Motivational Context Modulates Prediction Error Response in Schizophrenia

Jenna M. Reinen, Jared X. Van Snellenberg, Guillermo Horga, Anissa Abi-Dargham, Nathaniel D. Daw, Daphna Shohamy

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Background: Recent findings demonstrate that patients with schizophrenia are worse at learning to predict rewards than losses, suggesting that motivational context modulates learning in this disease. However, these findings derive from studies in patients treated with antipsychotic medications, D2 receptor antagonists that may interfere with the neural systems that underlie motivation and learning. Thus, it remains unknown how motivational context affects learning in schizophrenia, separate from the effects of medication. Methods: To examine the impact of motivational context on learning in schizophrenia, we tested 16 unmedicated patients with schizophrenia and 23 matched controls on a probabilistic learning task while they underwent functional magnetic resonance imaging (fMRI) under 2 conditions: one in which they pursued rewards, and one in which they avoided losses. Computational models were used to derive trial-by-trial prediction error responses to feedback. Results: Patients performed worse than controls on the learning task overall, but there were no behavioral effects of condition. FMRI revealed an attenuated prediction error response in patients in the medial prefrontal cortex, striatum, and medial temporal lobe when learning to predict rewards, but not when learning to avoid losses. Conclusions: Patients with schizophrenia showed differences in learning-related brain activity when learning to predict rewards, but not when learning to avoid losses. Together with prior work, these results suggest that motivational deficits related to learning in schizophrenia are characteristic of the disease and not solely a result of antipsychotic treatment.

Original languageEnglish (US)
Pages (from-to)1467-1475
Number of pages9
JournalSchizophrenia Bulletin
Issue number6
StatePublished - Nov 1 2016

All Science Journal Classification (ASJC) codes

  • Psychiatry and Mental health


  • antipsychotic medication
  • model-based fMRI
  • neuroimaging
  • prediction error
  • reinforcement learning


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