DynFS-MoE: Dynamic Functional-Structural Mixture-of-Experts for Post-Traumatic Epilepsy Diagnosis

2026-06-15

AI Summary

This study addresses the challenge of early diagnosis of post-traumatic epilepsy (PTE) following traumatic brain injury, which is hindered by complex dynamic alterations in both brain function and structure. The authors propose a dynamic multimodal mixture-of-experts framework that adaptively fuses functional and structural MRI data through a time-aware functional-structural encoder and a class-conditional expert routing mechanism. A novel Modality-Class Mixture-of-Experts (MoE) module is introduced to dynamically assign expert weights based on the classification objective, thereby capturing category-dependent patterns of brain region interactions. The method significantly outperforms static fusion baselines across three binary classification tasks. Furthermore, highly interpretable analyses reveal clinically meaningful interactions among key brain regions, offering valuable support for precise PTE diagnosis and risk stratification.

Abstract

Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI), yet early identification remains challenging due to the complex structural and functional alterations it induces in the brain. To address this, we propose a dynamic multimodal Mixture-of-Experts (MoE) framework that integrates functional and structural MRI through time-aware functional-structural encoding and class-conditioned expert routing. Within this framework, modality-specific and cross-modal experts learn complementary representations, while a Modality-Class MoE (MCoE) module dynamically dispatches expert weights according to each classification objective. Experimental results across three binary classification tasks demonstrate that the framework consistently outperforms static fusion baselines, and high-interpretability analyses further reveal meaningful region-of-interest (ROI) interactions. This dynamic multimodal expert framework effectively captures class-dependent brain interaction patterns and provides an interpretable approach for PTE diagnosis and risk stratification.

Problem

• Post-traumatic epilepsy
• Traumatic brain injury
• Early diagnosis
• Multimodal integration
• Brain alterations

Innovation

• Dynamic Mixture-of-Experts
• Multimodal Fusion
• Functional-Structural MRI
• Class-Conditioned Routing
• Interpretable Diagnosis