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bioRxiv · 10.64898/2026.04.10.717365

An EEG-fMRI Jointly Constrained Digital Twin Brain and Its Application in Alzheime's Disease

Yue, X.·Guo, D.·Xu, Y.·Chen, Y.·Zhang, R.·Luo, Y.·Wang, F.·Zeng, X.·Guo, Y.·Yao, D.
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Abstract

Current digital twin brain (DTB) models are typically optimized using single-modality functional neuroimaging data, which restricts their ability to simulate brain dynamics across multiple spatiotemporal scales. Here, we bridged this gap by developing a two-stage DTB (TS-DTB) modeling framework jointly constrained by functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data. Validation in both the healthy young and Alzheimers disease (AD) cohorts demonstrated that the TS-DTB model simultaneously captures subject-specific features of multi-scale brain dynamics. In particular, the TS-DTB models of AD patients successfully recapitulated spectral-temporal signatures of cognitive decline, mechanistically linking these deficits to excitation-inhibition (E-I) imbalances. By simulating responses to repetitive transcranial magnetic stimulation (rTMS), we further revealed that cognitive recovery in AD patients can be driven by E-I rebalancing via synaptic reconfiguration and background suppression. Overall, these findings underscore the potential of the TS-DTB to advance the mechanistic understanding of the brain and inform personalized digital therapeutics.

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Yue, X., Guo, D., Xu, Y., Chen, Y., Zhang, R., Luo, Y., Wang, F., Zeng, X., Guo, Y., Yao, D.. 2026-04-14. An EEG-fMRI Jointly Constrained Digital Twin Brain and Its Application in Alzheime's Disease. https://doi.org/10.64898/2026.04.10.717365

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