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Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time
Previous studies have demonstrated that the brain has an intrinsic resistance to changes in arousal state. This resistance is most easily measured at the population level in the setting of general anesthesia and has been termed neural inertia. To date, no study has attempted to determine neural iner...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794956/ https://www.ncbi.nlm.nih.gov/pubmed/35095434 http://dx.doi.org/10.3389/fnsys.2021.787612 |
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author | Wasilczuk, Andrzej Z. Meng, Qing Cheng McKinstry-Wu, Andrew R. |
author_facet | Wasilczuk, Andrzej Z. Meng, Qing Cheng McKinstry-Wu, Andrew R. |
author_sort | Wasilczuk, Andrzej Z. |
collection | PubMed |
description | Previous studies have demonstrated that the brain has an intrinsic resistance to changes in arousal state. This resistance is most easily measured at the population level in the setting of general anesthesia and has been termed neural inertia. To date, no study has attempted to determine neural inertia in individuals. We hypothesize that individuals with markedly increased or decreased neural inertia might be at increased risk for complications related to state transitions, from awareness under anesthesia, to delayed emergence or confusion/impairment after emergence. Hence, an improved theoretical and practical understanding of neural inertia may have the potential to identify individuals at increased risk for these complications. This study was designed to explicitly measure neural inertia in individuals and empirically test the stochastic model of neural inertia using spectral analysis of the murine EEG. EEG was measured after induction of and emergence from isoflurane administered near the EC(50) dose for loss of righting in genetically inbred mice on a timescale that minimizes pharmacokinetic confounds. Neural inertia was assessed by employing classifiers constructed using linear discriminant or supervised machine learning methods to determine if features of EEG spectra reliably demonstrate path dependence at steady-state anesthesia. We also report the existence of neural inertia at the individual level, as well as the population level, and that neural inertia decreases over time, providing direct empirical evidence supporting the predictions of the stochastic model of neural inertia. |
format | Online Article Text |
id | pubmed-8794956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87949562022-01-29 Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time Wasilczuk, Andrzej Z. Meng, Qing Cheng McKinstry-Wu, Andrew R. Front Syst Neurosci Neuroscience Previous studies have demonstrated that the brain has an intrinsic resistance to changes in arousal state. This resistance is most easily measured at the population level in the setting of general anesthesia and has been termed neural inertia. To date, no study has attempted to determine neural inertia in individuals. We hypothesize that individuals with markedly increased or decreased neural inertia might be at increased risk for complications related to state transitions, from awareness under anesthesia, to delayed emergence or confusion/impairment after emergence. Hence, an improved theoretical and practical understanding of neural inertia may have the potential to identify individuals at increased risk for these complications. This study was designed to explicitly measure neural inertia in individuals and empirically test the stochastic model of neural inertia using spectral analysis of the murine EEG. EEG was measured after induction of and emergence from isoflurane administered near the EC(50) dose for loss of righting in genetically inbred mice on a timescale that minimizes pharmacokinetic confounds. Neural inertia was assessed by employing classifiers constructed using linear discriminant or supervised machine learning methods to determine if features of EEG spectra reliably demonstrate path dependence at steady-state anesthesia. We also report the existence of neural inertia at the individual level, as well as the population level, and that neural inertia decreases over time, providing direct empirical evidence supporting the predictions of the stochastic model of neural inertia. Frontiers Media S.A. 2022-01-14 /pmc/articles/PMC8794956/ /pubmed/35095434 http://dx.doi.org/10.3389/fnsys.2021.787612 Text en Copyright © 2022 Wasilczuk, Meng and McKinstry-Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Wasilczuk, Andrzej Z. Meng, Qing Cheng McKinstry-Wu, Andrew R. Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time |
title | Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time |
title_full | Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time |
title_fullStr | Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time |
title_full_unstemmed | Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time |
title_short | Electroencephalographic Evidence for Individual Neural Inertia in Mice That Decreases With Time |
title_sort | electroencephalographic evidence for individual neural inertia in mice that decreases with time |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794956/ https://www.ncbi.nlm.nih.gov/pubmed/35095434 http://dx.doi.org/10.3389/fnsys.2021.787612 |
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