Action selection in early stages of psychosis: an active inference approach.

ABSTRACT:

Background

To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls.

Methods

SUBMITTER: Knolle F 

PROVIDER: S-EPMC9949875 | biostudies-literature | 2023 Jan-Feb

REPOSITORIES: biostudies-literature