Exploring Subnetwork Interactions in Heterogeneous Brain Network via Prior-Informed Graph Learning

The paper introduces KD-Brain, a Prior‑Informed Graph Learning framework that incorporates semantic and clinical priors to model interactions among functional subnetworks in brain networks. It employs a Semantic‑Conditioned Interaction mechanism to guide attention queries by subnetwork identities and a Pathology‑Consistent Constraint to align learned interactions with clinical priors. KD‑Brain achieves state‑of‑the‑art performance on disorder diagnosis tasks and identifies biomarkers that align with psychiatric pathophysiology.

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