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一个大胶质层在脑血管循环中不可或缺性的模型。

A model of indispensability of a large glial layer in cerebrovascular circulation.

机构信息

Department of Biotechnology, Indian Institute of Technology, Madras, Chennai, India.

出版信息

Neural Comput. 2010 Apr;22(4):949-68. doi: 10.1162/neco.2009.01-09-945.

Abstract

We formulate the problem of oxygen delivery to neural tissue as a problem of association. Input to a pool of neurons in one brain area must be matched in space and time with metabolic inputs from the vascular network via the glial network. We thus have a model in which neural, glial, and vascular layers are connected bidirectionally, in that order. Connections between neuro-glial and glial-vascular stages are trained by an unsupervised learning mechanism such that input to the neural layer is sustained by the precisely patterned delivery of metabolic inputs from the vascular layer via the glial layer. Simulations show that the capacity of such a system to sustain patterns is weak when the glial layer is absent. Capacity is higher when a glial layer is present and increases with the layer size. The proposed formulation of neurovascular interactions raises many intriguing questions about the role of glial cells in cerebral circulation.

摘要

我们将向神经组织输送氧气的问题表述为一个关联问题。一个大脑区域内的神经元池的输入必须在空间和时间上与血管网络的代谢输入通过神经胶质网络相匹配。因此,我们有一个模型,其中神经、神经胶质和血管层以这种顺序双向连接。神经胶质-血管阶段和血管胶质-神经阶段之间的连接是通过无监督学习机制进行训练的,使得来自血管层的代谢输入通过神经胶质层精确地输送到神经层,从而维持神经层的输入。模拟结果表明,当神经胶质层不存在时,该系统维持模式的能力较弱。当存在神经胶质层时,容量更高,并且随着层的大小增加而增加。神经血管相互作用的这种表述提出了许多关于神经胶质细胞在脑循环中的作用的有趣问题。

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