Impulse control disorders in Parkinson's disease are associated with dysfunction in stimulus valuation but not action valuation.
Identifieur interne : 000A39 ( Main/Exploration ); précédent : 000A38; suivant : 000A40Impulse control disorders in Parkinson's disease are associated with dysfunction in stimulus valuation but not action valuation.
Auteurs : Payam Piray [Pays-Bas] ; Yashar Zeighami [Canada] ; Fariba Bahrami [Iran] ; Abeer M. Eissa ; Doaa H. Hewedi ; Ahmed A. Moustafa [Pays-Bas]Source :
- The Journal of neuroscience : the official journal of the Society for Neuroscience [ 1529-2401 ] ; 2014.
English descriptors
- KwdEn :
- Aged, Antipsychotic Agents (therapeutic use), Computer Simulation, Disruptive, Impulse Control, and Conduct Disorders (complications), Female, Humans, Male, Middle Aged, Models, Psychological, Parkinson Disease (complications), Parkinson Disease (drug therapy), Probability Learning, Punishment, Reinforcement (Psychology), Reward, Severity of Illness Index.
- MESH :
- chemical , therapeutic use : Antipsychotic Agents.
- complications : Disruptive, Impulse Control, and Conduct Disorders, Parkinson Disease.
- drug therapy : Parkinson Disease.
- Aged, Computer Simulation, Female, Humans, Male, Middle Aged, Models, Psychological, Probability Learning, Punishment, Reinforcement (Psychology), Reward, Severity of Illness Index.
Abstract
A substantial subset of Parkinson's disease (PD) patients suffers from impulse control disorders (ICDs), which are side effects of dopaminergic medication. Dopamine plays a key role in reinforcement learning processes. One class of reinforcement learning models, known as the actor-critic model, suggests that two components are involved in these reinforcement learning processes: a critic, which estimates values of stimuli and calculates prediction errors, and an actor, which estimates values of potential actions. To understand the information processing mechanism underlying impulsive behavior, we investigated stimulus and action value learning from reward and punishment in four groups of participants: on-medication PD patients with ICD, on-medication PD patients without ICD, off-medication PD patients without ICD, and healthy controls. Analysis of responses suggested that participants used an actor-critic learning strategy and computed prediction errors based on stimulus values rather than action values. Quantitative model fits also revealed that an actor-critic model of the basal ganglia with different learning rates for positive and negative prediction errors best matched the choice data. Moreover, whereas ICDs were associated with model parameters related to stimulus valuation (critic), PD was associated with parameters related to action valuation (actor). Specifically, PD patients with ICD exhibited lower learning from negative prediction errors in the critic, resulting in an underestimation of adverse consequences associated with stimuli. These findings offer a specific neurocomputational account of the nature of compulsive behaviors induced by dopaminergic drugs.
DOI: 10.1523/JNEUROSCI.4063-13.2014
PubMed: 24899705
Affiliations:
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Eissa</name><affiliation><nlm:affiliation>Psychogeriatric Research Center, Department of Psychiatry, School of Medicine, Ain Shams University, 11566 Cairo, Egypt, and.</nlm:affiliation><wicri:noCountry code="subField">and</wicri:noCountry></affiliation></author><author><name sortKey="Hewedi, Doaa H" sort="Hewedi, Doaa H" uniqKey="Hewedi D" first="Doaa H" last="Hewedi">Doaa H. Hewedi</name><affiliation><nlm:affiliation>Psychogeriatric Research Center, Department of Psychiatry, School of Medicine, Ain Shams University, 11566 Cairo, Egypt, and.</nlm:affiliation><wicri:noCountry code="subField">and</wicri:noCountry></affiliation></author><author><name sortKey="Moustafa, Ahmed A" sort="Moustafa, Ahmed A" uniqKey="Moustafa A" first="Ahmed A" last="Moustafa">Ahmed A. Moustafa</name><affiliation wicri:level="1"><nlm:affiliation>School of Social Sciences and Psychology and Marcs Institute for Brain and Behaviour, University of Western Sydney, NSW 2751, Australia p.piray@donders.ru.nl a.moustafa@uws.edu.au.</nlm:affiliation><country wicri:rule="url">Pays-Bas</country><wicri:regionArea>School of Social Sciences and Psychology and Marcs Institute for Brain and Behaviour, University of Western Sydney, NSW 2751</wicri:regionArea><wicri:noRegion>NSW 2751</wicri:noRegion></affiliation></author></analytic><series><title level="j">The Journal of neuroscience : the official journal of the Society for Neuroscience</title><idno type="eISSN">1529-2401</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Aged</term><term>Antipsychotic Agents (therapeutic use)</term><term>Computer Simulation</term><term>Disruptive, Impulse Control, and Conduct Disorders (complications)</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Models, Psychological</term><term>Parkinson Disease (complications)</term><term>Parkinson Disease (drug therapy)</term><term>Probability Learning</term><term>Punishment</term><term>Reinforcement (Psychology)</term><term>Reward</term><term>Severity of Illness Index</term></keywords><keywords scheme="MESH" type="chemical" qualifier="therapeutic use" xml:lang="en"><term>Antipsychotic Agents</term></keywords><keywords scheme="MESH" qualifier="complications" xml:lang="en"><term>Disruptive, Impulse Control, and Conduct Disorders</term><term>Parkinson Disease</term></keywords><keywords scheme="MESH" qualifier="drug therapy" xml:lang="en"><term>Parkinson Disease</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Aged</term><term>Computer Simulation</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Models, Psychological</term><term>Probability Learning</term><term>Punishment</term><term>Reinforcement (Psychology)</term><term>Reward</term><term>Severity of Illness Index</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A substantial subset of Parkinson's disease (PD) patients suffers from impulse control disorders (ICDs), which are side effects of dopaminergic medication. Dopamine plays a key role in reinforcement learning processes. One class of reinforcement learning models, known as the actor-critic model, suggests that two components are involved in these reinforcement learning processes: a critic, which estimates values of stimuli and calculates prediction errors, and an actor, which estimates values of potential actions. To understand the information processing mechanism underlying impulsive behavior, we investigated stimulus and action value learning from reward and punishment in four groups of participants: on-medication PD patients with ICD, on-medication PD patients without ICD, off-medication PD patients without ICD, and healthy controls. Analysis of responses suggested that participants used an actor-critic learning strategy and computed prediction errors based on stimulus values rather than action values. Quantitative model fits also revealed that an actor-critic model of the basal ganglia with different learning rates for positive and negative prediction errors best matched the choice data. Moreover, whereas ICDs were associated with model parameters related to stimulus valuation (critic), PD was associated with parameters related to action valuation (actor). Specifically, PD patients with ICD exhibited lower learning from negative prediction errors in the critic, resulting in an underestimation of adverse consequences associated with stimuli. These findings offer a specific neurocomputational account of the nature of compulsive behaviors induced by dopaminergic drugs.</div></front></TEI><affiliations><list><country><li>Canada</li><li>Iran</li><li>Pays-Bas</li></country><region><li>Québec</li></region><settlement><li>Montréal</li></settlement><orgName><li>Université McGill</li></orgName></list><tree><noCountry><name sortKey="Eissa, Abeer M" sort="Eissa, Abeer M" uniqKey="Eissa A" first="Abeer M" last="Eissa">Abeer M. Eissa</name><name sortKey="Hewedi, Doaa H" sort="Hewedi, Doaa H" uniqKey="Hewedi D" first="Doaa H" last="Hewedi">Doaa H. Hewedi</name></noCountry><country name="Pays-Bas"><noRegion><name sortKey="Piray, Payam" sort="Piray, Payam" uniqKey="Piray P" first="Payam" last="Piray">Payam Piray</name></noRegion><name sortKey="Moustafa, Ahmed A" sort="Moustafa, Ahmed A" uniqKey="Moustafa A" first="Ahmed A" last="Moustafa">Ahmed A. Moustafa</name></country><country name="Canada"><region name="Québec"><name sortKey="Zeighami, Yashar" sort="Zeighami, Yashar" uniqKey="Zeighami Y" first="Yashar" last="Zeighami">Yashar Zeighami</name></region></country><country name="Iran"><noRegion><name sortKey="Bahrami, Fariba" sort="Bahrami, Fariba" uniqKey="Bahrami F" first="Fariba" last="Bahrami">Fariba Bahrami</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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