Nunez Paul L, Nunez Michael D, Srinivasan Ramesh
Cognitive Dissonance LLC, 1726 Sienna Canyon Drive, Encinitas, CA, 92024, USA.
Department of Cognitive Science, University of California at Irvine, Irvine, CA, 92617, USA.
Brain Topogr. 2019 Mar;32(2):193-214. doi: 10.1007/s10548-019-00701-3. Epub 2019 Jan 25.
A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuine sources occur at the micro scale of cell surfaces. Equivalent sources provide identical experimental outcomes over a range of scales and applications. In contrast, each representative source distribution is just one of many possible source distributions that yield similar experimental outcomes. Macro sources ("dipoles") may be defined at the macrocolumn (mm) scale and depend on several features of the micro sources-magnitudes, micro synchrony within columns, and distribution through the cortical depths. These micro source properties are determined by brain dynamics and the columnar structure of cortical tissue. The number of representative sources underlying EEG data depends on the spatial scale of neural tissue under study. EEG inverse solutions (e.g. dipole localization) and high resolution estimates (e.g. Laplacian, dura imaging) have both strengths and limitations that depend on experimental conditions. The proposed theoretical framework informs studies of EEG source localization, source characterization, and low pass filtering. It also facilitates interpretations of brain dynamics and cognition, including measures of synchrony, functional connections between cortical locations, and other aspects of brain complexity.
我们建立了一个生物物理框架，用于解释在脑组织的多个空间尺度上记录的电生理数据。膜表面的微电流源产生局部场电位、皮层脑电图和脑电图（EEG）。我们将多尺度源分为真实源、等效源或代表性源。真实源出现在细胞表面的微观尺度上。等效源在一系列尺度和应用中提供相同的实验结果。相比之下，每个代表性源分布只是产生相似实验结果的众多可能源分布之一。宏观源（“偶极子”）可以在宏观柱（毫米）尺度上定义，并取决于微源的几个特征——幅度、柱内的微同步以及通过皮层深度的分布。这些微源特性由脑动力学和皮层组织的柱状结构决定。脑电图数据背后的代表性源数量取决于所研究神经组织的空间尺度。脑电图逆解（例如偶极子定位）和高分辨率估计（例如拉普拉斯、硬脑膜成像）都有取决于实验条件的优点和局限性。所提出的理论框架为脑电图源定位、源特征描述和低通滤波的研究提供了信息。它还有助于对脑动力学和认知的解释，包括同步性测量、皮层位置之间的功能连接以及脑复杂性的其他方面。
