Increased conflict-induced slowing, but no differences in conflict-induced positive or negative prediction error learning in patients with schizophrenia

Abstract

People with schizophrenia (PSZ) often fail to pursue rewarding activities despite largely intact in-the-moment hedonic experiences. Deficits in effort-based decision making in PSZ may be related to enhanced effects of cost or reduced reward, i.e., through the amplification of negative prediction errors or by dampened positive prediction errors (here, positive and negative prediction errors refer to outcomes that are better or worse than expected respectively). We administered a modified Simon task to people with schizophrenia (PSZ; N = 46) and healthy controls (N = 32). The modification included a reinforcement learning component, where positive and negative prediction errors are dampened or boosted through the use of cognitively-effortful response conflict. EEG was recorded concurrently to investigate potential differences in conflict enhanced mid-frontal theta power between PSZ and controls. We found an enhanced effect of response conflict on response time in people with schizophrenia, but no discernible difference in conflict processing as reflected by the lack of a difference in theta-power enhancement to conflict in mid-frontal regions. Using the reinforcement learning transfer phase of the modified Simon task, PSZ also showed clear deficits in selecting the most rewarding stimulus during the 'easy' (most discriminable in terms of value) stimulus contrasts. However, we failed to find a difference between patients and controls in their gain or avoidance learning bias, nor did these biases correlate with negative symptoms. Previous studies had failed to find significant conflict effects on the Simon task likely due to its modest effect size. Our results show that PSZ do indeed possess subtle impairments in response-conflict, suggesting an increase in cognitive effort required for appropriate responding. In addition, while the lack of an overt positive or negative prediction error bias (i.e., a bias towards punishment or reward learning) was unexpected, it is consistent with recent work showing intact estimation of value when the reinforcement learning system is isolated from other contributors to value learning.