大脑皮层瞬时氧输送模型。

Frontiers in neuroenergetics Pub Date : 2009-06-29 eCollection Date: 2009-01-01 DOI:10.3389/neuro.14.003.2009
David Ress, Jeffrey K Thompson, Bas Rokers, Reswanul K Khan, Alexander C Huk
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引用次数: 26

摘要

流行的血流动力学脑成像方法,如血氧水平依赖功能磁共振成像(BOLD fMRI),将受益于对氧气在短时间神经活动中被输送到皮层的机制的详细了解。在短暂的视觉刺激后,视觉皮层的组织氧反应表现出丰富的动态,包括早期氧浓度下降,随后浓度大幅增加,以及大量的后期振荡(“振铃”)。我们引入了一个模型来解释汤普森等人(2003)所做的这些观察的全部时间过程。该模型用一组微分方程来处理氧运输,其中包括三室(血管内、血管外和细胞内)系统中的流动和扩散的组合。该系统中的血流使用包含惯性元素的集总线性系统的脉冲响应建模;这为耳鸣提供了一个简单的生物物理机制。对模型系统进行了数值求解,以获得与组织氧测量的良好拟合。这些结果有助于深入了解脑氧传递的动态,并可作为理解BOLD fMRI测量的起点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A model for transient oxygen delivery in cerebral cortex.

A model for transient oxygen delivery in cerebral cortex.

A model for transient oxygen delivery in cerebral cortex.

A model for transient oxygen delivery in cerebral cortex.

Popular hemodynamic brain imaging methods, such as blood oxygen-level dependent functional magnetic resonance imaging (BOLD fMRI), would benefit from a detailed understanding of the mechanisms by which oxygen is delivered to the cortex in response to brief periods of neural activity. Tissue oxygen responses in visual cortex following brief visual stimulation exhibit rich dynamics, including an early decrease in oxygen concentration, a subsequent large increase in concentration, and substantial late-time oscillations ("ringing"). We introduce a model that explains the full time-course of these observations made by Thompson et al. (2003). The model treats oxygen transport with a set of differential equations that include a combination of flow and diffusion in a three-compartment (intravascular, extravascular, and intracellular) system. Blood flow in this system is modeled using the impulse response of a lumped linear system that includes an inertive element; this provides a simple biophysical mechanism for the ringing. The model system is solved numerically to produce excellent fits to measurements of tissue oxygen. The results give insight into the dynamics of cerebral oxygen transfer, and can serve as the starting point to understand BOLD fMRI measurements.

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