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Spatiotemporal Scales and Links Between Electrical Neuroimaging Modalities

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Publisher Springer
Date 2011 Apr 13
PMID 21484504
Citations 3
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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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References
1.
Schultz W . Dopamine signals for reward value and risk: basic and recent data. Behav Brain Funct. 2010; 6:24. PMC: 2876988. DOI: 10.1186/1744-9081-6-24. View

2.
Averbeck B, Lee D . Coding and transmission of information by neural ensembles. Trends Neurosci. 2004; 27(4):225-30. DOI: 10.1016/j.tins.2004.02.006. View

3.
Lachaux J, Rudrauf D, Kahane P . Intracranial EEG and human brain mapping. J Physiol Paris. 2004; 97(4-6):613-28. DOI: 10.1016/j.jphysparis.2004.01.018. View

4.
Nunez P, Srinivasan R . A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness. Clin Neurophysiol. 2006; 117(11):2424-35. PMC: 1991284. DOI: 10.1016/j.clinph.2006.06.754. View

5.
Weiss S, Faber D . Field effects in the CNS play functional roles. Front Neural Circuits. 2010; 4:15. PMC: 2876880. DOI: 10.3389/fncir.2010.00015. View