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Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity

Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory...

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Autores principales: Hubbard, Ryan J., Zadeh, Iman, Jones, Aaron P., Robert, Bradley, Bryant, Natalie B., Clark, Vincent P., Pilly, Praveen K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8567828/
https://www.ncbi.nlm.nih.gov/pubmed/34746625
http://dx.doi.org/10.1162/netn_a_00201
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author Hubbard, Ryan J.
Zadeh, Iman
Jones, Aaron P.
Robert, Bradley
Bryant, Natalie B.
Clark, Vincent P.
Pilly, Praveen K.
author_facet Hubbard, Ryan J.
Zadeh, Iman
Jones, Aaron P.
Robert, Bradley
Bryant, Natalie B.
Clark, Vincent P.
Pilly, Praveen K.
author_sort Hubbard, Ryan J.
collection PubMed
description Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory consolidation, which along with metamemory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in metamemory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the theta band and increased efficiency in the spindle band. Additionally, stimulation-induced changes in beta-band path length were predictive of overnight changes in metamemory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects.
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spelling pubmed-85678282021-11-05 Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity Hubbard, Ryan J. Zadeh, Iman Jones, Aaron P. Robert, Bradley Bryant, Natalie B. Clark, Vincent P. Pilly, Praveen K. Netw Neurosci Research Article Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory consolidation, which along with metamemory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in metamemory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the theta band and increased efficiency in the spindle band. Additionally, stimulation-induced changes in beta-band path length were predictive of overnight changes in metamemory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects. MIT Press 2021-08-30 /pmc/articles/PMC8567828/ /pubmed/34746625 http://dx.doi.org/10.1162/netn_a_00201 Text en © 2021 Massachusetts Institute of Technology 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 the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Hubbard, Ryan J.
Zadeh, Iman
Jones, Aaron P.
Robert, Bradley
Bryant, Natalie B.
Clark, Vincent P.
Pilly, Praveen K.
Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
title Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
title_full Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
title_fullStr Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
title_full_unstemmed Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
title_short Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
title_sort brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8567828/
https://www.ncbi.nlm.nih.gov/pubmed/34746625
http://dx.doi.org/10.1162/netn_a_00201
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