We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced threecompartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential that contributes to the local field potential of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the dendritic field potential around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. [Mazzoni, A., S. Panzeri, N. K. Logothetis, and N. Brunel (2008). Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons. PLoS Computational Biology 4 (12), e1000239], and conclude that our biophysically motivated approach yields substantial improvement.
翻译:我们提出了一种生物物理方法,用于将神经网络活动结合到细胞外液体中的电场中。我们从一个单一金字塔神经元的减少三分组合模型开始,从一个单金字塔神经元的减少的三分组合模型开始,为外细胞空间中的登地极极极极极极极极极极极极极极极流,从而为有助于神经群潜力的局部领域潜力的登地极地潜力,提出了一种生物物理方法的观察模型。这项工作与广泛的地极地假设相一致,并满足了这种假设的动因是圆形金字塔细胞的“露地”组合。我们减少的三种组合计划使得能够产生一个渗漏的集成与火模型的网络,便于与现有的神经网络和观测模型进行比较。特别是通过数字模拟,我们将我们的方法与Mazzononi等人[Mazzoni, A., S. Panzeri, N. K. Logoettiti, N. Brunel(2008年),通过地方领域潜在的光场光场光场光场光场改进网络对自然和抑制进行自然学研究,并进行磁质实验性研究,并进行测试。