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J Neurosci. 2016 Jun 22;36(25):6623-33. doi: 10.1523/JNEUROSCI.3078-15.2016.

Computational Dissection of Dopamine Motor and Motivational Functions in Humans.

Author information

1
Motivation, Brain and Behavior Team, Institut du cerveau et de la Moelle Epinière, INSERM UMR1127, CNRS UMR 7225, Université Pierre et Marie Curie-Paris 6, Urgences cérébro-vasculaires, and.
2
Motivation, Brain and Behavior Team, Institut du cerveau et de la Moelle Epinière, INSERM UMR1127, CNRS UMR 7225, Université Pierre et Marie Curie-Paris 6.
3
Centre Multidisciplinaire des Sciences Comportementales Sorbonne Universités-INSEAD, 75005 Paris, and Economic Decision-Making Group, Laboratoire des Neurosciences Cognitives, Département d'Etudes Cognitives, Ecole Normale Supérieure, 75005 Paris, France.
4
INSERM UMR1127, CNRS UMR 7225, Université Pierre et Marie Curie-Paris 6, Département des Maladies du Système Nerveux, Centre Expert Inter-Régional de la Maladie de Parkinson, Hôpital de la Pitié-Salpêtrière, Assistance publique-Hôpitaux de Paris, 75013 Paris, France.
5
Motivation, Brain and Behavior Team, Institut du cerveau et de la Moelle Epinière, INSERM UMR1127, CNRS UMR 7225, Université Pierre et Marie Curie-Paris 6, mathias.pessiglione@gmail.com.

Abstract

Motor dysfunction (e.g., bradykinesia) and motivational deficit (i.e., apathy) are hallmarks of Parkinson's disease (PD). Yet, it remains unclear whether these two symptoms arise from a same dopaminergic dysfunction. Here, we develop a computational model that articulates motor control to economic decision theory, to dissect the motor and motivational functions of dopamine in humans. This model can capture different aspects of the behavior: choice (which action is selected) and vigor (action speed and intensity). It was used to characterize the behavior of 24 PD patients, tested both when medicated and unmedicated, in two behavioral tasks: an incentive motivation task that involved producing a physical effort, knowing that it would be multiplied by reward level to calculate the payoff, and a binary choice task that involved choosing between high reward/high effort and low reward/low effort options. Model-free analyses in both tasks showed the same two effects when comparing unmedicated patients to medicated patients: dopamine depletion (1) decreased the amount of effort that patients were willing to produce for a given reward and (2) slowed down the production of this effort, regardless of reward level. Model-based analyses captured these effects with two independent parameters, namely reward sensitivity and motor activation rate. These two parameters were respectively predictive of medication effects on clinical measures of apathy and motor dysfunction. More generally, we suggest that such computational phenotyping might help characterizing deficits and refining treatments in neuropsychiatric disorders.

SIGNIFICANCE STATEMENT:

Many neurological conditions are characterized by motor and motivational deficits, which both result in reduced behavior. It remains extremely difficult to disentangle whether these patients are simply unable or do not want to produce a behavior. Here, we propose a model-based analysis of the behavior produced in tasks that involve trading physical efforts for monetary rewards, to quantify parameters that capture motor dynamics as well as sensitivity to reward, effort, and fatigue. Applied to Parkinson's disease, this computational analysis revealed two independent effects of dopamine enhancers, which predicted clinical improvement in motor and motivational deficits. Such computational profiling might provide a useful explanatory level, between neural dysfunction and clinical manifestations, for characterizing neuropsychiatric disorders and personalizing treatments.

KEYWORDS:

Parkinson's disease; decision making; dopamine; effort; motivation; reward

PMID:
27335396
DOI:
10.1523/JNEUROSCI.3078-15.2016
[Indexed for MEDLINE]
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