Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder

by Lara Henco, Andreea O. Diaconescu, Juha M. Lahnakoski, Marie-Luise Brandi, Sophia H örmann, Johannes Hennings, Alkomiet Hasan, Irina Papazova, Wolfgang Strube, Dimitris Bolis, Leonhard Schilbach, Christoph Mathys Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and nonsocial information. Patients with schizophrenia and borderline personality disorder performed more poorly o n the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and MDD patients showed the opposite pattern and SCZ patients showed n o difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters e stimated for each participant from their behavior. This enabled additional insigh...
Source: PLoS Computational Biology - Category: Biology Authors: Source Type: research