Dynamic Inter-Modality Source Coupling Reveals Sex Differences in Brain Connectivity in Children: A Multimodal MRI Study of the ABCD Dataset.

In this study, we introduce Dynamic Inter-Modality Source Coupling (dIMSC), an extension of our earlier Inter-Modality Source Coupling (IMSC) method. While IMSC evaluated the coupling between source-based morphometry (SBM) from structural MRI (sMRI) and static functional network connectivity (sFNC) from resting-state fMRI (rs-fMRI), dIMSC incorporates the temporal dimension by linking SBM with dynamic functional network connectivity (dFNC). Using data from the Adolescent Brain Cognitive Development (ABCD) study, we applied dIMSC to examine brain connectivity and evaluate sex differences in children aged 9-11. Our analysis revealed significant sex-specific patterns: males exhibited stronger positive coupling in the putamen and hippocampus, while females showed stronger coupling in the superior parietal lobule and anterior cingulate cortex. On average, 27.12% of timecourses exhibited positive coupling, 46.63% neutral coupling, and 26.25% negative coupling, reflecting a balanced alignment between structural and functional features. Sex differences were also observed in neutral and negative coupling groups, with males demonstrating stronger coupling in the caudate and middle cingulate gyrus, and females in the cerebellum and inferior parietal lobule. These findings suggest distinct developmental trajectories in brain network organization between sexes, potentially reflecting sex-specific adaptations in functional integration and compensatory mechanisms. The dIMSC method advances our earlier work by enabling time-sensitive analysis of brain structure-function coupling, providing a powerful framework for investigating neurodevelopmental processes and their implications for cognitive and behavioral outcomes.Clinical RelevanceThis study identifies sex-specific patterns in brain connectivity during childhood, offering insights that could inform sex-tailored diagnostic and therapeutic approaches for neurodevelopmental disorders.