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A generalized phase resetting method for phase-locked modes prediction
We derived analytically and checked numerically a set of novel conditions for the existence and the stability of phase-locked modes in a biologically relevant master-slave neural network with a dynamic feedback loop. Since neural oscillators even in the three-neuron network investigated here receive...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5360347/ https://www.ncbi.nlm.nih.gov/pubmed/28323894 http://dx.doi.org/10.1371/journal.pone.0174304 |
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author | Oprisan, Sorinel A. Austin, Dave I. |
author_facet | Oprisan, Sorinel A. Austin, Dave I. |
author_sort | Oprisan, Sorinel A. |
collection | PubMed |
description | We derived analytically and checked numerically a set of novel conditions for the existence and the stability of phase-locked modes in a biologically relevant master-slave neural network with a dynamic feedback loop. Since neural oscillators even in the three-neuron network investigated here receive multiple inputs per cycle, we generalized the concept of phase resetting to accommodate multiple inputs per cycle. We proved that the phase resetting produced by two or more stimuli per cycle can be recursively computed from the traditional, single stimulus, phase resetting. We applied the newly derived generalized phase resetting definition to predicting the relative phase and the stability of a phase-locked mode that was experimentally observed in this type of master-slave network with a dynamic loop network. |
format | Online Article Text |
id | pubmed-5360347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53603472017-04-06 A generalized phase resetting method for phase-locked modes prediction Oprisan, Sorinel A. Austin, Dave I. PLoS One Research Article We derived analytically and checked numerically a set of novel conditions for the existence and the stability of phase-locked modes in a biologically relevant master-slave neural network with a dynamic feedback loop. Since neural oscillators even in the three-neuron network investigated here receive multiple inputs per cycle, we generalized the concept of phase resetting to accommodate multiple inputs per cycle. We proved that the phase resetting produced by two or more stimuli per cycle can be recursively computed from the traditional, single stimulus, phase resetting. We applied the newly derived generalized phase resetting definition to predicting the relative phase and the stability of a phase-locked mode that was experimentally observed in this type of master-slave network with a dynamic loop network. Public Library of Science 2017-03-21 /pmc/articles/PMC5360347/ /pubmed/28323894 http://dx.doi.org/10.1371/journal.pone.0174304 Text en © 2017 Oprisan, Austin http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Oprisan, Sorinel A. Austin, Dave I. A generalized phase resetting method for phase-locked modes prediction |
title | A generalized phase resetting method for phase-locked modes prediction |
title_full | A generalized phase resetting method for phase-locked modes prediction |
title_fullStr | A generalized phase resetting method for phase-locked modes prediction |
title_full_unstemmed | A generalized phase resetting method for phase-locked modes prediction |
title_short | A generalized phase resetting method for phase-locked modes prediction |
title_sort | generalized phase resetting method for phase-locked modes prediction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5360347/ https://www.ncbi.nlm.nih.gov/pubmed/28323894 http://dx.doi.org/10.1371/journal.pone.0174304 |
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