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通过生成式全脑建模研究神经退行性变中低兴奋性和结构解体相关的粘性动力学。

Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole-brain modeling.

机构信息

Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Peñalolén, Santiago, Chile.

Global Brain Health Institute (GBHI), University of California San Francisco (UCSFA), San Francisco, California, USA.

出版信息

Alzheimers Dement. 2024 May;20(5):3228-3250. doi: 10.1002/alz.13788. Epub 2024 Mar 19.

Abstract

INTRODUCTION

Alzheimer'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.

METHODS

We 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).

RESULTS

Metaconnectivity 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.

DISCUSSION

The results provide a novel agenda for developing mechanistic model-inspired characterization and therapies in clinical, translational, and computational neuroscience settings.

摘要

简介

阿尔茨海默病(AD)和行为变异额颞叶痴呆(bvFTD)在不同的代表性不足的人群中缺乏机械生物物理建模。脑电图(EEG)是一种具有高时间分辨率、成本效益的全球痴呆研究技术,但缺乏机械模型并产生不可复制的结果。

方法

我们开发了一种生成性全脑模型,该模型结合了 EEG 源水平的元连接、解剖先验和扰动方法。该模型应用于全球南方参与者(AD、bvFTD 和健康对照组)。

结果

元连接性优于成对连接性,并在患者中显示出更粘滞的动力学,改变的元连接模式与多模态疾病表现相关。生物物理模型表明,连接组解整合和兴奋性降低引发了改变的元连接动力学,并确定了用于脑刺激的关键区域。我们在第二个参与者子集的验证中复制了主要结果,这些结果使用未协调的、异构的记录设置。

讨论

这些结果为在临床、转化和计算神经科学环境中开发基于机械模型的特征和治疗方法提供了新的议程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f64e/11095480/dfeb58bd8133/ALZ-20-3228-g001.jpg

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