Document Type

Article

Publication Date

11-1-2016

Journal

Journal of Psychiatry and Neuroscience

Volume

41

Issue

6

First Page

367

Last Page

376

URL with Digital Object Identifier

10.1503/jpn.150234

Abstract

Background: Increasing evidence indicates that psychosis is associated with abnormal reward processing. Imaging studies in patients with first-episode psychosis (FEP) have revealed reduced activity in diverse brain regions, including the ventral striatum, insula and anterior cingulate cortex (ACC), during reward prediction. However, whether these reductions in local brain activity are due to altered connectivity has rarely been explored. Methods: We applied dynamic causal modelling and Bayesian model selection to fMRI data during the Salience Attribution Task to investigate whether patients with FEP showed abnormal modulation of connectivity between the ventral striatum, insula and ACC induced by rewarding cues and whether these changes were related to positive psychotic symptoms and atypical antipsychotic medication. Results: The model including reward-induced modulation of insula-ACC connectivity was the best fitting model in each group. Compared with healthy controls (n = 19), patients with FEP (n = 29) revealed reduced right insula-ACC connectivity. After subdividing patients according to current antipsychotic medication, we found that the reduced insula-ACC connectivity relative to healthy controls was observed only in untreated patients (n = 17), not in patients treated with antipsychotics (n = 12), and that it correlated negatively with unusual thought content in untreated patients with FEP. Limitations: The modest sample size of untreated patients with FEP was a limitation of our study. Conclusion: This study indicates that insula-ACC connectivity during reward prediction is reduced in untreated patients with FEP and related to the formation of positive psychotic symptoms. Our study further suggests that atypical antipsychotics may reverse connectivity between the insula and the ACC during reward prediction.

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