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Spatiotemporal scales and links between electrical neuroimaging modalities

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Abstract

Recordings of brain electrophysiological activity provide the most direct reflect of neural function. Information contained in these signals varies as a function of the spatial scale at which recordings are done: from single cell recording to large scale macroscopic fields, e.g., scalp EEG. Microscopic and macroscopic measurements and models in Neuroscience are often in conflict. Solving this conflict might require the developments of a sort of bio-statistical physics, a framework for relating the microscopic properties of individual cells to the macroscopic or bulk properties of neural circuits. Such a framework can only emerge in Neuroscience from the systematic analysis and modeling of the diverse recording scales from simultaneous measurements. In this article we briefly review the different measurement scales and models in modern neuroscience to try to identify the sources of conflict that might ultimately help to create a unified theory of brain electromagnetic fields. We argue that seen the different recording scales, from the single cell to the large scale fields measured by the scalp electroencephalogram, as derived from a unique physical magnitude—the electric potential that is measured in all cases—might help to conciliate microscopic and macroscopic models of neural function as well as the animal and human neuroscience literature.

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Acknowledgments

We thank Prof. Fivos Panetsos, Laboratory of Neurocomputing and Neurorobotics, Complutense University of Madrid, Spain for graciously providing the data shown in Fig. 2. This study has been supported by the 3R Research Foundation, Switzerland, under Grant number 119-10. We thank two anonymous reviewers for their detailed comments that contributed to improve earlier versions of this manuscript.

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Correspondence to Sara L. Gonzalez Andino.

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Gonzalez Andino, S.L., Perrig, S. & Grave de Peralta Menendez, R. Spatiotemporal scales and links between electrical neuroimaging modalities. Med Biol Eng Comput 49, 511–520 (2011). https://doi.org/10.1007/s11517-011-0769-4

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