Mechanisms Underlying Dopamine-Mediated Reward Bias in Compulsive Behaviors
| Autor: | Cecile Gallea, Mark Hallett, Raymond J. Dolan, Hubert H. Fernandez, Valerie Voon, Christina Brezing, Mathias Pessiglione |
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| Rok vydání: | 2010 |
| Předmět: |
Dopamine
Neuroscience(all) media_common.quotation_subject Mean squared prediction error Better than Expected Choice Behavior Outcome (game theory) Article Developmental psychology 03 medical and health sciences 0302 clinical medicine Bias Reward medicine Humans Learning Reinforcement learning Reinforcement 030304 developmental biology media_common 0303 health sciences General Neuroscience Addiction Parkinson Disease Magnetic Resonance Imaging Corpus Striatum Compulsive behavior Gambling Compulsive Behavior medicine.symptom Psychology Reinforcement Psychology 030217 neurology & neurosurgery medicine.drug Cognitive psychology |
| Zdroj: | Neuron |
| ISSN: | 0896-6273 |
| Popis: | SummaryPathological behaviors such as problem gambling or shopping are characterized by compulsive choice despite alternative options and negative costs. Reinforcement learning algorithms allow a computation of prediction error, a comparison of actual and expected outcomes, which updates our predictions and influences our subsequent choices. Using a reinforcement learning model, we show data consistent with the idea that dopamine agonists in susceptible individuals with Parkinson's disease increase the rate of learning from gain outcomes. Dopamine agonists also increase striatal prediction error activity, thus signifying a “better than expected” outcome. Thus, our findings are consistent with a model whereby a distorted estimation of the gain cue underpins a choice bias toward gains. |
| Databáze: | OpenAIRE |
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