Bernstein Center for Computational Neuroscience Berlin Berlin, Germany ; Department of German Language and Linguistics, Humboldt-Universität zu Berlin Berlin, Germany.
Front Comput Neurosci. 2013 Jan 4;6:100. doi: 10.3389/fncom.2012.00100. eCollection 2012.
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 three-compartment 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 (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) 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. (2008), and conclude that our biophysically motivated approach yields substantial improvement.
我们提出了一种生物物理方法，用于将源自皮质锥体神经元适当偶极电流的神经网络活动与细胞外液中的电场耦合。从单个锥体神经元的简化三隔间模型出发，我们推导出了细胞外空间树突偶极电流的观测模型，从而推导出了对神经元群体局部场电位 (LFP) 有贡献的树突场电位 (DFP)。这项工作符合并满足了广泛的偶极假设，该假设是由 DFP 在皮质锥体细胞周围的“开阔场”配置所激发的。我们的简化三隔间方案允许推导出漏电积分和放电 (LIF) 模型网络，这便于与现有的神经网络和观测模型进行比较。特别是，通过数值模拟，我们将我们的方法与 Mazzoni 等人（2008 年）的特定模型进行了比较，并得出结论，我们基于生物物理的方法可以带来实质性的改进。
