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Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps
Accumulating evidence suggests that sleep, and particularly Slow-Wave-Sleep (SWS), helps the implicit and explicit extraction of regularities within memories that were encoded in a previous wake period. Sleep following training on virtual navigation was also shown to improve performance in subsequen...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186812/ https://www.ncbi.nlm.nih.gov/pubmed/30349468 http://dx.doi.org/10.3389/fnhum.2018.00404 |
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author | Lerner, Itamar Gluck, Mark A. |
author_facet | Lerner, Itamar Gluck, Mark A. |
author_sort | Lerner, Itamar |
collection | PubMed |
description | Accumulating evidence suggests that sleep, and particularly Slow-Wave-Sleep (SWS), helps the implicit and explicit extraction of regularities within memories that were encoded in a previous wake period. Sleep following training on virtual navigation was also shown to improve performance in subsequent navigation tests. Some studies propose that this sleep-effect on navigation is based on explicit recognition of landmarks; however, it is possible that SWS-dependent extraction of implicit spatiotemporal regularities contributes as well. To examine this possibility, we administered a novel virtual navigation task in which participants were required to walk through a winding corridor and then choose one of five marked doors to exit. Unknown to participants, the markings on the correct door reflected the corridor’s shape (from a bird’s eye view). Detecting this regularity negates the need to find the exit by trial and error. Participants performed the task twice a day for a week, while their overnight sleep was monitored. We found that the more time participants spent in SWS across the week, the better they were able to implicitly extract the hidden regularity. In contrast, the few participants that explicitly realized the regularity did not rely on SWS to do so. Moreover, the SWS effect was strictly at the trait-level: Baseline levels of SWS prior to the experimental week could predict success just as well, but day-to-day variations in SWS did not predict day-to-day improvements. We propose that our findings indicate SWS facilitates implicit integration of new information into cognitive maps, possibly through compressed memory replay. |
format | Online Article Text |
id | pubmed-6186812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61868122018-10-22 Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps Lerner, Itamar Gluck, Mark A. Front Hum Neurosci Human Neuroscience Accumulating evidence suggests that sleep, and particularly Slow-Wave-Sleep (SWS), helps the implicit and explicit extraction of regularities within memories that were encoded in a previous wake period. Sleep following training on virtual navigation was also shown to improve performance in subsequent navigation tests. Some studies propose that this sleep-effect on navigation is based on explicit recognition of landmarks; however, it is possible that SWS-dependent extraction of implicit spatiotemporal regularities contributes as well. To examine this possibility, we administered a novel virtual navigation task in which participants were required to walk through a winding corridor and then choose one of five marked doors to exit. Unknown to participants, the markings on the correct door reflected the corridor’s shape (from a bird’s eye view). Detecting this regularity negates the need to find the exit by trial and error. Participants performed the task twice a day for a week, while their overnight sleep was monitored. We found that the more time participants spent in SWS across the week, the better they were able to implicitly extract the hidden regularity. In contrast, the few participants that explicitly realized the regularity did not rely on SWS to do so. Moreover, the SWS effect was strictly at the trait-level: Baseline levels of SWS prior to the experimental week could predict success just as well, but day-to-day variations in SWS did not predict day-to-day improvements. We propose that our findings indicate SWS facilitates implicit integration of new information into cognitive maps, possibly through compressed memory replay. Frontiers Media S.A. 2018-10-08 /pmc/articles/PMC6186812/ /pubmed/30349468 http://dx.doi.org/10.3389/fnhum.2018.00404 Text en Copyright © 2018 Lerner and Gluck. http://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 | Human Neuroscience Lerner, Itamar Gluck, Mark A. Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps |
title | Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps |
title_full | Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps |
title_fullStr | Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps |
title_full_unstemmed | Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps |
title_short | Individual Differences in Slow-Wave-Sleep Predict Acquisition of Full Cognitive Maps |
title_sort | individual differences in slow-wave-sleep predict acquisition of full cognitive maps |
topic | Human Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186812/ https://www.ncbi.nlm.nih.gov/pubmed/30349468 http://dx.doi.org/10.3389/fnhum.2018.00404 |
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