INTRODUCTIONAlzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost‐effective technique for studying dementia globally, but lacks mechanistic models and produces non‐replicable results.METHODSWe developed a generative whole‐brain model that combines EEG source‐level metaconnectivity, anatomical priors, and a perturbational approach. This model was applied to Global South participants (AD, bvFTD, and healthy controls).RESULTSMetaconnectivity outperformed pairwise connectivity and revealed more viscous dynamics in patients, with altered metaconnectivity patterns associated with multimodal disease presentation. The biophysical model showed that connectome disintegration and hypoexcitability triggered altered metaconnectivity dynamics and identified critical regions for brain stimulation. We replicated the main results in a second subset of participants for validation with unharmonized, heterogeneous recording settings.DISCUSSIONThe results provide a novel agenda for developing mechanistic model‐inspired characterization and therapies in clinical, translational, and computational neuroscience settings.

中文翻译：

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通过生成全脑模型研究与神经退行性疾病中低兴奋和结构崩解相关的粘性动力学

简介阿尔茨海默病 (AD) 和行为变异型额颞叶痴呆 (bvFTD) 在不同的、代表性不足的人群中缺乏机制生物物理模型。脑电图（EEG）是一种高时间分辨率、经济有效的技术，用于全球范围内研究痴呆症，但缺乏机制模型并产生不可复制的结果。方法我们开发了一种生成全脑模型，结合了脑电图源级元连通性、解剖学先验和扰动方法。该模型适用于全球南方参与者（AD、bvFTD 和健康对照）。结果元连接性优于成对连接性，并揭示了患者中更多的粘性动态，以及与多模式疾病表现相关的元连接模式的改变。生物物理模型表明，连接组解体和兴奋性低下会引发元连接动力学的改变，并确定大脑刺激的关键区域。我们在第二组参与者中复制了主要结果，以使用不协调、异构的记录设置进行验证。讨论结果为在临床、转化和计算神经科学设置中开发机械模型启发的表征和疗法提供了一个新颖的议程。