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A unified statistical model for the human electrocorticogram.

Authors :
Kalamangalam GP
Chelaru MI
Slater JD
Source :
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology [Clin Neurophysiol] 2016 Dec; Vol. 127 (12), pp. 3564-3573. Date of Electronic Publication: 2016 Jul 05.
Publication Year :
2016

Abstract

Objective: Extracellular field potentials (ECFs) generated in the cerebral cortex span a vast range of spatiotemporal scales. The process(es) leading to this large dynamic range remain debatable. Here we propose a novel statistical description of the amplitude spectrum of the human electrocorticogram (ECoG).<br />Methods: Spectral analysis was performed on long-term recordings from epilepsy patients undergoing pre-surgical evaluation with intracranial electrodes. Amplitude spectra were fit with a multi-component Gaussian model on semi-logarithmic axes.<br />Results: The Gaussian formulation provided excellent fits to the data. It also suggested how the changes accompanying the sleep-wake cycle and certain epileptiform transitions could be understood by variation in the parameters of the model.<br />Conclusions: The proposed continuum model synthesizes several previous observations regarding the statistical structure of the resting human ECoG. It offers a conceptual platform for understanding the EEG changes accompanying the sleep-wake cycle and pathologically hypersynchronous behaviour.<br />Significance: Statistical characterisation of the spectral distribution of field potentials yield insight into the cortico-cortical interactions that underlie the summated cortical ECFs comprising the ECoG. Such insight is relevant for a synoptic understanding of major state changes in the brain that are diagnosed in clinical practice by visual inspection of the ECoG.<br /> (Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1872-8952
Volume :
127
Issue :
12
Database :
MEDLINE
Journal :
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Publication Type :
Academic Journal
Accession number :
27449472
Full Text :
https://doi.org/10.1016/j.clinph.2016.06.027