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Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern

An electroencephalogram (EEG) signal is extremely nonstationary, highly composite and very complex, all of which reflects the underlying integral neurodynamics. Understanding the EEG “grammar”, its internal structural organization would place a “Rozetta stone” in researchers’ hands, allowing them to...

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Detalles Bibliográficos
Autores principales: Fingelkurts, Al. A, Fingelkurts, An. A
Formato: Texto
Lenguaje:English
Publicado: Bentham Open 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3043267/
https://www.ncbi.nlm.nih.gov/pubmed/21347201
http://dx.doi.org/10.2174/1874440001004010111
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author Fingelkurts, Al. A
Fingelkurts, An. A
author_facet Fingelkurts, Al. A
Fingelkurts, An. A
author_sort Fingelkurts, Al. A
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description An electroencephalogram (EEG) signal is extremely nonstationary, highly composite and very complex, all of which reflects the underlying integral neurodynamics. Understanding the EEG “grammar”, its internal structural organization would place a “Rozetta stone” in researchers’ hands, allowing them to more adequately describe the information processes of the brain in terms of EEG phenomenology. This Special Issue presents a framework where short-term EEG spectral pattern (SP) of a particular type is viewed as an information-rich event in EEG phenomenology. It is suggested that transition from one type of SP to another is accompanied by a “switch” between brain microstates in specific neuronal networks, or in cortex areas; and these microstates are reflected in EEG as piecewise stationary segments. In this context multiple faces of a short-term EEG SP reflect the poly-operational structure of brain activity.
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spelling pubmed-30432672011-02-23 Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern Fingelkurts, Al. A Fingelkurts, An. A Open Neuroimag J Editorial An electroencephalogram (EEG) signal is extremely nonstationary, highly composite and very complex, all of which reflects the underlying integral neurodynamics. Understanding the EEG “grammar”, its internal structural organization would place a “Rozetta stone” in researchers’ hands, allowing them to more adequately describe the information processes of the brain in terms of EEG phenomenology. This Special Issue presents a framework where short-term EEG spectral pattern (SP) of a particular type is viewed as an information-rich event in EEG phenomenology. It is suggested that transition from one type of SP to another is accompanied by a “switch” between brain microstates in specific neuronal networks, or in cortex areas; and these microstates are reflected in EEG as piecewise stationary segments. In this context multiple faces of a short-term EEG SP reflect the poly-operational structure of brain activity. Bentham Open 2010-09-08 /pmc/articles/PMC3043267/ /pubmed/21347201 http://dx.doi.org/10.2174/1874440001004010111 Text en © Fingelkurts and Fingelkurts; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
spellingShingle Editorial
Fingelkurts, Al. A
Fingelkurts, An. A
Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern
title Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern
title_full Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern
title_fullStr Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern
title_full_unstemmed Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern
title_short Editorial: EEG Phenomenology and Multiple Faces of Short-term EEG Spectral Pattern
title_sort editorial: eeg phenomenology and multiple faces of short-term eeg spectral pattern
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3043267/
https://www.ncbi.nlm.nih.gov/pubmed/21347201
http://dx.doi.org/10.2174/1874440001004010111
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