Reward sensitivity and anger in euthymic bipolar disorder

Psychiatry Research 215 (2014) 95–100

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Reward sensitivity and anger in euthymic bipolar disorder Or Duek a,n, Yamima Osher b, Robert H. Belmaker c, Yuly Bersudsky b, Ora Kofman a a b c

Department of Psychology, Ben Gurion University of the Negev, Beer Sheva, Israel Beer Sheva Mental Health Center, Department of Psychiatry, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel Bipolar Disorders Clinic, Hadassah Medical Center, Jerusalem, Israel

art ic l e i nf o

a b s t r a c t

Article history: Received 17 February 2013 Received in revised form 19 October 2013 Accepted 22 October 2013 Available online 30 October 2013

According to the hypersensitive behavioral approach system (BAS) model of bipolar disorder (BP), hypersensitivity of the BAS is a trait that should be present even in the euthymic state. This would be expected to result in increased anger and reward sensitivity, both of which are related to the approach system. This study examined these predictions through the use of tasks that assess different aspects of the BAS: reward sensitivity, anger and impulsivity. These characteristics were assessed using the probabilistic classification task (PCT), ultimatum game (UG) and single key impulsivity paradigm (SKIP), respectively. Participants were euthymic adult bipolar disorder patients (BP; N ¼40) and healthy controls (HC; N ¼41). In the UG, all participants showed the standard pattern of rejecting overtly unfair offers and accepting clearly fair offers; however, BPs rejected more of the moderately unfair offers than did HCs. BP and HC participants did not differ on their ability to learn, but did show different patterns of learning from reward and punishment. Learning for reward and punishment were negatively correlated in the BP group, suggesting that individuals could learn well either from reward or punishment, but not both. No correlation was found between these forms of learning in the HC group. BP patients show signs of their disorder even in the euthymic state, as seen by the dysbalance between reward and punishment learning and their residual anger in the UG. & 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords: Bipolar Reinforcement sensitivity theory BAS hypersensitivity model ultimatum game

1. Introduction One model of bipolar (BP) disorder (Depue et al., 1989), proposes that it involves a hypersensitive behavioral approach system (Depue and Iacono, 1989; Urosevic et al., 2008). This model is consistent with some studies which have used structural and functional neuroimaging of BP patients (Strakowski et al., 1999; Noga et al., 2001; Almeida et al., 2010). The current study examines three behavioral manifestations of the model—reward sensitivity, anger and impulsivity—in euthymic BP patients and matched controls. Since 1989, when Depue suggested that BP patients suffer from a hyper-sensitive behavioral approach system, which he termed the behavioral facilitation system (Depue et al., 1989), there has been a considerable amount of research in this field. Depue proposed that several major systems in the brain direct and motivate behavioral responses to significant stimuli (Depue et al., 1989). Gray and others suggested the reinforcement sensitivity theory (RST) as a framework for investigating motivated behavior. According to RST (Gray and McNaughton, 2000) there are three behavioral systems which organize human behavior. The first is the behavioral approach

n

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0165-1781/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2013.10.028

system (BAS), which is responsible for organizing behavior directed towards appetitive stimuli, is sensitive to stimuli that signal reward and the relief from punishment and is responsible for initiation of motor responses, positive affect, reward motivation and anger (Harmon-Jones and Allen, 1998; Depue and Collins, 1999). The BAS has been correlated to the activation of mesolimbic and mesocortical dopamine pathways in the brain, including the source of the projections in the ventral tegmental area, and the terminal regions of these projections in the nucleus accumbens and the orbitofrontal cortex, anterior cingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC) (Depue and Iacono, 1989; Depue and Collins, 1999; Berns et al., 2001). The second system, the fight flight freeze system (FFFS) is responsible for organizing behavior in response to aversive stimuli; it copes with an explicit danger that can be avoided or escaped. The third system, the behavioral inhibition system (BIS) is dominant during goal conflict resolution, including conflicts between: approach and avoidance (fight or flight), approach-approach or avoidance-avoidance. According to the BAS hypersensitivity model, individuals with BP disorder are subject to extreme fluctuations in activation and deactivation of this system. This will result in exaggerated approach to rewarding stimuli when activated, alternating with indifference to reward, when deactivated. This would lead to hypomanic/manic and depressive symptoms, respectively (Depue et al., 1989). High

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BAS scores have been correlated with bipolar symptoms (Alloy et al., 2006, 2008), and euthymic BP patients have been shown to score higher than healthy controls (Alloy et al., 2008) on the Barrat Impulsivity Scale (Barrett et al., 1996). Neuroimaging studies have provided circumstantial support for the BAS hypersensitivity model. Structural imaging studies found that the size of the amygdala of BP patients, which was correlated to emotional behavior and reward (Baylis and Gaffan, 1991; Aggleton, 1993), is significantly larger than that of healthy subjects (Strakowski et al., 1999). It has also been suggested that caudate enlargement may indicate a predisposition to bipolar disorder: Noga et al. (2001) found that both affected and unaffected monozygotic twins discordant for bipolar disorder had larger left caudate nuclei compared to the healthy participants (Noga et al., 2001), which may be related to altered reward sensitivity. Functional imaging studies indicate that adult (Almeida et al., 2010) and pediatric (Pavuluri et al., 2009) BP patients have higher activity levels in the amygdala and lower activity levels in several frontal cortical regions involved in emotional regulation, such as the ventro-lateral prefrontal cortex (VLPFC), dorso-lateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC). Self-report measures of trait anger and aggression have been positively associated with self-report measures of BAS (HarmonJones, 2003). BP patients, when manic, have been found to be more aggressive than other psychiatric patients (Látalová, 2009), although no studies reporting aggressive behavior in euthymic bipolar patients were found. This study examines the BAS hypersensitivity model of BP disorder via the use of behavioral tasks. Reward sensitivity was assessed by a probabilistic learning task (Bodi et al., 2009). This task was chosen because of its ability to differentiate learning motivated by reward and punishment. One of the most known reward-related tasks that was tested on BP patients is the Iowa Gambling Task (IGT) (Bechara et al., 1994). Some authors did find that BP patients in different mood states (manic, depressed or euthymic) chose a nonprofitable learning strategy (i.e.—chose more cards from the risky deck), while others found that only acute (manic, hypomanic or depressed) BP patients showed impaired decision making in the IGT (Yechiam et al., 2008; Adida et al., 2011). A recent meta-analyses was unable to detect consistent group differences between BP and healthy controls on the IGT (Edge et al., 2012), and the suggestion that euthymic BP patients are impulsive remains unresolved. Both the PCT and IGT assess learning involving reward and punishment which is at first implicit, but may involve a more explicit form of learning as the session progresses. However, the probabilistic classification task (PCT) allows one to distinguish between learning from reward or punishment, whereas in the IGT, the participant must weigh both elements in each choice. Therefore, the PCT was assessed in the present study. We assessed the response to subjectively unfair offers using the Ultimatum Game (UG) as described in Koenigs and Tranel (2007). The UG was chosen in order to assess euthymic BP patient's responses to subjectively unfair offers (i.e., less than 30%), as presented in previous studies (Pillutla and Murnighan, 1996; Koenigs and Tranel, 2007; Crockett et al., 2008). Responses to these offers were associated with anger, aggressive behavior and low serotonin levels (Pillutla and Murnighan, 1996; Sanfey et al., 2003; Crockett et al., 2008; Mehta and Beer, 2010). Impulsivity was assessed using the single key impulsiveness paradigm (SKIP) (Dougherty et al., 2003). BP patients were shown to be more impulsive in this task (Swann et al., 2009a). We hypothesized that euthymic BP patients would be more sensitive to reward, and hence, would show a steeper learning curve than healthy controls in the rewarded - but not the punished PCT. We hypothesized that BP patients will reject more ‘unfair’ offers than healthy controls. Lastly, BP patients were expected to

Table 1 Demographic data for bipolar and control participants. Group

Gender

N

Age

BP BP HC HC

Female Male Female Male

18 22 18 23

40.56 43.45 37.11 40.30

Education ( 7 10.38) ( 7 13.07) ( 7 11.41) ( 7 11.02)

13.22 13.73 13.44 13.57

( 7 2.24) ( 7 2.21) ( 7 1.98) ( 7 2.15)

Raven 40.39 43.82 45.50 43.30

( 7 12.48) ( 7 6.59) ( 7 9.41) ( 7 10.21)

be more impulsive, resulting in a higher rate of response in the SKIP, despite the loss of points which this entails. 2. Methods 2.1. Participants Forty-seven patients, ranging in age from 18 to 65, were recruited from the ambulatory out-patient Mood Disorder Clinic at the Beer-Sheva Mental Health Center (Osher et al., 2010). All were known to have Bipolar I disorder as diagnosed by DSM-IV criteria based on the chart review and clinical interview, and had been fully euthymic for at least 1 month before inclusion. The patient group was carefully chosen by both a psychiatrist and a psychologist with a comprehensive knowledge of patient history. Axis II diagnosed patients were also excluded from this study. The control group consisted of 42 age and education ( 7 3 years) matched healthy controls recruited from the community by local advertisement. Exclusion criteria for both groups included a known Axis I diagnosis (except bipolar disorder for the patients group), current substance use disorder, known history of brain injury, or serious medical condition. Patients were also excluded if they had received electroconvulsive therapy (ECT) in the past year. Healthy controls were excluded for family history of bipolar disorder, diagnosis of any major mental illness or if taking psychotropic medications. Table 1 presents mean age, education and Raven Progressive Matrices scores of participants. 2.2. Instruments 2.2.1. Probabilistic classification task (PCT) This was a computerized decision-making task, which tests the ability to implicitly learn a categorization rule based on either reward or on punishment. The participant does not know in advance which stimuli are associated with reward or punishment. In this task, the participant is asked to classify four unfamiliar stimuli to either category A or B; two stimuli are correlated to category A 80% of the time and two are correlated to category B 80% of the time. Two stimuli are associated with the punishment task (i.e., the participant loses points when choosing incorrectly and loses nothing if he chooses correctly) and the other two are associated with the reward task (i.e., the participant gains points when choosing correctly and gains nothing if he chooses incorrectly). The task has four blocks. In every block, each stimulus is presented 10 times in random order. Thus, each block consists of 20 reward trials and 20 punishment trials in a mixed order. Because the order is mixed, in the initial trials receiving feedback of 0 points is ambiguous as it can indicate a wrong response in the reward task or a correct response in the punishment task. The optimal answer, defined as the answer that fits the 80% probability was recorded. Thus the participant may learn from both reward (by gaining points) and punishment conditions (by losing points). To increase motivation, participants were promised a small monetary reward for achieving a high score (10 NIS, approximately $2.50). 2.2.2. Ultimatum game (UG) This is a social decision making task that has been used in various formats to assess inter-personal interactions in negotiation-like settings. The single offer version of the task used in the present study was intentionally designed to compare the participants' responses to unfair offers in order to provoke angry (negative approach) emotions. In this task the participant decides whether to accept or reject an offer of a small amount of cash (10 NIS, approximately $2.50) offered by a fictitious partner whose face and name are presented to the participant. In fact, the offers were programmed by the computer. If the participant accepts the offer, each player receives the amount specified. If the participant declines the offer, neither player receives anything. Some of the offers were fair (4 or 5 NIS to the participant, leaving 6 or 5 NIS to the partner), some were biased in favor of the participant (8 NIS), and most were biased in the favor of the fictitious partner, in varying degrees of unfairness (leaving only 1, 2 or 3 NIS to the participant; (Crockett et al., 2008)). Participants were told in advance that they will receive actual cash at the end of the task, in proportion to the amount accumulated by offers accepted. This is a slight variation of the Koeings et al. procedure (Koenigs and Tranel, 2007).

O. Duek et al. / Psychiatry Research 215 (2014) 95–100

2.2.3. SKIP The single key impulsivity paradigm (Dougherty et al., 2003) was designed to assess impulsive behavior and the ability to inhibit a habitual response in order to profit. It is a 20 min task in which the participant is instructed to click the mouse button freely any time. The participant is told that the amount of money earned by the presses will appear on-screen. In fact, points are added as a function of the length of the interval between presses, so that, unbeknownst to the participant, size of reward is negatively related to response rate. Raven standard progressive matrices A–E (Raven, 1960) were administered to assess intelligence. 2.2.4. Current mood state The Hamilton Rating Scale for Depression (HAM-D) (Hamilton, 1980), and the Young Mania Rating Scale (YMRS) (Young et al., 1978) were completed for each patient by the examining clinician to confirm the patient's euthymic status. 2.3. Procedure 2.3.1. Patient group Following evaluation during a regular follow-up appointment in the Mood Disorders Clinic, and after signing an informed consent form, participants were escorted to the on-site testing room where they were presented with the three computerized tasks in the order listed above, followed by the Raven Standard Progressive Matrices. Each participant was given the option to be tested in Hebrew or Russian. In fact, only one of the BP participants who completed the testing was tested in Russian. Healthy Controls group: HC participants were recruited from the community by local advertising via fliers, wall posters, and Internet announcements. Control participants were examined either on the Beer Sheva campus of the Ben-Gurion University of the Negev (N ¼43) or in their homes (N ¼ 5). The procedure for the controls was otherwise identical to the patient group procedure, with the exclusion of the clinical rating scales. Data collection continued for approximately 1 year (2011–2012). This study was approved by the Ben-Gurion University Ethical Committee on Human Experimentation, in accordance with the Declaration of Helsinki. 2.4. Statistical analyses 2.4.1. Learning from reward and punishment Three way analysis of variance (ANOVA) within-subject design was performed using the nlme package in Pinheiro and Bates (2000), Team (2008), with optimal response scores as the dependent variable, and learning condition (reward, punishment), group (bipolar, healthy controls) and block (1–4) as independent variables. In order to examine individual differences in the relationship between reward and punishment learning, a linear regression was performed, with total score from reward learning as the dependent variable, while group and total punishment scores were used as the predictor variable. 2.4.2. Unfairness First, we analyzed all data in order to test the manipulation (i.e to see that fair offers were accepted in most cases). Second, we analyzed group differences in acceptance of unfair offers (i.e. the participant is offered 30% or less of the total). Analysis of variance (ANOVA) was used for both analyses. 2.4.3. Impulsivity One way ANOVA was performed, with number of mouse clicks as the dependent variable and diagnostic group as the independent variable.

3. Results 3.1. Demographic data Eighty nine participants were recruited to this study. Five patients and one control subject were excluded from analyses because of failure to complete the entire experiment. Two patients were excluded from analyses because within 1 week following participation they experienced an acute affective episode. Thus, a total of 81 participants were included in data analyses (40 bipolar patients and 41 healthy controls). BP and HC groups, stratified by gender, did not differ significantly in age (female—[F(1,34)¼0.8, n.s], male—[F(1,43)¼ 0.766, n.s]) levels of education (female—[F(1,34)¼0.1, n.s], male— [F(1,43)¼0.062, n.s]) or intelligence (female—[F(1,34)¼1.9, n.s], male —[F(1,43)¼0.04, n.s]). Data are presented in Table 1. There was no significant difference between groups in either age [F(1,77)¼1.6, n.s.],

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level of education [F(1,77)¼0, n.s] or intelligence. [F(1,77)¼0.84, n.s]. Fifteen patients received monotherapy, 20 received two psychiatric medications, and 5 patients received three medications. Twenty three patients received lithium, 14 received an anti-convulsant, 24 received a dopamine blocker (first or second generation), 4 received an anti-depressant (SSRI or other). 3.2. Reward and punishment learning A main effect for block was found [F(3,553) ¼3.98, p o0.01] indicating that participants in both groups learned from reward [F(3,231)¼6.32, p¼0.0004] as well as from punishment [F(3,231)¼ 3.34, po0.05]. A main effect was also found for condition [F(1,316)¼ 7.8, po0.01], indicating that overall learning from punishment was superior to learning from reward. Regression analysis revealed a significant negative correlation between reward and punishment scores specifically in the bipolar group (β ¼ 0.62), and no correlation in the control group (β ¼0.03), see Fig. 1. It is possible that the adherence of euthymic BP patients to either reward or punishment is based on their first experience with the task. Thus, we analyzed the data after dividing the participants into two groups based on whether they were exposed to reward or punishment on the first trial. As stated above, a score of zero is ambiguous on the first trial as it can mean either no reward or absence of punishment. Nineteen BP and 22 HC received punishment on the first trial the and remainder received reward. Mean7 SEM of optimal answers of BP who received punishment as first stimulus was 10.9 70.35, BP who received reward as first stimulus had mean of 11.670.38. HC who received punishment as first stimulus had 12.27 70.31 and HC who received reward as first stimulus gained 11.8 70.33. There was no main effect of first stimulus on learning [F( 1,77)¼0.02, n.s,]. In order to test whether medication with anti-psychotic drugs would affect the pattern of probabilistic learning, a three way ANOVA was performed with group (HC, BP with anti-psychotics, BP without antipsychotic), condition (reward and punishment) and block, with participant's optimal answers as the dependent variable. Performance of patients on anti-psychotic medication did not differ from that of patients on only mood stabilizer medication [F(2,78) ¼1.9, n.s]. Mean optimal answer7SEM of the BP group with anti-psychotic was 10.847 0.32, BP without anti-psychotic was 11.79 70.4 and HC mean optimal answers was 12.06 70.23. 3.3. Unfairness While the groups did not differ in their tendencies to accept fair or reject overtly unfair offers [F(1,79)¼0.1, n.s], the BP patients were significantly more likely to reject moderately unfair offers (i.e. 30%) [F(1,159) ¼ 5.63, p o0.05]. Results are presented in Fig. 2. As in learning task, no effect of drugs was found [F(2,78) ¼0.121, n. s]. The acceptance rate for the 30% offer was as follows: 0.76 70.05 HC, 0.66 70.09 BP with anti-psychotics, 0.617 0.01, BP without anti-psychotics. 3.4. Impulsive Behavior There was no difference in the number of presses between BP patients and HC participants (Mean þSEM)¼785 7220 (BP) vs. 671 7178 (HC), F(1,78) ¼0.16, n.s. 4. Discussion We found that euthymic BP participants differed from HC in two aspects of reward/punishment learning. Euthymic BP patients showed a strong negative correlation between learning conditions

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100

% of Reward Optimal Responses

75

Group BP

50

HC

25

0 40

60

80

100

% of Punishment Optimal Responses Fig. 1. Probabilistic Classification Task—Correlation between reward and punishment learning scores. BP subjects show a significant negative correlation between reward and punishment learning. Healthy controls show no such correlation.

(i.e. reward/punishment) while HCs showed no such association, suggesting that euthymic BP patients were able to learn either from reward or punishment but were unable to alternate between the two tasks. We also found that BP patients rejected more moderately unfair offers in the UG, even at a cost to themselves. Lastly we did not find any group differences in impulsiveness using SKIP. Our findings suggest that whereas HC are able to switch between different task requirements (i.e. reward and punishment), in euthymic BP patients there is a strong tendency towards dominance of one system over the other at any given point in time. This may relate to certain clinical phenomena common in bipolar disorder—the reckless pursuit of pleasurable activities heedless of negative consequences, found in mania, as well as the lack of response to normally rewarding activities which characterizes depression. Those clinical actions are addressed in the BAS dysregulation model (Depue and Iacono, 1989) which suggests that the behavioral approach system (BAS) of BP patients is hypersensitive and will respond positively to reward and negatively to the lack of reward. This finding is also apparent in several studies of cognitive flexibility in BP patients. In those studies BP patients show less flexibility compared to HCs, as manifested by an impairment in working memory, verbal fluency and executive control (Arts et al., 2008). The intra-group variance of BP patients in the learning task might also explain the lack of consistent behavioral findings in comparison to HC. Although, according to fMRI studies and self-report questionnaires, BP patients show more sensitivity to reward stimuli, they do not succeed in reward based learning tasks (Edge et al., 2012; Linke, 2012). Our findings suggest that while some BP patients succeed, others are more responsive to learning from punishment. In the

present study, all participants were tested only once, limiting our ability to conclude whether the tendency to learn from either reward or punishment represents an individual trait of BP patients or whether this tendency changes during the course of the illness. Although we found that the random presentation of reward or punishment on the first trial had no consequence on the rate of learning, one cannot infer that each patient has an inherent tendency to react more to either reward or punishment. Future studies should address this issue, perhaps by using of a mood induction or reward/punishment manipulation prior the beginning of the task, in order to see if the individual's tendency can be altered. Overall, this finding should be addressed in future studies, in order to better understand this intra-group variance. Individual differences in BP patients can affect their clinical course of illness and responsiveness to treatment. A possible explanation for BAS hypersensitivity could lie in the hemispheric connectivity of BP patients. Leow et al. found that euthymic BP patients shows impaired hemispheric connectivity compared to healthy controls (Leow et al., 2013). It was shown that BP patients and their mono-zygotic twins showed a larger left caudate, compared to BP patients and their dizygotic twins and healthy controls (Noga et al., 2001). Activity of the left hemisphere was correlated to higher reward sensitivity (Pizzagalli et al., 2005) in healthy participants. This suggests that imaging studies could reveal hyper or hypo activation of the left hemisphere of the BP patients during performance of learning tasks. In our study, BP patients showed heightened sensitivity to unfair offers compared to healthy controls. In the UG they rejected more moderately unfair offers (30%), as described in Crockett et al. (2008). Harmon-Jones and colleagues consider anger to be part of

O. Duek et al. / Psychiatry Research 215 (2014) 95–100

99

% of offers accepted

90

Group BP

70

HC

50

1

2

3

4

5

8

Number of NIS (out of 10 total) offered to the participant Fig. 2. Ultimatum Game—Percentage of offers accepted by BP vs. healthy controls. Trials which offer the participant 1 or 2 out of 10 NIS are considered very unfair (n¼12). Trials offering 3 out of 10 NIS are considered moderately unfair (n ¼6). No trials offered more than 8 NIS. *p o 0.05.

the approach system (Carver and Harmon-Jones, 2009). Their studies also correlate left hemisphere activation with anger and mania- related symptoms in BP patients (Harmon-Jones and Allen, 1998; Harmon-Jones, 2003; Harmon-Jones et al., 2008). Rejection of unfair offers was associated with anger, aggressive behavior and serotonin depletion (Pillutla and Murnighan, 1996; Koenigs and Tranel, 2007; Crockett et al., 2008; Mehta and Beer, 2010). However, an alternative interpretation is that unfair offers represent aversive stimuli, resulting in activation of the BIS. This interpretation is supported by the finding that BP patients have higher BIS scores, (Meyer et al., 2001; Yechiam et al., 2008), and that the regions showing increased brain activity during rejection of unfair offers, such as the insula, VLPFC, and ACC (Sanfey et al., 2003), are known to be involved in conflict resolution. Thus, it is possible that rejecting more offers derives from inhibitory behavior and not anger. In order to better understand this behavior, future studies should use a task that may address anger, aggression in a more direct way, i.e. actively “hurting” the other. One possible task is the Dictator Game, which is similar to the UG but here the participant is the one that decides how to divide the money. Although the quantitative data from the UG do not definitively favor the BIS or BAS hypothesis, analysis of statements made during the testing and debriefing support our hypothesis that the increased rejections for the moderately unfair offers were related to anger, in both groups. For example, BP patients stated: “I refused only those who looked like jerks”, “I'm not willing to give in”, “I don't want anyone to earn more than I do” and HC said, “I don't want to be a 'sucker'”. In addition, some of the participants expressed regret at having rejected offers, suggesting that they realized that they acted impulsively, leading to a loss of profit.

Regarding impulsivity, the task we chose (SKIP) involves at least two aspects of this trait, reward directed impulsivity and disinhibition of motor reactions (Dougherty et al., 2003). It may be useful for future studies to utilize tasks which distinguish between these aspects. The BAS hypersensitivity model would predict that reward-directed impulsivity would be most affected in patients with BP disorder. Our results contrast with those of Swann et al. (2009b) who did find higher responses and shorter delays in the SKIP in BP patients. In order to better understand the results, it is important to use other tasks and variations. If BP patients are “stuck” on one modality (i.e. reward/punishment) is it possible to manipulate this modality or to predict in which modality the BP patient will be? One option may be to try to enhance a rewarding state or punishing state before the beginning of the probabilistic learning task by altering reward and punishment contingencies. Another option is to use more explicit reward-directed task, such as the Balloon Analogue Risk Task (Lejuez et al., 2002). This study has some limitations. The patients were not diagnosed using a standardized method (such as the structural clinical interview for DSM-IV, i.e. SCID). Moreover, patients were not assessed with personality questionnaires, such that there may be patients with personality traits which are relevant but did not meet criteria for axis II disorders in DSM-IV. It should be pointed out that the staff of the Mood Disorder Clinic (two psychiatrists and a psychologist) have known most of the patients for at least several years (many have been known for over 20 years). We believe that this supports the accuracy of the diagnoses and the decisions regarding Axis II disorders. In summary, these findings suggest that euthymic bipolar patients may show altered responses in both positive (reward) and negative

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(anger) approach behavior. We propose that, taken together, these findings support the proposition that it is explicitly the BAS which appears to be dysregulated in bipolar patients. We would suggest that additional research employing different paradigms of behavioral testing, as discussed above, could contribute to a more complete understanding of the possible relevance of a hypersensitive bas to the diathesis of bipolar disorder. Swerdlow (2012) recently exhorted therapists to develop therapies based on enhancing spared neural functions, rather than on focusing on pathologies. Given the extensive neuropharmacological research on the neural substrates of reward and punishment (Cools et al., 2007; Cools, 2008), further research into characterizing individual differences in BP's may enable therapists to tailor patient management to the individual patient's specific strengths. Acknowledgment The contribution of Ms. Ma'ayan Abargil and Ms. Ella Paltiel are gratefully acknowledged. References Adida, M., Jollant, F., Clark, L., Besnier, N., Guillaume, S., Kaladjian, A., MazzolaPomietto, P., Jeanningros, R., Goodwin, G.M., Azorin, J.M., 2011. Trait-related decision-making impairment in the three phases of bipolar disorder. Biological Psychiatry 70, 357–365. Aggleton, J.P., 1993. The contribution of the amygdala to normal and abnormal emotional states. Trends in Neuroscience 16, 328–333. Alloy, L., Abramson, L., Walshaw, P., Cogswell, A., Smith, J., Neeren, A., Hughes, M., Iacoviello, B., Gerstein, R., Keyser, J., Urosevic, S., Nusslock, R., 2006. Behavioral Approach System (BAS) sensitivity and bipolar spectrum disorders: a retrospective and concurrent behavioral high-risk design. Motivation and Emotion 30, 143–155. Alloy, L.B., Abramson, L.Y., Walshaw, P.D., Cogswell, A., Grandin, L.D., Hughes, M.E., Iacoviello, B.M., Whitehouse, W.G., Urosevic, S., Nusslock, R., Hogan, M.E., 2008. Behavioral approach system and behavioral inhibition system sensitivities and bipolar spectrum disorders: prospective prediction of bipolar mood episodes. Bipolar Disorders 10, 310–322. Almeida, J.R.C., Versace, A., Hassel, S., Kupfer, D.J., Phillips, M.L., 2010. Elevated amygdala activity to sad facial expressions: a state marker of bipolar but not unipolar depression. Biological Psychiatry 67, 414–421. Arts, B., Jabben, N., Krabbendam, L., van Os, J., 2008. Meta-analyses of cognitive functioning in euthymic bipolar patients and their first-degree relatives. Psychological Medicine 38, 771–785. Barrett, P.M., Dadds, M.R., Rapee, R.M., 1996. Family treatment of childhood anxiety: a controlled trial. Journal of Consulting and Clinical Psychology 64, 333–342. Baylis, L.L., Gaffan, D., 1991. Amygdalectomy and ventromedial prefrontal ablation produce similar deficits in food choice and in simple object discrimination learning for an unseen reward. Experimental Brain Research 86, 617–622. Bechara, A., Damasio, A.R., Damasio, H., Anderson, S.W., 1994. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50, 7–15. Berns, G.S., McClure, S.M., Pagnoni, G., Montague, P.R., 2001. Predictability modulates human brain response to reward. Journal of Neuroscience 21, 2793–2798. Bodi, N., Keri, S., Nagy, H., Moustafa, A., Myers, C.E., Daw, N., Dibo, G., Takats, A., Bereczki, D., Gluck, M.A., 2009. Reward-learning and the novelty-seeking personality: a between- and within-subjects study of the effects of dopamine agonists on young Parkinson's patients. Brain 132, 2385–2395. Carver, C.S., Harmon-Jones, E., 2009. Anger is an approach-related affect: evidence and implications. Psychological Bulletin 135, 183. Cools, R., 2008. Role of dopamine in the motivational and cognitive control of behavior. Neuroscientist 14, 381–395. Cools, R., Robinson, O.J., Sahakian, B., 2007. Acute tryptophan depletion in healthy volunteers enhances punishment prediction but does not affect reward prediction. Neuropsychopharmacology 33, 2291–2299. Crockett, M.J., Clark, L., Tabibnia, G., Lieberman, M.D., Robbins, T.W., 2008. Serotonin modulates behavioral reactions to unfairness. Science 320, 1739. Depue, R.A., Collins, P.F., 1999. Neurobiology of the structure of personality: dopamine, facilitation of incentive motivation, and extraversion. The Behavioral and Brain Sciences 22, 491–517. Depue, R.A., Iacono, W.G., 1989. Neurobehavioral aspects of affective disorders. Annual Review of Psychology 40, 457–492. Depue, R.A., Krauss, S., Spoont, M.R., Arbisi, P., 1989. General behavior inventory identification of unipolar and bipolar affective conditions in a nonclinical university population. Journal of Abnormal Psychology 98, 117–126. Dougherty, D.M., Bjork, J.M., Andrew Harper, R., Marsh, D.M., Gerard Moeller, F., Mathias, A.C., Swann, A.C., 2003. Behavioral impulsivity paradigms: a

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