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Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States
Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordin...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197642/ https://www.ncbi.nlm.nih.gov/pubmed/33906901 http://dx.doi.org/10.1523/JNEUROSCI.1837-20.2021 |
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author | Barbero-Castillo, Almudena Mateos-Aparicio, Pedro Dalla Porta, Leonardo Camassa, Alessandra Perez-Mendez, Lorena Sanchez-Vives, Maria V. |
author_facet | Barbero-Castillo, Almudena Mateos-Aparicio, Pedro Dalla Porta, Leonardo Camassa, Alessandra Perez-Mendez, Lorena Sanchez-Vives, Maria V. |
author_sort | Barbero-Castillo, Almudena |
collection | PubMed |
description | Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordings from the ferret (either sex) cerebral cortex in vitro (sPCI) to investigate the role of GABAergic inhibition in cortical complexity. We studied two dynamical states: slow-wave activity (synchronous state) and desynchronized activity, that express low and high causal complexity respectively. Progressive blockade of GABAergic inhibition during both regimes revealed its impact on the emergent cortical activity and on sPCI. Gradual GABA(A) receptor blockade resulted in higher synchronization, being able to drive the network from a desynchronized to a synchronous state, with a progressive decrease of complexity (sPCI). Blocking GABA(B) receptors also resulted in a reduced sPCI, in particular when in a synchronous, slow wave state. Our findings demonstrate that physiological levels of inhibition contribute to the generation of dynamical richness and spatiotemporal complexity. However, if inhibition is diminished or enhanced, cortical complexity decreases. Using a computational model, we explored a larger parameter space in this relationship and demonstrate a link between excitatory/inhibitory balance and the complexity expressed by the cortical network. SIGNIFICANCE STATEMENT The spatiotemporal complexity of the activity expressed by the cerebral cortex is a highly revealing feature of the underlying network's state. Complexity varies with physiological brain states: it is higher during awake than during sleep states. But it also informs about pathologic states: in disorders of consciousness, complexity is lower in an unresponsive wakefulness syndrome than in a minimally conscious state. What are the network parameters that modulate complexity? Here we investigate how inhibition, mediated by either GABA(A) or GABA(A) receptors, influences cortical complexity. And we do this departing from two extreme functional states: a highly synchronous, slow-wave state, and a desynchronized one that mimics wakefulness. We find that there is an optimal level of inhibition in which complexity is highest. |
format | Online Article Text |
id | pubmed-8197642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-81976422021-06-14 Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States Barbero-Castillo, Almudena Mateos-Aparicio, Pedro Dalla Porta, Leonardo Camassa, Alessandra Perez-Mendez, Lorena Sanchez-Vives, Maria V. J Neurosci Research Articles Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordings from the ferret (either sex) cerebral cortex in vitro (sPCI) to investigate the role of GABAergic inhibition in cortical complexity. We studied two dynamical states: slow-wave activity (synchronous state) and desynchronized activity, that express low and high causal complexity respectively. Progressive blockade of GABAergic inhibition during both regimes revealed its impact on the emergent cortical activity and on sPCI. Gradual GABA(A) receptor blockade resulted in higher synchronization, being able to drive the network from a desynchronized to a synchronous state, with a progressive decrease of complexity (sPCI). Blocking GABA(B) receptors also resulted in a reduced sPCI, in particular when in a synchronous, slow wave state. Our findings demonstrate that physiological levels of inhibition contribute to the generation of dynamical richness and spatiotemporal complexity. However, if inhibition is diminished or enhanced, cortical complexity decreases. Using a computational model, we explored a larger parameter space in this relationship and demonstrate a link between excitatory/inhibitory balance and the complexity expressed by the cortical network. SIGNIFICANCE STATEMENT The spatiotemporal complexity of the activity expressed by the cerebral cortex is a highly revealing feature of the underlying network's state. Complexity varies with physiological brain states: it is higher during awake than during sleep states. But it also informs about pathologic states: in disorders of consciousness, complexity is lower in an unresponsive wakefulness syndrome than in a minimally conscious state. What are the network parameters that modulate complexity? Here we investigate how inhibition, mediated by either GABA(A) or GABA(A) receptors, influences cortical complexity. And we do this departing from two extreme functional states: a highly synchronous, slow-wave state, and a desynchronized one that mimics wakefulness. We find that there is an optimal level of inhibition in which complexity is highest. Society for Neuroscience 2021-06-09 /pmc/articles/PMC8197642/ /pubmed/33906901 http://dx.doi.org/10.1523/JNEUROSCI.1837-20.2021 Text en Copyright © 2021 Barbero-Castillo et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Research Articles Barbero-Castillo, Almudena Mateos-Aparicio, Pedro Dalla Porta, Leonardo Camassa, Alessandra Perez-Mendez, Lorena Sanchez-Vives, Maria V. Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States |
title | Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States |
title_full | Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States |
title_fullStr | Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States |
title_full_unstemmed | Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States |
title_short | Impact of GABA(A) and GABA(B) Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States |
title_sort | impact of gaba(a) and gaba(b) inhibition on cortical dynamics and perturbational complexity during synchronous and desynchronized states |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197642/ https://www.ncbi.nlm.nih.gov/pubmed/33906901 http://dx.doi.org/10.1523/JNEUROSCI.1837-20.2021 |
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