Open AccessClassification of social anhedonia using temporal and spatial network features from a social cognition fMRI task
Author(s) -
Krohne Laerke Gebser,
Wang Yi,
Hinrich Jesper L.,
Moerup Morten,
Chan Raymond C. K.,
Madsen Kristoffer H.
Publication year - 2019
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.24751
Subject(s) - anhedonia , schizotypy , psychology , schizophrenia (object oriented programming) , cognitive psychology , cognition , functional magnetic resonance imaging , brain activity and meditation , task (project management) , developmental psychology , neuroscience , electroencephalography , management , psychiatry , economics
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 series) and network dynamics were extracted using task activation maps, seed region analysis, independent component analysis (ICA), and a newly developed multi‐subject archetypal analysis (MSAA), which here aimed to further bridge aspects of both seed region analysis and decomposition by incorporating a spotlight approach.We found significant classification of subjects with elevated levels of social anhedonia when using the times series extracted using MSAA, indicating that temporal dynamics carry important information for classification of social anhedonia. Interestingly, we found that the same time series yielded the highest classification performance in a task classification of the ToM condition. Finally, the spatial network corresponding to that time series included both prefrontal and temporal‐parietal regions as well as insula activity, which previously have been related schizotypy and the development of schizophrenia.