Latent Brain State-Guided Mixture-of-Experts for EEG-to-fMRI Reconstruction

Translating electroencephalography (EEG) into functional magnetic resonance imaging (fMRI) signals could enable region-resolved estimation of blood-oxygen-level-dependent (BOLD) dynamics and functional connectivity using only EEG at inference, without costly fMRI acquisition. However, this mapping is challenging because neurovascular coupling is temporally delayed and varies across brain regions, while existing approaches often fail to separate shared hemodynamic dynamics from region-specific decoding. To address this challenge, we propose Latent Brain State-Guided Mixture-of-Experts (**E2fMoE**), inspired by neurovascular coupling in which neural activity gives rise to delayed, region-dependent BOLD responses. Accordingly, E2fMoE performs shared-state inference before regional decoding. Specifically, a state-space mixer transforms EEG tokens into slowly evolving latent representations, while region-of-interest (ROI) queries extract region-specific information and route it through shared and specialized experts. Residual prediction and low-rank connectivity-aware calibration further refine reconstruction. Extensive experiments across four simultaneous EEG-fMRI datasets show that E2fMoE outperforms representative EEG representation models and EEG-to-fMRI baselines in temporal reconstruction and functional-connectivity preservation. Code is available in the supplementary material.