Tenke C E, Schroeder C E, Arezzo J C, Vaughan H G
Department of Biopsychology, NYS Psychiatric Institute, New York 10032.
Exp Brain Res. 1993;94(2):183-92. doi: 10.1007/BF00230286.
Current source density (CSD) analysis provides an index of the location, direction, and density of transmembrane currents that arise with synchronous activation of neural tissue and that generate an evoked potential profile in the extracellular medium. In neocortex and other laminated structures, a simplified, one-dimensional CSD analysis can be computed by differentiation of voltages sampled at discrete points in a linear array. One-dimensional CSD analysis is a practical and accurate method for defining both regional activity patterns and neural generators of surface-recorded evoked and event-related potentials. In computing the CSD, common practices of differentiating across spatial grids of 200 microns or more and use of spatial smoothing routines help to reduce noise, but severely limit the spatial resolution available to the analysis. High-resolution CSD procedures (i.e., 3 point differentiation using a spatial grid of 100 microns or less) are more suited to identification of processes within individual cortical laminae or sublaminae, but can magnify the contributions of computational artifacts. Despite the inclusion of independent indices of cellular activity (e.g., multiunit activity), both high- and low-resolution analyses may indicate current source and sink configurations for which there is more than one plausible physiological interpretation. In the present study we examined the resolving capacity and pitfalls of common CSD procedures using simulated ensembles of current dipoles. These were positioned and oriented to model the depolarization of lamina 4C stellate cells and thalamocortical afferents in macaque striate cortex. Empirically, the surface N40 appears in association with a CSD configuration which includes current sinks within the thalamorecipient (stellate) subdivisions of lamina 4C and a large current source extending considerably below 4C. Dipole ensemble contributions to the CSD profile were computed and compared to physiological data from this region. Small asymmetries in activation of model stellate laminae were sufficient to produce substantial open field contributions. However, the best fit with empirical CSD profile was found when the simulation included contributions from thalamocortical axons, along with both open and closed field contributions from dual stellate cell sublaminae. High-resolution CSD profiles were shown to be interpretable when computational artifacts characteristic of closed and open fields were identified using a series of differentiation grids.
电流源密度（CSD）分析提供了跨膜电流的位置、方向和密度的指标，这些跨膜电流由神经组织的同步激活产生，并在细胞外介质中生成诱发电位分布。在新皮层和其他分层结构中，可以通过对线性阵列中离散点采样的电压进行微分来计算简化的一维CSD分析。一维CSD分析是一种实用且准确的方法，用于定义区域活动模式以及表面记录的诱发电位和事件相关电位的神经发生器。在计算CSD时，跨越200微米或更大空间网格进行微分以及使用空间平滑程序的常见做法有助于减少噪声，但会严重限制分析可用的空间分辨率。高分辨率CSD程序（即使用100微米或更小的空间网格进行三点微分）更适合识别单个皮质层或亚层内的过程，但会放大计算伪迹的贡献。尽管纳入了细胞活动的独立指标（例如，多单位活动），但高分辨率和低分辨率分析都可能表明存在不止一种合理生理学解释的电流源和电流汇配置。在本研究中，我们使用模拟的电流偶极子集合研究了常见CSD程序的分辨能力和缺陷。这些电流偶极子的位置和方向被设定为模拟猕猴纹状皮层中第4C层星状细胞和丘脑皮质传入纤维的去极化。根据经验，表面N40的出现与一种CSD配置相关，该配置包括第4C层丘脑接受区（星状）亚区内的电流汇以及一个在4C层下方相当深处延伸的大电流源。计算了偶极子集合对CSD分布的贡献，并与该区域的生理数据进行了比较。模型星状层激活中的小不对称足以产生大量的开放场贡献。然而，当模拟包括丘脑皮质轴突的贡献以及双星状细胞亚层的开放场和封闭场贡献时，发现与经验CSD分布的最佳拟合。当使用一系列微分网格识别封闭场和开放场特有的计算伪迹时，高分辨率CSD分布被证明是可解释的。
