Motor Learning and Decision Making in Volatile Environment in Bipolar Disorder

Abstract

Predictive processing currently is one of the major lines of research in computational psychiatry. There is substantial evidence for the impaired Bayesian learning in affective disorders., and in particular impaired learning about uncertainty estimations. Based on our previous results in state and trait anxiety., we developed a study design., completed a pilot study and are now in the process of participant recruitment and data acquisition in order to test our hypotheses. We hypothesize that changes in learning in volatile environment may be an important feature., if not the core feature., of bipolar disorder. Also., we pose the questions of possible changes in motor learning and in neurophysiological markers of predictive coding in bipolar disorder.