Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-07-19
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG) signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary.
Therefore, spectral analysis of EEG may miss many properties inherent in such signals.
A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics.
In recent work by Fielitz and Borchardt (2011, 2014), the concept of information equilibrium (IE) in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium.
We utilized a publicly available database of polysomnogram EEG data from fourteen subjects with eight different one-minute tracings of sleep stage 2 and waking and an overlapping set of eleven subjects with eight different one-minute tracings of sleep stage 3.
We applied principles of IE to model EEG as a system that transfers (equilibrates) information from the time domain to scalp-recorded voltages.
We find that waking consciousness is readily distinguished from sleep stages 2 and 3 by several differences in mean information transfer constants.
Principles of IE applied to EEG may therefore prove to be useful in the study of changes in brain function more generally.
American Psychological Association (APA)
Zorick, Todd& Smith, Jason. 2016. Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100165
Modern Language Association (MLA)
Zorick, Todd& Smith, Jason. Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1100165
American Medical Association (AMA)
Zorick, Todd& Smith, Jason. Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100165
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100165