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Estimating microscopic biophysical information from macroscopic neuroimaging data via the inversion of neural-glial mass models

通过神经胶质细胞模型的反演从宏观神经影像数据估计微观生物物理信息

基本信息

批准号：
RGPIN-2015-05966
负责人：
SoteroDiaz, Roberto
金额：
$ 2.33万
依托单位：
University of Calgary
依托单位国家：
加拿大
项目类别：
Discovery Grants Program - Individual
财政年份：
2019
资助国家：
加拿大
起止时间：
2019-01-01 至 2020-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=684266
关键词：
Estimating microscopic biophysical information macroscopic

项目摘要

Progress in the neuroimaging field in recent years has made it possible to create maps of hemodynamic-based and electrophysiology-based functional connectivity, as well as diffusion MRI-based structural connectivity maps. However, a major challenge we face is not only the reproduction of realistic brain connectivity and dynamics, but also the identification of important features and mechanism of these dynamics and of the network structure that are critical to brain function. The broad goal of this research program is the development of large-scale theoretical brain models to bridge the gap between structure and function in the brain, and identify key network properties underlying the empirically observed dynamics. More specifically, this proposal is focused on the development of a macroscopic generative model of brain activity built from multiple interconnected neural-glial mass models (NGMMs), which will bridge the microscopic and macroscopic spatial scales in the brain. Thus, by estimating this model from macroscopic data we can infer microscopic data such as excitatory and inhibitory synaptic activity, which is indispensable for understanding the mechanism underlying brain information processing.**

近年来神经成像领域的进步使得创建基于血流动力学和电生理学的功能连接图以及基于弥散磁共振成像的结构连接图成为可能。然而，我们面临的一个主要挑战不仅是再现真实的大脑连通性和动力学，而且还需要识别这些动力学的重要特征和机制，以及对大脑功能至关重要的网络结构。这项研究计划的广泛目标是发展大规模的理论大脑模型，以弥合大脑结构和功能之间的差距，并确定经验观察到的动力学背后的关键网络属性。更具体地说，这项提议的重点是开发一个宏观的大脑活动生成模型，该模型由多个相互关联的神经胶质质量模型(NGMM)建立，将在大脑的微观和宏观空间尺度上架起桥梁。因此，通过从宏观数据估计这个模型，我们可以推断微观数据，如兴奋性和抑制性突触活动，这对于理解大脑信息处理的机制是不可或缺的。