Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning
Sleep and wakefulness are no longer to be considered as discrete states. During wakefulness brain regions can enter a sleep-like state (off-periods) in response to a prolonged period of activity (local use-dependent sleep). Similarly, during nonREM sleep the slow-wave activity, the hallmark of sleep...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2018-04-01
|
Series: | Frontiers in Human Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/article/10.3389/fnhum.2018.00122/full |
id |
doaj-ee4f1f9b93dc4fdcac80759cfc7ba767 |
---|---|
record_format |
Article |
spelling |
doaj-ee4f1f9b93dc4fdcac80759cfc7ba7672020-11-25T02:04:11ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612018-04-011210.3389/fnhum.2018.00122317047Local Use-Dependent Sleep in Wakefulness Links Performance Errors to LearningAngelica Quercia0Filippo Zappasodi1Filippo Zappasodi2Giorgia Committeri3Giorgia Committeri4Michele Ferrara5Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, ItalyDepartment of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies (ITAB), G. d'Annunzio University of Chieti-Pescara, Chieti, ItalyDepartment of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies (ITAB), G. d'Annunzio University of Chieti-Pescara, Chieti, ItalyDepartment of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Coppito, ItalySleep and wakefulness are no longer to be considered as discrete states. During wakefulness brain regions can enter a sleep-like state (off-periods) in response to a prolonged period of activity (local use-dependent sleep). Similarly, during nonREM sleep the slow-wave activity, the hallmark of sleep plasticity, increases locally in brain regions previously involved in a learning task. Recent studies have demonstrated that behavioral performance may be impaired by off-periods in wake in task-related regions. However, the relation between off-periods in wake, related performance errors and learning is still untested in humans. Here, by employing high density electroencephalographic (hd-EEG) recordings, we investigated local use-dependent sleep in wake, asking participants to repeat continuously two intensive spatial navigation tasks. Critically, one task relied on previous map learning (Wayfinding) while the other did not (Control). Behaviorally awake participants, who were not sleep deprived, showed progressive increments of delta activity only during the learning-based spatial navigation task. As shown by source localization, delta activity was mainly localized in the left parietal and bilateral frontal cortices, all regions known to be engaged in spatial navigation tasks. Moreover, during the Wayfinding task, these increments of delta power were specifically associated with errors, whose probability of occurrence was significantly higher compared to the Control task. Unlike the Wayfinding task, during the Control task neither delta activity nor the number of errors increased progressively. Furthermore, during the Wayfinding task, both the number and the amplitude of individual delta waves, as indexes of neuronal silence in wake (off-periods), were significantly higher during errors than hits. Finally, a path analysis linked the use of the spatial navigation circuits undergone to learning plasticity to off periods in wake. In conclusion, local sleep regulation in wakefulness, associated with performance failures, could be functionally linked to learning-related cortical plasticity.http://journal.frontiersin.org/article/10.3389/fnhum.2018.00122/fulldelta activityerrorshigh-density EEGoverlearningtime on taskwayfinding |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Angelica Quercia Filippo Zappasodi Filippo Zappasodi Giorgia Committeri Giorgia Committeri Michele Ferrara |
spellingShingle |
Angelica Quercia Filippo Zappasodi Filippo Zappasodi Giorgia Committeri Giorgia Committeri Michele Ferrara Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning Frontiers in Human Neuroscience delta activity errors high-density EEG overlearning time on task wayfinding |
author_facet |
Angelica Quercia Filippo Zappasodi Filippo Zappasodi Giorgia Committeri Giorgia Committeri Michele Ferrara |
author_sort |
Angelica Quercia |
title |
Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning |
title_short |
Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning |
title_full |
Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning |
title_fullStr |
Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning |
title_full_unstemmed |
Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning |
title_sort |
local use-dependent sleep in wakefulness links performance errors to learning |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Human Neuroscience |
issn |
1662-5161 |
publishDate |
2018-04-01 |
description |
Sleep and wakefulness are no longer to be considered as discrete states. During wakefulness brain regions can enter a sleep-like state (off-periods) in response to a prolonged period of activity (local use-dependent sleep). Similarly, during nonREM sleep the slow-wave activity, the hallmark of sleep plasticity, increases locally in brain regions previously involved in a learning task. Recent studies have demonstrated that behavioral performance may be impaired by off-periods in wake in task-related regions. However, the relation between off-periods in wake, related performance errors and learning is still untested in humans. Here, by employing high density electroencephalographic (hd-EEG) recordings, we investigated local use-dependent sleep in wake, asking participants to repeat continuously two intensive spatial navigation tasks. Critically, one task relied on previous map learning (Wayfinding) while the other did not (Control). Behaviorally awake participants, who were not sleep deprived, showed progressive increments of delta activity only during the learning-based spatial navigation task. As shown by source localization, delta activity was mainly localized in the left parietal and bilateral frontal cortices, all regions known to be engaged in spatial navigation tasks. Moreover, during the Wayfinding task, these increments of delta power were specifically associated with errors, whose probability of occurrence was significantly higher compared to the Control task. Unlike the Wayfinding task, during the Control task neither delta activity nor the number of errors increased progressively. Furthermore, during the Wayfinding task, both the number and the amplitude of individual delta waves, as indexes of neuronal silence in wake (off-periods), were significantly higher during errors than hits. Finally, a path analysis linked the use of the spatial navigation circuits undergone to learning plasticity to off periods in wake. In conclusion, local sleep regulation in wakefulness, associated with performance failures, could be functionally linked to learning-related cortical plasticity. |
topic |
delta activity errors high-density EEG overlearning time on task wayfinding |
url |
http://journal.frontiersin.org/article/10.3389/fnhum.2018.00122/full |
work_keys_str_mv |
AT angelicaquercia localusedependentsleepinwakefulnesslinksperformanceerrorstolearning AT filippozappasodi localusedependentsleepinwakefulnesslinksperformanceerrorstolearning AT filippozappasodi localusedependentsleepinwakefulnesslinksperformanceerrorstolearning AT giorgiacommitteri localusedependentsleepinwakefulnesslinksperformanceerrorstolearning AT giorgiacommitteri localusedependentsleepinwakefulnesslinksperformanceerrorstolearning AT micheleferrara localusedependentsleepinwakefulnesslinksperformanceerrorstolearning |
_version_ |
1724943932404531200 |