Macroscopic neural mass model constructed from a current-based network model of spiking neurons
Macroscopic neural mass model constructed from a current-based network model of spiking neurons
复制标题
从基于电流的尖峰神经元网络模型构建的宏观神经质量模型
DOI：
10.1007/s00422-017-0710-5
复制
发表时间：
2017
影响因子：
1.9
通讯作者：
梅原広明，岡田真人，寺前順之介，成瀬康
中科院分区：
文献类型：
--
作者：
木村周平;佐藤昌直, 岡田眞里子;梅原広明，岡田真人，寺前順之介，成瀬康
神经质量模型 (NMM) 是描述宏观皮质动力学（包括脑电图和脑磁图信号）的有效框架。最初，这些模型是在具有相对较长时间常数的突触动力学的经验基础上制定的。通过阐明NMM与神经元、突触等微观结构动力学之间的关系，我们可以从多尺度的角度更好地理解皮质和神经机制。在之前的一项研究中，NMM 是通过对群体中神经元的突触动力学方程进行平均并进一步对膜电位动力学方程进行平均来分析得出的。然而，突触电流的平均假设神经元膜电位几乎不随时间变化，并且它们保持在亚阈值水平以保留基于电导的模型。该近似将 NMM 限制为非发射状态。在本研究中，我们新提出了一种 NMM 的推导方法，即通过交替逼近假设与膜电位无关的突触电流，从而采用基于电流的模型。我们提出的模型释放了几乎恒定的膜电位的约束。我们确认，在非放电情况下，所获得的模型可简化为先前的模型，并且它再现了尖峰神经元的平均膜电位的时间平均值和相对功率谱密度。进一步确保现有的 NMM 能够正确模拟单个神经元的平均动态，即使它们在群体中出现尖峰。
Neural mass models (NMMs) are efficient frameworks for describing macroscopic cortical dynamics including electroencephalogram and magnetoencephalogram signals. Originally, these models were formulated on an empirical basis of synaptic dynamics with relatively long time constants. By clarifying the relations between NMMs and the dynamics of microscopic structures such as neurons and synapses, we can better understand cortical and neural mechanisms from a multi-scale perspective. In a previous study, the NMMs were analytically derived by averaging the equations of synaptic dynamics over the neurons in the population and further averaging the equations of the membrane-potential dynamics. However, the averaging of synaptic current assumes that the neuron membrane potentials are nearly time invariant and that they remain at sub-threshold levels to retain the conductance-based model. This approximation limits the NMM to the non-firing state. In the present study, we newly propose a derivation of a NMM by alternatively approximating the synaptic current which is assumed to be independent of the membrane potential, thus adopting a current-based model. Our proposed model releases the constraint of the nearly constant membrane potential. We confirm that the obtained model is reducible to the previous model in the non-firing situation and that it reproduces the temporal mean values and relative power spectrum densities of the average membrane potentials for the spiking neurons. It is further ensured that the existing NMM properly models the averaged dynamics over individual neurons even if they are spiking in the populations.