Structural co-modulation: An individualized measure of inter-component interactions in source-based morphometry

Area of Science:

• Neuroimaging
• Brain network analysis
• Structural MRI

Background:

• Source-based morphometry (SBM) identifies covarying structural brain networks.
• Standard SBM has limitations in characterizing inter-network relationships at the individual level.

Purpose of the Study:

• To introduce a novel co-modulation approach for individualized structural brain organization.
• To create a subject-specific, network-like measure of structural brain organization.
• To overcome limitations of standard SBM in characterizing inter-network relationships.

Main Methods:

• Developed a co-modulation approach transforming SBM loading vectors into symmetric matrices.
• Computed outer products of subject-specific SBM loading vectors.
• Applied the method to structural MRI data from schizophrenia patients and healthy controls.

Main Results:

• Observed widespread reductions in structural co-modulation in the schizophrenia group.
• Identified significant co-modulation alterations within and between visual, default-mode, and cognitive control networks.
• Found correlations between co-modulation patterns, cognitive performance, and clinical symptom severity in schizophrenia patients.

Conclusions:

• Structural co-modulation offers a robust framework for quantifying individualized structural brain relationships.
• This method enhances the characterization of structural brain organization beyond standard SBM.
• Provides a new avenue for integrating structural and functional brain analyses.