KOCOBrain: Kuramoto-Guided Graph Network for Uncovering Structure-Function Coupling in Adolescent Prenatal Drug Exposure
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Abstract (arXiv)
Exposure to psychoactive substances during pregnancy, such as cannabis, can disrupt neurodevelopment and alter large-scale 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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 10 of its 26 references that are in the map. First posted on arXiv 16 Jan 2026.
Builds on
10 of 26 references.
References · 10
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Citing papers per year: 2026: 2.
2 papers.
- 2026NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance Use Initiation Prediction from Longitudinal Functional Connectomecited by 0
- 2026Learning Structural-Functional Brain Representations through Multi-Scale Adaptive Graph Attention for Cognitive Insightcited by 0
- 2026Learning Structural-Functional Brain Representations through Multi-Scale Adaptive Graph Attention for Cognitive Insight31 Mar 2026
- 2026NeuroBRIDGE: Behavior-Conditioned Koopman Dynamics with Riemannian Alignment for Early Substance Use Initiation Prediction from Longitudinal Functional Connectome31 Mar 2026