Brain Functional Segregation Predicts Symptom Severity and Treatment Response in Psychotic Disorders

Abstract

Functional segregation, i.e., anticorrelated neural activities, has not been well-explored in fMRI studies. We introduced the Negative Degree Centrality (NDC) method to quantify functional segregation. We found decreased NDC in psychotic disorder patients compared to controls. Positive, negative, and general psychotic symptoms were associated with impaired NDC in three different brain networks respectively. Using NDC and a machine learning approach, we identified two subgroups of patients with distinct recovery trajectories after one-year treatment. Our findings suggested impaired functional segregation in different brain circuits might be the neurobiological mechanisms associated with various psychotic symptoms and outcome heterogeneity in psychotic disorders.