Background: Negative symptoms are core features of schizophrenia (SZ); however, the cognitive and neural basis for individual negative symptom domains remains unclear. Converging evidence suggests a role for striatal and prefrontal dopamine in reward learning and the exploration of actions that might produce outcomes that are better than the status quo. The current study examines whether deficits in reinforcement learning and uncertainty-driven exploration predict specific negative symptom domains.
Methods: We administered a temporal decision-making task, which required trial-by-trial adjustment of reaction time to maximize reward receipt, to 51 patients with SZ and 39 age-matched healthy control subjects. Task conditions were designed such that expected value (probability × magnitude) increased, decreased, or remained constant with increasing response times. Computational analyses were applied to estimate the degree to which trial-by-trial responses are influenced by reinforcement history.
Results: Individuals with SZ showed impaired Go learning but intact NoGo learning relative to control subjects. These effects were most pronounced in patients with higher levels of negative symptoms. Uncertainty-based exploration was substantially reduced in individuals with SZ and selectively correlated with clinical ratings of anhedonia.
Conclusions: Schizophrenia patients, particularly those with high negative symptoms, failed to speed reaction times to increase positive outcomes and showed reduced tendency to explore when alternative actions could lead to better outcomes than the status quo. Results are interpreted in the context of current computational, genetic, and pharmacological data supporting the roles of striatal and prefrontal dopamine in these processes.
Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.