Computational analysis of genesis of ERP and ERF

描述（由申请人提供）：我们建议建立哺乳动物新皮层的数学网络模型，以阐明事件相关磁场（ERFs）和电位（ERPs）的起源。我们之前使用基于RD Traub 1991年模型的数学模型提供了豚鼠海马ERF和ERP起源的基本解释。我们建议将这项工作扩展到新皮层，以便最终帮助解释来自人脑的脑磁图（MEG）和脑电图（EEG）信号。在这个R03应用程序中，我们将把我们的项目限制在四个特定的目标上，这些目标解决了开发新皮层数学模型以解释MEG和EEG的一系列初始问题。目的1：我们将首先在Mainen模型的基础上建立新皮层主要神经元的单细胞室模型。我们的模型将基于真实的解剖数据和更新的通道动力学和分布，包括II/III和V层的锥体细胞，iv层的棘状星状细胞和III层的抑制性神经元（棘状星状细胞）。将计算跨膜电位和细胞特性（例如IV关系），并与已发表的实验数据进行比较，以验证模型。目的2：我们将计算每种细胞类型的细胞内电流分布，推断细胞对脑电信号和脑电信号的贡献。为了估计每个神经元的脑电信号和脑电信号，将在离细胞较远的地方计算每个细胞内的净电流偶极矩。我们预计脑磁图和脑电图信号将主要是由于锥体细胞的传统假设。我们的新贡献将包括对实际形状的细胞模型的当前偶极矩的定量估计。目的3：我们将确定远端和近端根尖树突、包皮周围区域和基底树突对ERF和ERP的贡献，因为它们可以很容易地用隔室模型进行评估。这将对具有重复发射和爆炸发射模式的锥体细胞进行。我们预测，对于重复放电的细胞，包皮周围区域的电流将主导MEG和EEG信号；对于爆发细胞，顶梢树突远端和近端主干区域的电流将主导，而由于其几何形状，基底树突的电流贡献相对较小。目标4：一旦我们在第一年开发和测试单细胞模型，我们将把所有细胞类型连接在一个网络中，计算丘脑皮层输入将产生的ERF和ERP到第四层，并将它们与实验波形进行比较。

DESCRIPTION (provided by applicant): We propose to develop mathematical network models of the mammalian neocortex in order to elucidate the genesis of event-related magnetic fields (ERFs) and electrical potentials (ERPs). We have previously provided a fundamental account of the genesis of ERF and ERP for the guinea pig hippocampus using a mathematical model based on RD Traub's 1991 model. We are proposing to extend this work to the neocortex in order to eventually help interpret magnetoencephalography (MEG) and electroencephalography (EEG) signals from the human brain. In this R03 application, we will limit our project to four specific aims that address a set of initial problems in developing mathematical models of the neocortex for interpretation of MEG and EEG. Aim1: We will first develop single-cell compartment models of the principal neurons of the neocortex based on Mainen's model. Our models will consist of the pyramidal cells in layers II/III and layer V, the spiny stellate cells in layer IIV and the inhibitory neurons (aspiny stellate cells) in layer III, based on real anatomical data and updated channel kinetics and distributions. The transmembrane potentials and cell properties (e.g. IV relation) will be 'computed and compared with published experimental data to validate the models. Aim 2: We will compute the intracellular current distribution in each cell type to infer the contributions of cells to MEG and EEG signal. The net current dipole moment in each cell will be computed at distances far from the cells in order to estimate the MEG and EEG signals per single neurons. We expect that the MEG and EEG signal will be primarily due to the pyramidal cells as conventionally assumed. Our new contribution will consist of quantitative estimates of the current dipole moments for realistically shaped cell models. Aim 3: We will determine the contributions of the distal and proximal apical dendrites, the perisomal region and basal dendrites to the ERF and ERP since they can be readily assessed with compartment models. This will be done for pyramidal cells with repetitive firing and bursting mode of firing. We predict that the currents in the perisomal region will dominate MEG and EEG signals for cells with repetitive firing and the currents in the distal as well as proximal trunk area of the apical dendrites to dominate for bursting cells, while the basal dendrites will have relatively small contributions due to their geometry. Aim 4: Once we develop and test single cell models in year 1, we will connect all cell types in a network, compute the ERF and ERP that would be produced by thalamocortical inputs into layer IV, and compare them with experimental waveforms.