Alpha band EEG resting-state dynamic functional source connectivity in first-episode schizophrenia

Schizophrenia is a complex and severe mental illness that remains challenging to characterize. This study investigates dynamic functional source connectivity in the alpha band from resting-state EEG in individuals experiencing the first episode of schizophrenia and matched controls. Cortical sources were estimated from EEG data, and static and dynamic functional connectivity were computed in the alpha band. The dynamic connectivity matrices were clustered to identify brain network states, from which temporal, power, and graph theory features were obtained for each subject. Statistical analysis showed no differences between patients and controls but identified significant correlations between metrics and cognitive and pathopsychological scores. These findings highlight the potential of dynamic approaches in providing a complementary set of features in characterizing schizophrenia.