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Computational modeling of reversal learning impairments in schizophrenia and bipolar disorder reveals shared failure
Angus W MacDonald1, Edward Patzelt2, Zeb Kurth-Nelson3
1Department of Psychology, University of Minnesota.
Abstract:
The distinction between the concepts of schizophrenia and bipolar disorder is fundamental to the Kraepelinian tradition in psychiatry. One mechanism undergirding this distinction, a difference in reward sensitivity, has been championed by a number of scholars. As part of the Cognitive Neuroscience Test Reliability and Clinical applications for Serious mental illnesses consortium, 225 participants including people with schizophrenia (n = 69), schizoaffective disorder (n = 55), and bipolar affective disorder (n = 53) performed a probabilistic reversal learning task. This task switches the rewarded stimulus at various times throughout the task. Our analyses leveraged a Hidden Markov Model to examine trial-by-trial decisions of participants to reveal the differences between patient groups in their response to reward feedback. Whereas no patient group showed difficulty reversing their preferred categories after a switch in the task's contingencies and bipolar patient performance was spared in some other ways, all patient groups made more errors throughout the task because of a greater tendency to shift away from rewarded categories (i.e., win-switching). Furthermore, patients' cognitive ability is specifically related to this aspect of the task. Rather than validating a Kraepelinian dichotomy, these findings suggest that a failure to exploit rewards may reflect a mechanistic deficit common across both affective and nonaffective psychoses related to cognitive impairments in patients. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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