Mathias E J, Plank M J, David T
a UC HPC , University of Canterbury , Christchurch , New Zealand .
b School of Mathematics and Statistics , University of Canterbury , Christchurch , New Zealand .
Comput Methods Biomech Biomed Engin. 2017 Apr;20(5):508-518. doi: 10.1080/10255842.2016.1255732. Epub 2016 Nov 11.
The mechanisms with which neurons communicate with the vasculature to increase blood flow, termed neurovascular coupling is still unclear primarily due to the complex interactions between many parameters and the difficulty in accessing, monitoring and measuring them in the highly heterogeneous brain. Hence a solid theoretical framework based on existing experimental knowledge is necessary to study the relation between neural activity, the associated vasoactive factors released and their effects on the vasculature. Such a framework should also be related to experimental data so that it can be validated against repetitive experiments and generate verifiable hypothesis. We have developed a mathematical model which describes a signaling mechanism of neurovascular coupling with a model of pyramidal neuron and its corresponding fMRI BOLD response. In the first part of two papers we describe the integration of the neurovascular coupling unit extended to include a complex neuron model, which includes the important Na/K ATPase pump, with a model that provides a BOLD signal taking its input from the cerebral blood flow and the metabolic rate of oxygen consumption. We show that this produces a viable signal in terms of initial dip, positive and negative BOLD signals.
神经元与脉管系统进行通信以增加血流量的机制，即所谓的神经血管耦合，目前仍不清楚，主要原因是许多参数之间存在复杂的相互作用，并且在高度异质性的大脑中获取、监测和测量这些参数存在困难。因此，基于现有实验知识构建一个坚实的理论框架对于研究神经活动、相关血管活性因子的释放及其对脉管系统的影响之间的关系是必要的。这样一个框架还应与实验数据相关，以便能够通过重复实验进行验证并生成可验证的假设。我们已经开发了一个数学模型，该模型用锥体神经元模型及其相应的功能磁共振成像血氧水平依赖（BOLD）反应来描述神经血管耦合的信号传导机制。在两篇论文的第一部分中，我们描述了扩展后的神经血管耦合单元的整合，该单元包括一个复杂的神经元模型，其中包含重要的钠钾ATP酶泵，以及一个从脑血流量和氧消耗代谢率获取输入并提供BOLD信号的模型。我们表明，就初始下降、正负BOLD信号而言，这会产生一个可行的信号。
