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Phase-Amplitude Coupling in Spontaneous Mouse Behavior

The level of activity of many animals including humans rises and falls with a period of ~ 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment...

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Autores principales: Thengone, Daniel, Gagnidze, Khatuna, Pfaff, Donald, Proekt, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025157/
https://www.ncbi.nlm.nih.gov/pubmed/27631971
http://dx.doi.org/10.1371/journal.pone.0162262
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author Thengone, Daniel
Gagnidze, Khatuna
Pfaff, Donald
Proekt, Alex
author_facet Thengone, Daniel
Gagnidze, Khatuna
Pfaff, Donald
Proekt, Alex
author_sort Thengone, Daniel
collection PubMed
description The level of activity of many animals including humans rises and falls with a period of ~ 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment, most notably the light:dark cycle. In addition to the circadian oscillations, behavior of many animals is influenced by multiple oscillations occurring at faster—ultradian—time scales. These ultradian oscillations are also thought to be driven by feedback loops. While many studies have focused on identifying such ultradian oscillations, less is known about how the ultradian behavioral oscillations interact with each other and with the circadian oscillation. Decoding the coupling among the various physiological oscillators may be important for understanding how they conspire together to regulate the normal activity levels, as well in disease states in which such rhythmic fluctuations in behavior may be disrupted. Here, we use a wavelet-based cross-frequency analysis to show that different oscillations identified in spontaneous mouse behavior are coupled such that the amplitude of oscillations occurring at higher frequencies are modulated by the phase of the slower oscillations. The patterns of these interactions are different among different individuals. Yet this variability is not random. Differences in the pattern of interactions are confined to a low dimensional subspace where different patterns of interactions form clusters. These clusters expose the differences among individuals—males and females are preferentially segregated into different clusters. These sex-specific features of spontaneous behavior were not apparent in the spectra. Thus, our methodology reveals novel aspects of the structure of spontaneous animal behavior that are not observable using conventional methodology.
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spelling pubmed-50251572016-09-27 Phase-Amplitude Coupling in Spontaneous Mouse Behavior Thengone, Daniel Gagnidze, Khatuna Pfaff, Donald Proekt, Alex PLoS One Research Article The level of activity of many animals including humans rises and falls with a period of ~ 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment, most notably the light:dark cycle. In addition to the circadian oscillations, behavior of many animals is influenced by multiple oscillations occurring at faster—ultradian—time scales. These ultradian oscillations are also thought to be driven by feedback loops. While many studies have focused on identifying such ultradian oscillations, less is known about how the ultradian behavioral oscillations interact with each other and with the circadian oscillation. Decoding the coupling among the various physiological oscillators may be important for understanding how they conspire together to regulate the normal activity levels, as well in disease states in which such rhythmic fluctuations in behavior may be disrupted. Here, we use a wavelet-based cross-frequency analysis to show that different oscillations identified in spontaneous mouse behavior are coupled such that the amplitude of oscillations occurring at higher frequencies are modulated by the phase of the slower oscillations. The patterns of these interactions are different among different individuals. Yet this variability is not random. Differences in the pattern of interactions are confined to a low dimensional subspace where different patterns of interactions form clusters. These clusters expose the differences among individuals—males and females are preferentially segregated into different clusters. These sex-specific features of spontaneous behavior were not apparent in the spectra. Thus, our methodology reveals novel aspects of the structure of spontaneous animal behavior that are not observable using conventional methodology. Public Library of Science 2016-09-15 /pmc/articles/PMC5025157/ /pubmed/27631971 http://dx.doi.org/10.1371/journal.pone.0162262 Text en © 2016 Thengone et al 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
Thengone, Daniel
Gagnidze, Khatuna
Pfaff, Donald
Proekt, Alex
Phase-Amplitude Coupling in Spontaneous Mouse Behavior
title Phase-Amplitude Coupling in Spontaneous Mouse Behavior
title_full Phase-Amplitude Coupling in Spontaneous Mouse Behavior
title_fullStr Phase-Amplitude Coupling in Spontaneous Mouse Behavior
title_full_unstemmed Phase-Amplitude Coupling in Spontaneous Mouse Behavior
title_short Phase-Amplitude Coupling in Spontaneous Mouse Behavior
title_sort phase-amplitude coupling in spontaneous mouse behavior
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025157/
https://www.ncbi.nlm.nih.gov/pubmed/27631971
http://dx.doi.org/10.1371/journal.pone.0162262
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