Cargando…
Discrete Structure of the Brain Rhythms
Neuronal activity in the brain generates synchronous oscillations of the Local Field Potential (LFP). The traditional analyses of the LFPs are based on decomposing the signal into simpler components, such as sinusoidal harmonics. However, a common drawback of such methods is that the decomposition p...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6349927/ https://www.ncbi.nlm.nih.gov/pubmed/30692564 http://dx.doi.org/10.1038/s41598-018-37196-0 |
_version_ | 1783390351071903744 |
---|---|
author | Perotti, L. DeVito, J. Bessis, D. Dabaghian, Y. |
author_facet | Perotti, L. DeVito, J. Bessis, D. Dabaghian, Y. |
author_sort | Perotti, L. |
collection | PubMed |
description | Neuronal activity in the brain generates synchronous oscillations of the Local Field Potential (LFP). The traditional analyses of the LFPs are based on decomposing the signal into simpler components, such as sinusoidal harmonics. However, a common drawback of such methods is that the decomposition primitives are usually presumed from the onset, which may bias our understanding of the signal’s structure. Here, we introduce an alternative approach that allows an impartial, high resolution, hands-off decomposition of the brain waves into a small number of discrete, frequency-modulated oscillatory processes, which we call oscillons. In particular, we demonstrate that mouse hippocampal LFP contain a single oscillon that occupies the θ-frequency band and a couple of γ-oscillons that correspond, respectively, to slow and fast γ-waves. Since the oscillons were identified empirically, they may represent the actual, physical structure of synchronous oscillations in neuronal ensembles, whereas Fourier-defined “brain waves” are nothing but poorly resolved oscillons. |
format | Online Article Text |
id | pubmed-6349927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63499272019-01-30 Discrete Structure of the Brain Rhythms Perotti, L. DeVito, J. Bessis, D. Dabaghian, Y. Sci Rep Article Neuronal activity in the brain generates synchronous oscillations of the Local Field Potential (LFP). The traditional analyses of the LFPs are based on decomposing the signal into simpler components, such as sinusoidal harmonics. However, a common drawback of such methods is that the decomposition primitives are usually presumed from the onset, which may bias our understanding of the signal’s structure. Here, we introduce an alternative approach that allows an impartial, high resolution, hands-off decomposition of the brain waves into a small number of discrete, frequency-modulated oscillatory processes, which we call oscillons. In particular, we demonstrate that mouse hippocampal LFP contain a single oscillon that occupies the θ-frequency band and a couple of γ-oscillons that correspond, respectively, to slow and fast γ-waves. Since the oscillons were identified empirically, they may represent the actual, physical structure of synchronous oscillations in neuronal ensembles, whereas Fourier-defined “brain waves” are nothing but poorly resolved oscillons. Nature Publishing Group UK 2019-01-28 /pmc/articles/PMC6349927/ /pubmed/30692564 http://dx.doi.org/10.1038/s41598-018-37196-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Perotti, L. DeVito, J. Bessis, D. Dabaghian, Y. Discrete Structure of the Brain Rhythms |
title | Discrete Structure of the Brain Rhythms |
title_full | Discrete Structure of the Brain Rhythms |
title_fullStr | Discrete Structure of the Brain Rhythms |
title_full_unstemmed | Discrete Structure of the Brain Rhythms |
title_short | Discrete Structure of the Brain Rhythms |
title_sort | discrete structure of the brain rhythms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6349927/ https://www.ncbi.nlm.nih.gov/pubmed/30692564 http://dx.doi.org/10.1038/s41598-018-37196-0 |
work_keys_str_mv | AT perottil discretestructureofthebrainrhythms AT devitoj discretestructureofthebrainrhythms AT bessisd discretestructureofthebrainrhythms AT dabaghiany discretestructureofthebrainrhythms |