Journal
NEURON
Volume 65, Issue 1, Pages 135-142Publisher
CELL PRESS
DOI: 10.1016/j.neuron.2009.12.027
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Funding
- National Institute of Neurological Disorders and Stroke, National Institutes of Health
- NINDS/NIH
- Wellcome Trust
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Pathological 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.
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