Identifying Neurophysiological Subtypes in Clinical High Risk for Psychosis Using Functional Connectome Profiling
Related Experiment Video
Updated: Oct 31, 2026
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Guoliang Hou1, Jiayu Feng1, Yulin Wang1
1Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China.
Background And Hypothesis:
The clinical high-risk (CHR) state already harbors substantial heterogeneity. Delineating homogeneous subgroups at this stage is critical for elucidating disease mechanisms and advancing precision psychiatry. However, the neurobiological heterogeneity among individuals at CHR and its clinical relevance remain poorly understood. Study Design: We applied Heterogeneity Through Discriminative Analysis to resting-state functional connectome profiling to identify potential neurophysiological subtypes within a large multicenter CHR dataset (N = 838) compared to healthy controls (HC) (N = 244).
Study Results:
The results revealed 2 distinct neurophysiological subtypes within the CHR population. Subtype 1 exhibited widespread reductions in overall functional connectivity-particularly within the sensorimotor network and the salience network-whereas Subtype 2 showed widespread increases within these networks. Compared with HC and Subtype 1, Subtype 2 showed poorer performance in sustained attention and verbal learning/memory. However, Subtype 1 did not differ significantly from HC in these domains.
Conclusions:
These findings provide robust evidence for neurophysiological subtypes among individuals at CHR and further suggest that patterns of aberrant brain network organization have already diverged during the CHR stage, accompanied by dissociable cognitive profiles.
