Classification of social anhedonia using temporal and spatial network features from a social cognition fMRI task.

ABSTRACT: Previous studies have suggested that the degree of social anhedonia reflects the vulnerability for developing schizophrenia. However, only few studies have investigated how functional network changes are related to social anhedonia. The aim of this fMRI study was to classify subjects according to their degree of social anhedonia using supervised machine learning. More specifically, we extracted both spatial and temporal network features during a social cognition task from 70 subjects, and used support vector machines for classification. Since impairment in social cognition is well established in schizophrenia-spectrum disorders, the subjects performed a comic strip task designed to specifically probe theory of mind (ToM) and empathy processing. Features representing both temporal (time ser

SUBMITTER: Krohne LG 

PROVIDER: S-EPMC6865405 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature