 (25.11) 27.25 (20.96) 38.65 (18.86) 1.915 .163
A161–200 7.12 (4.06) 21.50 (12.37) 10.38 (11.85) 6.292 .005b
B161–200 31.15 (20.73) 40.50 (21.14) 28.46 (16.88) 1.143 .331
C161–200 28.27 (24.95) 22.75 (13.20) 22.88 (17.23) 0.322 .727
D161–200 33.46 (17.61) 15.25 (12.77) 38.08 (21.22) 4.954 .013c
HC (M [SD]) PD-apathy (M [SD]) PD-no apathy (M [SD]) F p
BART-NA 36.38 (10.89) 30.09 (16.06) 26.32 (10.94) 2.046 .146
IGT
A61–100 12.50 (8.48) 12.75 (9.24) 9.04 (4.85) 0.916 .410
B61–100 21.15 (21.33) 39.75 (22.16) 37.50 (17.32) 3.087 .059a
C61–100 20.19 (8.87) 18.50 (8.91) 14.81 (8.57) 1.272 .294
D61–100 45.19 (25.11) 27.25 (20.96) 38.65 (18.86) 1.915 .163
A161–200 7.12 (4.06) 21.50 (12.37) 10.38 (11.85) 6.292 .005b
B161–200 31.15 (20.73) 40.50 (21.14) 28.46 (16.88) 1.143 .331
C161–200 28.27 (24.95) 22.75 (13.20) 22.88 (17.23) 0.322 .727
D161–200 33.46 (17.61) 15.25 (12.77) 38.08 (21.22) 4.954 .013c

Notes: HC = healthy control; PD = Parkinson's disease; BART = Balloon Analogue Risk Task, average number of adjusted pumps; IGT = Iowa Gambling Task (A, B, C, D = percentage of cards selected from the individual deck on Trials 61–100 or Trials 161–200).

aHC < PD-apathy.

bHC and PD-no apathy < PD-apathy.

cHC and PD-no apathy > PD-apathy.

As there was a trend toward a relationship between apathy and IGT performance over the first 100 trials, we decided to examine whether apathy played a role in the additional 100 trials. In fact, individuals in the HC and PD-no apathy groups selected significantly less from Deck A than individuals in the PD-apathy group (p = .005, partial η2 = 0.28). HC and PD-no apathy groups also selected significantly more from Deck D on Trials 161–200 than those in the PD-apathy group (p = .013, partial η2 = 0.23). No differences emerged for Decks B (p = .331) or C (p = .727). Finally, the examination of the learning scores indicated that individuals in the PD-apathy group selected more from Deck A over time than individuals in the HC group (p = .021, partial η2 = 0.21).

#### BART analyses

No significant between-groups differences emerged (p = .146).

## Discussion

The present study sought to clarify inconsistent findings regarding the relationship between risky decision-making, as assessed by the IGT and BART, and PD status by examining the effects of apathy, LEDs, and difficulties learning to choose advantageously. The first aim was to clarify the relationship between PD status and risky decision-making. We found that on a deck-level analysis of the standard IGT, individuals with PD selected more from Deck B than HCs. This is the first investigation of the IGT in PD in which individual deck selections were examined, and although Deck B is considered a disadvantageous deck based on negative long-term outcomes, it is not considered as disadvantageous as Deck A (Bechara, 2008). It is possible that PD participants selected from Deck B based on its high immediate rewards (which Deck A also has) and its low frequency of losses (losses on 10% of trials vs. losses on 50% of trials with Deck A). Previous research with IGT variations has shown that HC participants will choose more from decks with a lower frequency of losses but long-term losses than decks with a higher frequency of losses but long-term gains (Caroselli et al., 2006; Chiu et al., 2008; Lin, Chiu, & Huang, 2009). This Deck B preference may help explain some of the previous inconsistencies on the IGT in PD that have utilized the standard scoring (i.e., advantageous minus disadvantageous selections; Czernecki et al., 2002; Delazer et al., 2009; Euteneuer et al., 2009; Gescheidt et al., 2012; Ibarretxe-Bilbao et al., 2009; Kawamura & Kobayakawa, 2009; Kobayakawa et al., 2008, 2010; Mimura et al., 2006; Pagonabarraga et al., 2007; Perretta et al., 2005; Stout et al., 2001; Thiel et al., 2003).

No significant differences between the HC and PD groups were found on the BART, consistent with previous studies suggesting that it is the presence of impulse control disorders, not PD itself, affecting performance on this task (Claasen et al., 2011; Simioni et al., 2012). The differing findings based on the type of risky decision-making task administered are consistent with previous research showing little overlap in the predictive utility of the IGT and BART in substance use and other risk-taking behaviors (Aklin, Lejuez, Zvolensky, Kahler, & Gwadz, 2005; Lejuez et al., 2003; Upton, Bishara, Ahn, & Stout, 2011). It is believed that the BART and IGT assess different components of risky decision-making. For example, the advantages and disadvantages of each deck must be learned on the IGT, whereas on the BART the amounts to be gained/lost are provided. In addition, the amounts of money won/lost are significantly greater on the IGT. It is possible that the IGT assesses learning from feedback, and the BART assesses more frank risk-taking. Future research into decision-making in PD should continue to utilize multiple assessment measures to more fully assess the construct.

The second aim was to investigate the potential role of apathy in risky decision-making. Our results provide initial evidence that apathy does have a relationship with decision-making in PD. Specifically, we found a trend toward the PD-apathy group selecting significantly more than the HC group from Deck B, a deck associated with losses on only 10% of trials but ultimately long-term negative outcomes (Bechara, 2008), during decision-making under risk on the standard IGT. This preliminary finding, given the small sample size, shows that our previous finding of the PD group (independent of apathy) Deck B preference was likely influenced by the apathy level. Thus, individuals with PD and apathy may be sensitive to the low frequency of losses and higher short-term gains of Deck B. Again, no group differences emerged on the BART, providing further evidence that it assesses a different component of risky decision-making in PD than the IGT. In addition, other questionnaires collected during the study session that assessed impulsivity and state mood were not associated with decision-making task performance in controls or PD participants (with or without apathy).

The third study aim was to investigate whether individuals with PD experienced difficulties learning the risks/benefits on the IGT, in turn leading to poorer performance on this task. Increasing the number of learning trials resulted in similar performance between the HC and PD-no apathy groups, as both groups preferred Deck D, the most advantageous deck. However, with an additional 100 trials, individuals with PD and apathy selected more from Deck A on Trials 161–200 than those in the PD-no apathy group, and less from Deck C than those in the HC and PD-no apathy groups. The present findings indicate that with an additional 100 trials and more time to learn the risks/benefits of decisions, a subgroup of PD participants (those with apathy) selected from the deck associated with “pathological” risk-taking (Bechara, 2008), whereas those with PD but no apathy learned to select advantageously.

The final aim was to examine the effect of LED on decision-making. No correlations were found between decision-making and LED. Although previous research has shown a link between reward-based learning, risk-taking, and dopamine levels (Frank, 2005; Frank, Seeberger, & O'Reilly, 2004; Ljungberg, Apicella, & Schultz, 1992; Mirenowicz & Schultz, 1994; Moustafa, Cohen, Sherman, & Frank, 2008; van Eimeren et al., 2009; Voon et al., 2010), we failed to find a relation between LED and reward-based decision-making in the present study.

The present findings have important implications for clinical practice. We recommend that clinicians utilize multiple behavioral measures of the decision-making construct in order to fully assess its facets. Utilizing the IGT, for example, may provide evidence of impaired learning of risks and benefits associated with different decisions, differing emphases on short- versus long-term risks and benefits, and poor emotion-based decision-making. Use of the BART may instead help to assess impaired risk-taking behaviors (i.e., impulsivity). We also recommend that clinicians assess for both depression and apathy in patients with PD, as both conditions can affect performance on measures of decision-making and other cognitive abilities. Finally, we recommend that clinicians consider administering an additional 100 trials of the IGT, in order to differentiate between slowed learning of the risks/benefits of their decisions and frank decision-making impairment.

There were several limitations to the present study. As previously discussed, our sample of individuals with PD and clinically significant apathy was small. Thus, it is important for the present findings to be replicated in a larger sample of PD participants with and without apathy. In addition, individuals with a significant level of current depressive symptoms were excluded from the present study. We found between-group differences in depression scores, although GDS-S scores were not correlated with the decision-making variables. In future studies, the effect of a combination of depression and apathy in individuals with PD on risky decision-making should be examined, as both apathy and depression on their own can influence decision-making. In addition, future research with larger samples should investigate whether the presence of depressive symptoms affects decision-making independent of apathy. Future research should also clarify whether overall level of cognitive functioning, such as that assessed with the MMSE or MoCA, is associated with performance on behavioral decision-making tasks in PD. Our sample was highly educated (average 15–16 years), and additional research with lower educational levels is warranted as educational level and premorbid cognitive ability have been shown to influence performance on some decision-making tasks. Finally, only two participants in the present study were not currently prescribed levodopa or a dopamine agonist, preventing direct examination of whether the presence or the absence of levodopa or other agonist medication affected decision-making.

Taken together, our results provide the first evidence that apathy is related to risky decision-making in PD, and providing additional learning trials can result in improved decision-making in those without apathy. Future research should utilize multiple measures of risky decision-making, such as the IGT, BART, Columbia Card Task (CCT; Figner & Voelki, 2004), and Game of Dice Task (GDT; Brand et al., 2005), to determine what aspects of risky decision-making are affected by PD staging, LEDs, apathy, and other variables. The CCT and GDT both utilize more explicit information about the risks and benefits of decisions and may provide clinicians and researchers alike with information about whether the lack of explicit information on the IGT is affecting performance in PD. In addition, future research should continue to examine how apathy—with and without comorbid depression—can affect cognition and quality of life in PD. Researchers could choose to evaluate and then control for apathy in studies, or use apathy as a variable of exclusion in participant recruitment. In addition, the manipulation of the apathy level would allow for the understanding of the potential cause-and-effect relationship between apathy and cognitive task performance.

## Funding

This research was supported by a grant from the Brown Clinical Psychology Training Consortium Postdoctoral Fellowship Competitive Grant Program. The funding source had no involvement in the study design, data collection, analysis, or interpretation, in the writing of the manuscript, or in the decision to submit the article for publication.

## Conflicts of Interest

The authors' financial conflicts of interest are as follows. JG: Psychological Assessment Resources (royalties). JHF: Teva, Ingelheim Boehringer, General Electric (lectures); United Biosource, Bubaloo Halsted & Reitman LLC, EMD Serono, Genzyme, Teva, Acadia, Addex Pharmaceuticals, Schwarz Pharmaceuticals, Roche (consulting); Michael J. Fox Foundation, National Institutes of Health, Cephalon, EMD Serono, Teva, Acadia (research); and Demos Press (royalties).

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