Motivation, reward, and Parkinson’s disease: influence of dopatherapy

Neuropsychologia 40 (2002) 2257–2267

Motivation, reward, and Parkinson’s disease: influence of dopatherapy V. Czernecki a , B. Pillon a,b,∗ , J.L. Houeto b , J.B. Pochon a , R. Levy a,b , B. Dubois a,b b

a INSERM E 007, Hˆ opital de la Salpˆetrière, Paris, France Fédération de Neurologie, Hˆopital de la Salpˆetrière, 47 Blvd de l’Hˆopital, 75651 Paris cedex 13, France

Received 11 January 2002; received in revised form 28 June 2002; accepted 9 July 2002

Abstract “Orbitofrontal” and “cingulate” striatofrontal loops and the mesolimbic dopaminergic system that modulates their function have been implicated in motivation and sensitivity to reinforcement in animals. Parkinson’s disease (PD) provides a model to assess their implications in humans. The aims of the study were to investigate motivation and sensitivity to reinforcement in non-demented and -depressed PD patients and to evaluate the influence of dopaminergic therapy by comparing patients in “on” (with l-Dopa) and “off” (without l-Dopa) states. Twenty-three PD patients were compared, in both the “on” and “off” states, to 28 controls, using: (1) an Apathy Scale; (2) Stimulus–Reward Learning, Reversal, and Extinction tasks; and (3) a Gambling task. PD patients were found: (1) mildly apathetic; (2) impaired on Stimulus–Reward Learning and Reversal, but not on Extinction; and (3) able to progress in the Gambling task during the first, but not the second assessment. There was no significant correlation between these various deficits. l-Dopa treatment clearly improved motivation, but had more limited and contrasting effects on other variables, decreasing the number of omission errors in Reversal, but increasing the number of perseveration errors in Extinction. These results suggest: (1) an implication of striatofrontal loops in human motivation and explicit and implicit sensitivity to reinforcement; (2) a positive influence of l-Dopa treatment on the subjective evaluation of motivation, but contrasting effects on reward sensitivity. © 2002 Elsevier Science Ltd. All rights reserved. Keywords: Sensitivity to reinforcement; Mesocorticolimbic dopaminergic system; Striatofrontal loops

1. Introduction Motivation is a conscious or unconscious internal state, which incites the subject to act [28]. It influences all stages of behavioural planning: determination of aim, selection and elaboration of responses, and evaluation of consequences of action. Conversely, motivation and planning are affected by the ability to identify the behavioural relevance and the reinforcing value of environmental stimuli and to take into account the difference between the anticipated and the obtained reward. Motivation and sensitivity to reinforcement are therefore central processes for adaptive orientation of behaviour. According to Rolls [40], “computing the reward and punishment value of sensory stimuli, and then using selection between different rewards and avoidance of punishments in a common reward-based currency appears to be the fundamental solution that the brain uses in order to produce appropriate behaviour”. ∗ Corresponding author. Present address: Centre de Neuropsychologi´ e, F´ed´eration de Neurologie, Hˆopital de la Salpˆetri`ere, 47 Blvd de l’Hˆopital, 75651 Paris cedex 13, France. Tel.: +33-1-42-16-17-77; fax: +33-1-42-16-27-39. E-mail address: [email protected] (B. Pillon).

This computation may be explicit when the rule is clear and the same reward is regularly associated to the same stimulus, as in Stimulus–Reward Learning. When subjects have explicitly learned the stimulus–reward association, the reward contingencies may be unexpectedly reversed (Reversal), or extinguished (Extinction) [41]. The ability to reverse the stimulus–reward–response association suggests a form of “sensitivity to reward” flexibility [11], whereas the ability to withhold a response is related to control of impulsiveness [41]. In real life, however, outcomes in terms of reward or punishment are more uncertain. Bechara et al. [3,4] designed a task, so called the Gambling task, which resembles the decisions made in real life. The task includes four decks of cards, two of them being disadvantageous (high gains and unpredictable higher penalties), whereas the other two are advantageous (small immediate gains and lower penalties). Normal subjects progressively learn to choose the advantageous decks. This behaviour is largely implicit, since bias toward the selection of advantageous choices occurs before the subject becomes aware of the goodness or badness of his or her choice, and a great proportion of normal controls do not reach awareness [6].

0028-3932/02/$ – see front matter © 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 0 2 8 - 3 9 3 2 ( 0 2 ) 0 0 1 0 8 - 2

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Animal studies implicate limbic structures (amygdala and orbitofrontal cortex) in motivation, reinforcement associated learning, “sensitivity to reward” flexibility, and control of impulsiveness [40,48]. The ventral striatum, which connects the limbic and frontal executive systems via the “orbitofrontal” and “cingulate” loops, [2] is also involved. In addition, the mesolimbic and the nigrostriatal dopaminergic systems, which modulate the activity of these loops, intervene in signalling changes or errors in the prediction of rewarding events [43]. In humans, reinforcement associated learning, “sensitivity to reward” flexibility, and control of impulsiveness have been shown to be impaired by orbitofrontal lesions [3,41], whereas apathy or loss of motivation, in the absence of depression, has been observed in cases of lesions of basal ganglia [16,24,26]. Is apathy related to decreased sensitivity to reinforcement? Are the striatofrontal loops involved in reinforcement associated learning in humans? Does dopamine intervene in “sensitivity to reward” flexibility? Parkinson’s disease (PD), which alters the mesocorticolimbic dopaminergic system [21,33] and consequently impairs the function of “orbitofrontal” and “cingulate” loops [1,10], may help to answer these questions. Indeed, apathy has been observed in PD and might worsen the cognitive and behavioural difficulties of these patients [25,45]. The aims of the study were to investigate motivation and sensitivity to reinforcement in non-demented and -depressed PD patients and to evaluate the influence of dopaminergic therapy comparing patients in “on” (with l-Dopa) and “off” (without l-Dopa) states. 2. Methods 2.1. Subjects Thirty patients hospitalised in the Neurology Department of the Salpetriere Hospital for therapeutic equilibration or for candidature for subthalamic nucleus deep brain stimulation were recruited for the study. Inclusion criteria were idiopathic PD [20], persistence of a good reactivity to l-Dopa, lack of dementia (score >130 on the Mattis Dementia Rating Scale) [29] or depression (score <20 on the Montgomery and Asberg Depression Rating Scale (MADRS)) [30], ability

Table 2 Characteristics of parkinsonian patients and control subjects Patients N Age (years) Education (years) Gender (M/F) Mattis DRS MADRS

23 57.6 ± 11.5 ± 9/14 139.1 ± 8.3 ±

Controls 2.1 0.6 0.8 1.4

28 58.1 ± 12.7 ± 18/10 141.1 ± 6.2 ±

P – 0.68 0.01 0.21 0.0004 0.06

1.7 0.5 0.3 0.8

Values expressed as mean±S.E.M.; Dementia Rating Scale (DRS); Montgomery and Asberg Depression Rating Scale (MADRS).

to be tested not only in the “on” state (maximum therapeutic effect of dopaminergic treatment), but also in the “off” state (after about 12 h of therapeutic withdrawal). From the 30 preincluded subjects, 7 had a motor syndrome that was too severe and could not be assessed in the “off” state. Twenty-three patients were therefore included and were randomly divided into 2 subgroups: the “On-first” subgroup with 10 patients examined first in the “on” state and a day after in the “off” state; and the “Off-first” subgroup with 13 patients examined first in the “off” state and a day after in the “on” state. There was no significant difference between the two subgroups in terms of either the principal characteristics of the disease: age at onset, duration of evolution, Hoehn and Yahr stage in the “on” or “off” states [17], Unified Parkinson’s Disease Rating Scale (UPDRS) motor score in the “on” or “off” states [13], and dose of l-Dopa; or the neuropsychological data: frontal score [38], Modified Wisconsin Card Sorting Test variables [31], category and phonemic fluencies (animal names and words beginning by M in 60 s) [7], and verbal learning [15]. Therefore, these data are presented for the overall group of patients (Table 1). They indicate a good sensitivity to l-Dopa, as shown by the comparison of the Hoehn and Yahr and UPDRS motor scores in the “off” and “on” states. They also show a mild cognitive impairment compared to controls [37]. Twenty-eight control subjects without neurologic or psychiatric disorders, matched to the patients for age and sex, were recruited (Table 2). Their level of education was higher than that of the patients, but was not significantly correlated to the experimental variables in controls and did not influence the differences between patients and controls on the experimental variables (as shown in Section 3). A comparison

Table 1 Neurologic and neuropsychological characteristics of parkinsonian patients Neurologic characteristics Age at onset (years) Duration of disease (years) Hoehn and Yahr “on” Hoehn and Yahr “off” UPDRS “on” UPDRS “off” Dose of l-Dopa (mg per day) Values expressed as mean ± S.E.M.

Neuropsychological data 42.6 14.9 2.2 3.8 12.4 38.7 1115.3

± ± ± ± ± ± ±

2.2 1.2 0.1 0.1 2.0 2.8 67.4

Frontal score (out of 60) Wisconsin criteria (out of 6) Wisconsin perseverations Wisconsin abandons Category fluency (60 s) Phonemic fluency (60 s) Grober free recall (out of 48)

55.6 5.6 1.8 1.3 21.3 12.5 24.8

± ± ± ± ± ± ±

0.9 0.1 0.4 0.3 1.0 0.3 1.5

V. Czernecki et al. / Neuropsychologia 40 (2002) 2257–2267

of the two groups confirmed the existence of a mild dysexecutive syndrome on the Mattis Dementia Rating Scale and a trend for more dysthymic disorders on the MADRS in patients. The Ethical Committee of the Salpetriere Hospital approved the study and all subjects gave informed written consent. 2.2. Neuropsychological assessment For patients and controls, there were two assessments that were separated by a period of 24 h. The duration of each assessment was short (about 40 min), allowing the patients to stay as much as possible in a stable state throughout the experiment. In controls, the second assessment enabled us to evaluate test–retest effects. For each assessment, the tests were presented in the same order: Apathy Scale, Stimulus–Reward Learning (hereafter referred to as Stimulus–Reward Learning 1) and Reversal, Gambling task, new Stimulus–Reward Learning (hereafter referred to as Stimulus–Reward Learning 2) and Extinction. The Apathy Scale included 14 questions (for instance: “Do you have plans and goals for the future?”) read by the examiner. For each question, the subject was provided with four possible answers: “not at all”, “slightly”, “some”, or “a lot”. Scores ranged from 0 to 42, higher scores indicating more apathy, and a score of 14 as the pathological cut-off score. Subjects were asked to answer in function of what they really felt at the moment of the examination. This scale has been shown reliable to evaluate apathy in PD [45]. Stimulus–Reward Learning, Reversal, and Extinction were adapted from Rolls et al. [41]. Deficits in Reversal have been shown to be related to dysfunction of the orbitofrontal cortex, but not of the dorsolateral prefrontal cortex, in focal lesions both in animals and in humans [11,40,41]. In Stimulus–Reward Learning 1, the subject first learned to touch one of two highly discriminable coloured fractal images that appeared one at a time on a video monitor equipped with a touch screen. Different patterns were used for the first and second assessments. The subject gained one point for touching the correct pattern or not touching the incorrect one, and lost one point for not touching the correct pattern or touching the incorrect one. If the pattern was touched, it was immediately replaced by a message telling the subject whether a point had been gained or lost. If the pattern was not touched, it disappeared after 7 s and was replaced by a message telling the subject whether a point had been gained or lost. Correct responses were also signalled by a pleasant rising tone, whereas incorrect responses were signalled by a short unpleasant tone. A running total of points obtained was displayed on the screen. The subject was asked to try to gain as many points as possible. He/she advanced each new trial at his/her own pace, by pressing the space bar on a keyboard, until a criterion of 9 correct responses out of the preceding 10 trials had been reached. The score consisted of the number of trials needed to attain the criterion.

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Once the Stimulus–Reward Learning criterion had been reached, the Reversal task automatically occurred without warning, the relationship between the patterns and the rewarding or punishing consequences being reversed. Testing continued for 30 trials and further reversals occurred whenever the criterion of 9 successive correct responses was reached again. The scores consisted of the number of reversals in 30 trials, the number of trials and the number of errors for the first reversal, the last error trial for the first reversal, and the total number of commission errors (previously correct stimuli touched) and omission errors (previously incorrect stimuli not touched). The Stimulus–Reward Learning 2, before Extinction, consisted of the same procedure than before Reversal, but with different patterns. The score was again the number of trials necessary to attain the criterion of 9 correct responses out of the 10 preceding trials. After the Stimulus–Reward Learning 2 criterion had been reached, the Extinction task automatically took place. Points could only be won by refraining from touching both of the patterns, and were lost by touching either of them. The scores were the number of trials needed for extinction, the last error trial, the total number of perseveration errors (previously correct stimuli touched), and attribution errors (previously incorrect stimuli touched). Bechara et al. [3] provided the computerised version of the Gambling task. Deficits on this task have been shown to be related to lesions or dysfunction of the orbitofrontal cortex and to be independent of working memory deficits, which are related to lesions of the prefrontal dorsolateral cortex [5]. The subject sees on the screen 4 decks of cards labelled A–D, each of them being programmed to have 60 cards. Using a mouse, he/she can click on a card from any of the four decks. Every time the subject picks a card, a message is displayed on the screen indicating the amount of money he/she has won or lost. A green bar on the top of the screen also changes according to the amount of money won or lost. The subject is asked to win as much money as possible, and, if he/she cannot, to avoid losing money as much as possible. The experiment shuts off automatically when 100 cards have been selected. The subject must progressively discover that decks A and B are disadvantageous (big gains but bigger losses), while decks C and D are advantageous (small gains but even smaller losses). The scores consisted of the numbers of advantageous choices (C + D) minus disadvantageous choices (A + B) for each of the 5 blocks of 20 cards and for the total of the 100 cards. 2.3. Analysis of data The same analyses were performed for all variables: (1) analysis of the effects of PD, using Global ANOVA with the three groups as a between factor (control subjects, “On-first” patients and “Off-first” patients) and repetition effect (second assessment versus first assessment) as a within factor, followed by post-hoc analysis of the group factor (Fisher

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Test), the repetition factor (separate ANOVA with repeated measures for each group) and potential interaction between group and repetition; (2) analysis of the effects of l-Dopa therapy, using Patients ANOVA with the two groups of patients as a between factor (“On-first” patients and “Off-first” patients) and treatment effect (“on” l-Dopa state versus “off” l-Dopa state) as a within factor. When an interaction was observed between group and l-Dopa state, analysis of the effects of l-Dopa therapy was completed by comparing, with ANOVA, the three groups of subjects only on the first assessment. Correlations between demographic and clinical variables and experimental variables were searched for with the non-parametric Spearman Rank Correlation Test.

3. Results 3.1. Motivation Global ANOVA showed no repetition effect on the Apathy Scale [F (1, 48) = 0.025; P = 0.88], but did show a group effect [F (2, 48) = 5.65; P = 0.006] and an interaction between group and repetition [F (2, 48) = 8.32; P = 0.0008]. Post-hoc analysis of the group effect showed that “On-first” patients (P = 0.027) and “Off-first” patients (P < 0.0001) differed from controls, but not one from another (P = 0.13). Apathy was therefore similar in both groups of patients and more severe in patients than in controls. Post-hoc analysis of the interaction effect between group and repetition showed no difference between the first and the second assessments in controls [F (1, 27) = 1.20; P = 0.28], but a trend for a better score in the first assessment (on state) for the “On-first” patients [F (1, 9) = 4.29; P = 0.068] and a better score in the second assessment (on state) for the “Off-first” patients [F (1, 12) = 8.72; P = 0.012). Apathy was therefore less severe under l-Dopa treatment, whatever the group of patients and the order of assessment (Table 3). Patients ANOVA confirmed this result, since there was a clear l-Dopa state effect [F (1, 21) = 11.70; P = 0.0026], but no group effect [F (1, 21) = 0.70; P = 0.41] and no interaction between group and treatment [F (1, 21) = 0.25; P = 0.62]. Overall, these results show the existence of apathy in PD, with an improvement under l-Dopa treatment. 3.2. Stimulus–Reward Learning 1 (before reversal) Global ANOVA showed a group effect [F (2, 48) = 6.07; P = 0.0045] and a repetition effect [F (1, 48) = 11.53; P = 0.014] for the number of trials in Stimulus–Reward Learning 1, but failed to show an interaction between group and repetition [F (2, 48) = 1.24; P = 0.30]. Post-hoc analysis of the group effect showed that “On-first” patients (P < 0.008) and “Off-first” patients (P = 0.014) dif-

fered from controls, but not one from another (P = 0.73). Stimulus–Reward Learning was therefore similar in both groups of patients and impaired relative to controls. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in controls [F (1, 27) = 8.06; P = 0.0085] and in “Off-first” patients [F (1, 12) = 6.23; P = 0.029]. The difference between the two assessments was not significant in “On-first” patients [F (1, 9) = 0.79; P = 0.39]. Patients ANOVA showed neither a significant difference between groups [F (1, 21) = 0.27; P = 0.61] nor an effect of treatment [F (1, 21) = 0.39; P = 0.54], but did show an interaction between group and treatment [F (1, 21) = 4.70; P = 0.042]. Given the interaction between l-Dopa state and group in patients, we compared the three groups of subjects only on the first assessment. The group effect just failed significance [F (2, 48) = 3.04; P = 0.057). Post-hoc analysis showed that “Off-first” patients (P = 0.04) and “On-first” patients (P = 0.074) nearly differed from controls, but that the two groups of patients performed similarly (P = 0.90). Overall, these results show the existence of Stimulus– Reward Learning deficits in PD, which are not clearly sensitive to l-Dopa treatment. 3.3. Stimulus–Reward Learning 2 (before extinction) Global ANOVA showed a trend for a group effect [F (2, 48) = 2.57; P = 0.087], a repetition effect [F (1, 48) = 12.10; P = 0.0011], and a trend for an interaction between group and repetition [F (2, 48) = 2.56; P = 0.088] for the number of trials in Stimulus–Reward Learning 2. Post-hoc analysis of the group effect showed that the two groups of patients did not significantly differ (P = 0.41), and that “On-first” patients differed from controls (P < 0.014), but not “Off-first” patients (P = 0.10). Post-hoc analysis of the repetition effect showed no significant improvement in the second assessment in controls [F (1, 27) = 1.77; P = 0.19], “On-first” patients [F (1, 9) = 3.40; P = 0.10] or “Off-first” patients [F (1, 12) = 2.78; P = 0.13]. The lack of difference between the two assessments was due to ceiling effects, since Stimulus–Reward Learning required a minimum of nine trials. Patients ANOVA failed to show either a significant difference between groups [F (1, 21) = 0.61; P = 0.44] or an effect of treatment [F (1, 21) = 0.01; P = 0.92], but did show an interaction between group and treatment [F (1, 21) = 6.02; P = 0.02]. The comparison of the three groups of subjects on the first assessment failed significance [F (2, 48) = 2.62; P = 0.083]. Post-hoc analysis showed that the two groups of patients performed similarly (P = 0.43), and that “On-first” patients differed from controls (P = 0.035), but not “Off-first” patients (P = 0.19). Overall, these results are in agreement with those observed in Stimulus–Reward Learning 1, but are limited by ceiling effects.

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Table 3 Scores of controls and parkinsonian patients on experimental variables Controls

“On-first”

“Off-first”

8.2 ± 0.6 7.6 ± 0.6

9.4 ± 2.0 12.8 ± 2.0

14.8 ± 2.3 12.3 ± 2.1

Stimulus–Reward Learning 1 Before Reversal 1 Before Reversal 2

18.5 ± 2.4 11.2 ± 0.6

33.4 ± 11.3 21.8 ± 5.0

34.6 ± 7.5 13.7 ± 2.6

Stimulus–Reward Learning 2 Before Extinction 1 Before Extinction 2

11.6 ± 0.8 10.4 ± 0.6

22.1 ± 7.4 13.8 ± 3.0

17.6 ± 4.6 9.9 ± 0.2

Motivation Apathy Scale 1 Apathy Scale 2

Reversal Total Reversals 1 Total Reversals 2 Last error in first Reversal 1 Last error in first Reversal 2 Commission errors 1 Commission errors 2 Omission errors 1 Omission errors 2

1.7 2.3 8.4 2.5 7.3 3.6 6.6 3.0

± ± ± ± ± ± ± ±

0.2 0.1 1.9 0.5 1.1 0.3 0.8 0.3

0.8 1.4 14.9 5.7 10.0 9.0 6.4 6.7

± ± ± ± ± ± ± ±

0.3 0.3 2.9 1.6 2.1 2.8 0.6 2.4

1.2 1.7 13.2 9.7 12.3 4.4 10.2 4.2

± ± ± ± ± ± ± ±

0.2 0.2 3.4 2.5 2.2 0.9 1.7 0.9

Extinction Last error 1 Last error 2 Perseveration errors 1 Perseveration errors 2 Attribution errors 1 Attribution errors 2

10.1 7.7 2.7 2.2 1.8 1.7

± ± ± ± ± ±

1.5 1.3 0.4 0.3 0.3 0.4

15.7 9.1 4.8 2.4 3.2 2.1

± ± ± ± ± ±

4.0 2.3 1.0 0.6 1.3 0.5

14.0 13.0 3.3 3.2 2.4 2.2

± ± ± ± ± ±

3.0 3.4 0.6 0.5 0.7 0.7

Gambling Advantageous − disadvantageous 1 Advantageous − disadvantageous 2

7.6 ± 4.2 44.9 ± 7.1

6.8 ± 9.4 13.6 ± 14.1

14.6 ± 4.4 18.5 ± 9.8

Values expressed as mean ± S.E.M. In bold, the values obtained in the on l-Dopa state. “On-first” subgroup: patients with, then without l-Dopa treatment. “Off-first” subgroup: patients without, then with l-Dopa treatment.

3.4. Number of reversals Global ANOVA showed a group effect [F (2, 48) = 6.64; P = 0.0029] and a repetition effect [F (1, 48) = 25.24; P < 0.0001] for the number of reversals, but did not show an interaction between group and repetition [F (2, 48) = 0.01; P = 0.99]. Post-hoc analysis of the group effect showed that the two groups of patients did not significantly differ (P = 0.25), but that “On-first” patients (P < 0.0001) and “Off-first” patients (P = 0.004) differed from controls. The number of reversals was therefore similar in both groups of patients and was impaired relative to controls. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in controls [F (1, 27) = 16.61; P = 0.0004], in “On-first” patients [F (1, 9) = 13.5; P = 0.005] and in “Off-first” patients [F (1, 12) = 5.04; P = 0.046]. These results indicate that, although impaired in PD, Reversal may improve with learning. Patients ANOVA showed neither a significant difference between groups [F (1, 21) = 1.26; P = 0.27] nor an effect of treatment [F (1, 21) = 0.01; P = 0.96], but showed an interaction between group and treatment [F (1, 21) = 13.50; P = 0.0015]. The comparison of the three groups of subjects

on the first assessment showed a group effect [F (2, 48) = 4.46; P = 0.017]. Post-hoc analysis showed that “On-first” patients (P = 0.007) and “Off-first” patients (P = 0.08) nearly differed from controls, but that the two groups of patients performed similarly (P = 0.34). Overall, these results show the existence of Reversal deficits in PD, which are not clearly sensitive to l-Dopa treatment. 3.5. Last error in Reversal Global ANOVA showed a group effect [F (2, 48) = 4.62; P = 0.015] and a repetition effect [F (1, 48) = 14.06; P < 0.0005] for the last error in Reversal, but did not show an interaction between group and repetition [F (2, 48) = 0.76; P = 0.47]. Post-hoc analysis of the group effect showed that the two groups of patients did not significantly differ (P = 0.96), but that “On-first” patients (P = 0.005) and “Off-first” patients (P = 0.002) differed from controls. The last error in Reversal was therefore similar in both groups of patients and impaired relative to controls. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in controls [F (1, 27) = 13.76;

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P = 0.001] and in “On-first” patients [F (1, 9) = 24.95; P = 0.0016], but not in “Off-first” patients [F (1, 12) = 0.67; P = 0.43). Patients ANOVA showed neither a significant difference between groups [F (1, 21) = 0.13; P = 0.72] nor an effect of treatment [F (1, 21) = 1.05; P = 0.32], but did show an interaction between group and treatment [F (1, 21) = .5.30; P = 0.0334]. The comparison of the three groups of subjects on the first assessment was not significant [F (2, 48) = 1.78; P = 0.18]. Overall, these results confirm the existence of Reversal deficits in PD, which are not clearly sensitive to l-Dopa treatment. 3.6. Commission errors in Reversal Some values were missing for technical reasons. Global ANOVA showed a group effect [F (2, 39) = 4.04; P = 0.0253], a repetition effect [F (1, 39) = 16.51; P = 0.0002], and a trend for interaction between group and repetition [F (2, 39) = 3.06; P = 0.0582] for commission errors in Reversal. Post-hoc analysis of the group effect showed that the two groups of patients did not significantly differ (P = 0.87), but that “On-first” patients (P = 0.0329) and “Off-first” patients (P = 0.0119) differed from controls. The number of commission errors in Reversal was therefore similar in both groups of patients and impaired relative to controls. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in controls [F (1, 25) = 15.40; P = 0.0006] and in “Off-first” patients [F (1, 8) = 15.04; P = 0.0044], but not in “On-first” patients [F (1, 6) = 0.10; P = 0.76]. This lack of repetition effect in “On-first” patients explains the interaction between group and repetition. Patients ANOVA showed no significant difference between groups [F (1, 14) = 0.23; P = 0.64], but did show a trend for an effect of treatment [F (1, 14) = 3.72; P = 0.0742] and an interaction between group and treatment [F (1, 14) = 6.20; P = 0.026]. The comparison of the three groups of patients on the first assessment failed significance [F (2, 39) = 2.68; P = 0.08]. Post-hoc analysis showed that “Off-first” patients (P = 0.03) differed from controls, but not “On-first” patients (P = 0.28). Overall, these results confirm the existence of Reversal deficits in PD and show a trend for less commission errors under l-Dopa treatment. 3.7. Omission errors in Reversal Some values were also missing for the same reasons. Global ANOVA showed only a trend for a group effect [F (2, 39) = 2.67; P = 0.0815], a repetition effect [F (1, 39) = 16.78; P = 0.0002] and an interaction between group and repetition [F (2, 39) = 4.40; P = 0.0190] for omission errors in Reversal. Post-hoc analysis of the group effect showed that the two groups of patients did

not significantly differ (P = 0.75), but that “On-first” patients (P = 0.0447) and “Off-first” patients (P = 0.0102) differed from controls. The number of omission errors in Reversal was therefore similar in both groups of patients and impaired relative to controls. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in controls [F (1, 25) = 23.98; P < 0.0001] and in “Off-first” patients [F (1, 8) = 20.90; P = 0.0018], but not in “On-first” patients [F (1, 6) = 0.16; P = 0.90]. This lack of repetition effect in “On-first” patients explains the interaction between group and repetition. Patients ANOVA showed no significant difference between groups [F (1, 14) = 0.13; P = 0.73], but showed an effect of treatment [F (1, 14) = 6.49; P = 0.0232] and an interaction between group and treatment [F (1, 14) = 5.37; P = 0.0362]. The comparison of the three groups of patients on the first assessment failed significance [F (2, 39) = 2.87; P = 0.069]. Post-hoc analysis showed that controls and “On-first” patients performed similarly (P = 0.90) and that “Off-first” patients differed from controls (P = 0.03) and nearly differed (P = 0.069) from “On-first” patients. Overall, these results confirm the existence of Reversal deficits in PD and show a decrease of omission errors under l-Dopa treatment. 3.8. Last error in Extinction Global ANOVA showed a repetition effect [F (1, 48) = 4.53; P < 0.0385] for the last error in Extinction, but did not show a group effect [F (2, 48) = 1.95; P = 0.15] or an interaction between group and repetition [F (2, 48) = 0.95; P = 0.39]. Post-hoc analysis of the repetition effect showed a trend for a better performance in the second assessment in “On-first” patients [F (1, 9) = 4.52; P = 0.0623], but not in controls [F (1, 27) = 1.67; P = 0.21] or “Off-first” patients [F (1, 12) = 0.10; P = 0.76]. Patients ANOVA showed no significant difference between groups [F (1, 21) = 0.07; P = 0.79], no effect of treatment [F (1, 21) = 1.54; P = 0.23], and no interaction between group and treatment [F (1, 21) = .2.84; P = 0.11]. Overall, these results show no Extinction deficits in PD and no effect of treatment. 3.9. Perseveration errors in Extinction Some values were missing. Global ANOVA showed a repetition effect [F (1, 42) = 6.21; P = 0.0167] for perseveration errors in Extinction, but did not show a group effect [F (2, 42) = 1.93; P = 0.16] or an interaction between group and repetition [F (2, 42) = 2.44; P = 0.10]. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in “On-first” patients [F (1, 8) = 10.90; P = 0.01], but not in controls [F (1, 25) = 1.15; P = 0.29] or in “Off-first” patients [F (1, 9) = 0.02; P = 0.88].

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Patients ANOVA did not show a significant difference between groups [F (1, 17) = 0.15; P = 0.70], but did show an effect of treatment [F (1, 17) = 5.36; P = 0.0333] and an interaction between group and treatment [F (1, 17) = 6.37; P = 0.0219]. The comparison of the three groups of patients on the first assessment failed significance [F (2, 43) = 2.79; P = 0.0726]. Post-hoc analysis showed that “On-first” patients (P = 0.0229) differed from controls, but not “Off-first” patients (P = 0.58). Overall, these results confirm the lack of Extinction deficits in PD, but show a trend for more perseveration errors under l-Dopa treatment. 3.10. Attribution errors in Extinction Some values were missing. Global ANOVA showed no group effect [F (2, 42) = 1.14; P = 0.33], no repetition effect [F (1, 42) = 1.19; P = 0.28], and no interaction between group and repetition [F (2, 42) = 0.56; P = 0.57] for attribution errors in Extinction. Patients ANOVA showed no significant difference between groups [F (1, 17) = 0.13; P = 0.73], no effect of treatment [F (1, 17) = 0.59; P = 0.45] and no interaction between group and treatment [F (1, 17) = 1.23; P = 0.28]. Overall, these results confirm the mildness of Extinction deficits in PD. 3.11. Number of advantageous minus disadvantageous choices in the Gambling task Global ANOVA showed no group effect [F (2, 48) = 6.55; P = 0.22] for the number of advantageous minus disadvantageous choices in the Gambling task, but did show a repetition effect [F (1, 48) = 9.12; P < 0.004] and an interaction between group and repetition [F (2, 48) = 5.54; P = 0.0068]. Post-hoc analysis of the repetition effect showed a better performance in the second assessment in controls [F (1, 27) = 27.82; P < 0.0001], but neither in “On-first” patients [F (1, 9) = 0.43; P = 0.53] nor in “Off-first” patients [F (1, 12) = 0.24; P = 0.63]. This difference of repe-

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tition effects in controls and in patients explains the interaction. ANOVAs with repeated measures (five blocks of trials in each assessment) performed for each group of patients showed, in controls, a progressive increase of performance during the first assessment [F (4, 108) = 9.16; P < 0.0001] and during the second assessment [F (4, 108) = 10.47; P < 0.0001]; in “Off-first” patients, a progressive increase during the first assessment [F (4, 48) = 4.55; P < 0.0034] but not during the second assessment [F (4, 48) = 1.28; P = 0.29]; in “On-first” patients, no significant change during the first [F (4, 36) = 1.73; P = 0.16] or the second assessment [F (4, 36) = 0.03; P = 0.99]. Patients ANOVA showed no significant difference between groups [F (1, 21) = 0.28; P = 0.60], no effect of treatment [F (1, 21) = 0.05; P = 0.82] and no interaction between group and treatment [F (1, 21) = 0.70; P = 0.41]. Overall, these results show the existence of deficits in the Gambling task in PD, which are not sensitive to l-Dopa treatment (Fig. 1). 3.12. Correlation between experimental and other variables in controls and in patients In controls, age, gender, education, cognitive efficiency, and depression had no significant influence on the experimental variables (P > 0.10). The number of reversals was significantly correlated with the global score on the Gambling task (ρ = 0.44; P < 0.05). There was no other significant correlation among the experimental variables. In patients, demographic variables had little influence on the performance: a significant effect of age on the number of reversals (ρ = −0.43; P < 0.05) and of age (ρ = −0.46; P < 0.05) and education (ρ = 0.45; P < 0.05) on the global score of the Gambling task, but no effect of gender. The characteristics of the disease (age at onset, duration of disease and motor scores) had no significant influence on the experimental variables. There were some correlations between mood or cognitive performance of patients and experimental variables: (1) the Apathy Scale score and the MADRS score (ρ = 0.51; P < 0.05); (2) the Mattis

Fig. 1. Gambling task in controls, “Off-first” (first assessment without and second assessment with l-Dopa) and “On-first” (first assessment with and second assessment without l-Dopa) parkinsonian patients. Values are expressed as (mean ± S.E.M.) total number of cards selected from advantageous minus disadvantageous decks from the 1st to the 100th trial in 5 blocks of 20 cards.

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Dementia Rating Scale score and the number of trials on Stimulus–Reward Learning (ρ = −0.53; P < 0.05), the number of errors in the first reversal (ρ = −0.42; P < 0.05), and the number of commission (ρ = −0.56; P < 0.01) and omission (ρ = −0.59; P < 0.01) errors in Reversal; (3) the “frontal score” and the number of commission (ρ = −0.44; P < 0.05) and omission (ρ = −0.43; P < 0.05) errors in Reversal and the global score of the Gambling task (ρ = −0.59; P < 0.01). There were no significant relationships among the experimental variables. 3.13. Synthesis of main results The performance of control subjects showed: (1) an improvement from the first to the second assessment on Stimulus–Reward Learning and on all variables of Reversal, but no significant change on the Apathy Scale or Extinction; (2) a progressive improvement on the Gambling task, both during each assessment and from the first to the second assessment. Compared to controls, patients were: (1) apathetic; (2) impaired on Stimulus–Reward Learning and on all variables of Reversal, but not on Extinction; and (3) unable to progress in the second assessment of the Gambling task. The effect of l-Dopa therapy was clear on the Apathy Scale, with an improvement of motivation under treatment. It was less clear on other variables: no overall effect on Stimulus–Reward Learning, Reversal or Extinction; contrasting effects on omission errors in Reversal, decreased under l-Dopa, and perseveration errors in Extinction, increased under l-Dopa. There was no influence of disease characteristics on these variables.

4. Discussion Several experimental variables were impaired in patients with PD. Their score on the Apathy Scale was higher than in control subjects, confirming that apathy may be observed in PD, even in non-demented and -depressed patients. Apathy was mild, since the mean score for patients was lower than the cut-off pathological score of 14. However, three patients in the “On-first” subgroup and six patients in the “Off-first” subgroup had pathological scores, comprising 39% of patients. This percentage is higher than that of 12% reported by Starkstein et al. [45] in non-depressed patients, and is probably related to a longer evolution of the disease. Although the patients in our study were not clinically depressed, there was a mild but significant correlation between the Apathy Scale and MADRS scores, probably due to anhedonia, a common factor in the two scales. Stimulus–Reward Learning was also impaired in patients. In normal controls, it required only some trials and errors. The acquisition was conscious (at the end of the first learning all controls said that they had to touch a stimulus and not to touch the other one) and easily transferred to another pair of patterns (the second Stimulus–Reward Learning task

attained a ceiling effect and was nearly perfect from the first assessment). When compared to controls, the performance of PD patients was impaired in both Stimulus–Reward Learning tasks, although they were able to learn and transfer the rule of reinforcement to a new pair of patterns, since their performance was normalised before extinction in the second assessment. Such a deficit is in agreement with the results recently obtained with a more complex task of Stimulus–Reward Concurrent Learning [47]. The task used in the present study, given its cognitive simplicity, better demonstrates the existence of an explicit reinforcement associated learning deficit in non-demented and -depressed PD patients. In controls, Reversal improved in the second assessment, where it was nearly optimal. This was not the case for the Extinction task, suggesting that it is easier to explicitly reverse the Stimulus–Reward association than to inhibit all responses. The difference between patients and control subjects was highly significant for Reversal but not for Extinction. These results are in favour of a deficit in “sensitivity to reward” flexibility rather than in control of impulsiveness, and are in line with those obtained using more cognitively complex tasks of probabilistic and concurrent reversal [47]. One of the advantages of the task designed by Rolls et al. [41] lies in its very low cognitive demand, allowing a clear dissociation to be demonstrated in patients with orbitofrontal lesion between impaired “sensitivity to reward” flexibility, shown by the deficit in Reversal, and preserved “cognitive” flexibility, shown by a normal performance on the Tower of London task. The same authors underlined the existence of a converse dissociation in patients with lesion of the dorsolateral prefrontal cortex, whose performance was normal in Reversal and impaired in cognitive planning. In our study, a mild, but significant correlation was observed between “sensitivity to reward” (Reversal) and “cognitive” (Mattis Dementia Rating Scale and frontal scores) flexibility. This may be due to the fact that PD is associated with the dysfunction of both the “dorsolateral prefrontal” circuit, implicated in “cognitive” flexibility, and “orbitofrontal” and “anterior cingulate” circuits, involved in “sensitivity to reward” flexibility [11]. The progression of performance of control subjects was slower on the Gambling task as shown by Bechara et al. [3]. Only 50% of controls were conscious of the difference between advantageous and disadvantageous decks of cards. These results confirm the more implicit dimension of the reinforcement learning in the Gambling task. In the first assessment, PD patients performed in a similar manner to control subjects, in agreement with a recent study by Stout et al. [46], but did not progress further in the second assessment, which is a new result. It may be hypothesised that a decrease in motivation or in sensitivity to reinforcement impairs the mobilisation or maintenance of attentional resources required by this particular type of implicit learning [34]. Indeed, in tasks such as the Tower of Toronto [42] or Serial Reaction Times [23], learning scores increase during the

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first stages but do not progress further, suggesting an impairment of long-term consolidation processes [12,14], which may rely on motivation and sensitivity to reinforcement. An alternative explanation is that a progressive awareness might be necessary for a further progression of reinforcement associated learning [44]. This would be supported by the fact that in our study only 13% of patients compared to 50% of control subjects became aware of the difference between advantageous and disadvantageous decks of cards. To summarise, patients with PD were impaired in motivation, in explicit and implicit reinforcement associated learning, and in “sensitivity to reward” flexibility. It might be objected that the deficits of parkinsonian patients observed in the Reinforcement Associated Learning and Reversal tasks result from cognitive problems rather than from a dysfunction of motivation or reward sensitivity. First, deficits of executive functions, working memory, and learning have been observed in PD [36], and might influence the performance. Reinforcement Associated Learning and Reversal tasks, however, have been repeatedly shown to be only disturbed following lesions of the orbitofrontal areas and not following lesions of the dorsolateral cortex, both in primates [40] and in humans [3,41]. Furthermore, as previously underlined, double dissociations have been found in patients with frontal lobe or subcortical lesions between performance on cognitive tests of executive functions and sensitivity to reinforcement [41], between working memory and decision making [5], and between attentional set-shifting and reversal [39,49], suggesting a relative independence between cognition and sensitivity to reward. Second, it might be considered that the rewards used in the study were too symbolic to be truly reinforcing. The reinforcing value of abstract reward was confirmed, however, by the behaviour of control subjects, who were disappointed to lose even symbolic dollars, and by a recent fMRI study showing a correlation between brain activation in orbitofrontal areas and the magnitude of symbolic monetary gain or losses [32]. These data suggest, therefore, an impairment of reward sensitivity in PD, in agreement with the results obtained by Swainson et al. [47]. Interestingly, there was no correlation between motivation and sensitivity to reward deficits. This is likely due to the diversity of implicated neuropsychological processes involved: subjective feeling versus objective performance, explicit versus implicit reinforcement associated learning, reversal versus learning. For instance, a correlation between the number of reversals and the performance on the Gambling task was observed in controls who became progressively aware of the strategy to adopt, but disappeared in patients who remained unaware. The different sensitivity of these deficits to dopaminergic therapy is also indicative of the diversity of underlying neurophysiologic mechanisms. The Apathy Scale improved in the “on” state. This dopaminergic reactivity of apathy has not been shown before. It is in agreement with studies showing an improvement of the subjective state of patients when they are at the optimal therapeutic effect of dopaminergic therapy [9,27],

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but it is more specific to motivation. By contrast, explicit Stimulus–Reward Learning and most of the variables of Reversal were not clearly sensitive to dopaminergic therapy. This would appear surprising bearing in mind that various experimental studies in primates implicate dopamine in reinforcement associated learning [43]. The transfer of reinforcement associated learning from the “on” to the “off” state might be hampered by the difference in physiological states, as it has been shown that verbal learning under alcohol is more difficult to evoke in the state of abstinence [19]. Another explanation is that dopaminergic depletion is more severe in the nigrostriatal system than in the mesocorticolimbic system. Medication doses sufficient to restore dopamine function in the most affected region (the dorsal striatum) could be excessive for other less affected regions (ventral striatum) [22]. In agreement with this hypothesis, recent studies found a deficit in reversal learning when parkinsonian patients were medicated [47], with a relative improvement following l-Dopa withdrawal [8]. Such an interpretation might explain the greater number of perseveration errors in Extinction under l-Dopa treatment, since PD patients included in our study were candidates for deep brain stimulation of the subthalamic nucleus and received high doses of l-Dopa [35]. However, the deleterious effects of medication on the mesocorticolimbic dopaminergic system cannot account for the deficits observed in the “off” state. The longer duration of the disease in our group of patients would be accompanied by more extensive dopamine depletion in the ventral striatum, leading to an abolition of this overdose effect. In agreement with this interpretation, l-Dopa treatment decreased the number of omission errors in Reversal. The lack of influence of dopaminergic therapy in the Gambling task is noteworthy, given the hypothesis, drawn from primate studies, that the fluctuating output of dopaminergic neurons signals changes or errors in the prediction of future salient and rewarding events, suggesting that dopamine is implicated in the neuronal changes that allow behaviour to be guided by reinforcement [18]. This kind of implicit learning would require processes of long-term consolidation [12,14], which are probably poorly sensitive to the short-term fluctuations of dopaminergic therapy. In conclusion, these results implicate striatofrontal loops in human motivation, explicit and implicit sensitivity to reinforcement, and “sensitivity to reward” flexibility. They also underline the complexity of the relationships between these factors, due to the participation of various neuropsychological and underlying dopaminergic mechanisms.

Acknowledgements INSERM and Assistance Publique supported the study. Dr. A. Bechara kindly provided us with the computerised version of his Gambling task. Dr. A.M. Bonnet and the nurses of the Centre d’Investigation Clinique and Federation

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