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基于三神经元系统前馈抑制网络的神经血管耦合中近红外光谱(NIRS)与血氧水平依赖(BOLD)信号的计算分析

Computational analysis of NIRS and BOLD signal from neurovascular coupling with three neuron-system feedforward inhibition network.

作者信息

Bandyopadhyay Anirban, Sharma Gaurav, Roy Chowdhury Shubhajit

机构信息

Biomedical Systems Laboratory, Multimedia Analytics, Networks and Systems Group, Indian Institute of Technology Mandi, India.

出版信息

J Theor Biol. 2020 Aug 7;498:110297. doi: 10.1016/j.jtbi.2020.110297. Epub 2020 May 1.

Abstract

Several neurological disorders occur due to hypoxic condition in brain arising from impairment of cerebral functionality, which can be controlled by neural stimulation driven vasoactive response mediated through biological response in astrocyte, a phenomenon known as neurovascular coupling. Brain can adjust with the problem of hypoxic condition by causing vasodilation with the help of this mechanism. To deduce the mechanism behind vasodilation of blood vessel caused by neuronal stimulus, current study articulates a mathematical model involving neuronal system feedforward inhibition network model (FFI) with two other functional components of neurovascular coupling, i.e. astrocyte and smooth muscle cell lining blood vessel. This study includes the neural inhibition network system where glutamatergic pyramidal neuron and GABAergic interneuron act antagonistically with each other. The proposed model successfully includes the implication of the inhibition system to design mathematical model for neurovascular coupling. Result of the proposed model shows that the increase in neuronal stimulus from 20 to 60 µA/cm has the ability to increase the vasodilatory activity of blood tissue vasculature. Oxygenation level and hemodynamic response due to input synaptic stimulation has been calculated by regional cerebral oxygenation level (rS0) and blood oxygen level dependent (BOLD) imaging signal which supports vasodilation of blood vessel with increase in synaptic input stimulus.

摘要

由于大脑功能受损导致的缺氧状况会引发多种神经疾病,而这种状况可通过神经刺激驱动的血管活性反应来控制,该反应由星形胶质细胞中的生物反应介导,这一现象被称为神经血管耦合。大脑可借助这一机制通过引起血管舒张来调节缺氧问题。为推断神经元刺激导致血管舒张背后的机制,当前研究阐述了一个数学模型,该模型涉及神经元系统前馈抑制网络模型(FFI)以及神经血管耦合的其他两个功能组件,即星形胶质细胞和血管内壁的平滑肌细胞。这项研究包括神经抑制网络系统,其中谷氨酸能锥体神经元和γ-氨基丁酸能中间神经元相互拮抗。所提出的模型成功纳入了抑制系统的影响,以设计神经血管耦合的数学模型。所提出模型的结果表明,神经元刺激从20微安/平方厘米增加到60微安/平方厘米有能力增强血液组织血管系统的血管舒张活性。通过局部脑氧合水平(rS0)和血氧水平依赖(BOLD)成像信号计算了由于输入突触刺激引起的氧合水平和血流动力学反应,这支持了随着突触输入刺激增加血管的舒张。

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