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Functional Connectivity-Based Searchlight Multivariate Pattern Analysis for Discriminating Schizophrenia Patients and
Yayuan Chen1,2, Sijia Wang1, Xi Zhang2
1Department of Radiology, Tianjin Key Laboratory of Functional Imaging and Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
Schizophrenia Bulletin
|May 31, 2024
Summary
Functional connectivity (FC)-based searchlight multivariate pattern analysis (CBS-MVPA) effectively distinguishes schizophrenia patients from healthy individuals. This method also predicts clinical variables, offering insights into schizophrenia
Area of Science:
- Neuroscience
- Psychiatry
- Medical Imaging
Background:
- Schizophrenia is a complex disorder marked by functional dysconnectivity.
- Identifying brain network abnormalities is crucial for understanding schizophrenia.
- Existing methods face challenges in clinical practice.
Purpose of the Study:
- To investigate the efficacy of functional connectivity (FC)-based searchlight multivariate pattern analysis (CBS-MVPA) in discriminating schizophrenia patients from healthy controls.
- To explore the potential of CBS-MVPA in predicting clinical variables in schizophrenia.
- To identify specific brain subnetworks associated with schizophrenia.
Main Methods:
- Recruited 112 schizophrenia patients and 119 healthy controls.
- Acquired resting-state functional magnetic resonance imaging (fMRI) data.
- Constructed whole-brain FC subnetworks and applied CBS-MVPA.
Main Results:
- CBS-MVPA identified 63 subnetworks with high classification accuracy (62.2%-75.6%) between groups.
- Five specific subnetworks demonstrated predictive capabilities for clinical variables.
- These subnetworks involve regions like the dorsolateral superior frontal gyrus and hippocampus.
Conclusions:
- CBS-MVPA is a valuable tool for localizing schizophrenia-related information in brain networks.
- The method captures relationships between network abnormalities and clinical variables.
- This deepens the understanding of schizophrenia's neurological mechanisms.
