KOCOBrain: Kuramoto-Guided Graph Network for Uncovering Structure-Function Coupling in Adolescent Prenatal Drug Exposure
Abstract
Exposure to psychoactive substances during pregnancy, such as cannabis, can disrupt neurodevelopment and alter largescale brain networks, yet identifying their neural signatures remains challenging. We introduced KOCOBrain: KuramotO COupled Brain Graph Network; a unified graph neural network framework that integrates structural and functional connectomes via Kuramoto-based phase dynamics and cognition-aware attention. The Kuramoto layer models neural synchronization over anatomical connections, generating phase-informed embeddings that capture structure-function coupling, while cognitive scores modulate information routing in a subject-specific manner followed by a joint objective enhancing robustness under class imbalance scenario. Applied to the ABCD cohort, KOCOBrain improved prenatal drug exposure prediction over relevant baselines and revealed interpretable structure-function patterns that reflect disrupted brain network coordination associated with early exposure.
Fields of Study & Subjects
Advanced Graph Neural Networks
Bioinformatics and Genomic Networks
Topological and Geometric Data Analysis
Publication details
- Journal / source
- 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)
- Publisher
- IEEE
- Pages
- 1–5
- Publication date
- 8 April 2026