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Sigma frequency dependent motor learning in Williams syndrome
There are two basic stages of fine motor learning: performance gain might occur during practice (online learning), and improvement might take place without any further practice (offline learning). Offline learning, also called consolidation, has a sleep-dependent stage in terms of both speed and acc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711805/ https://www.ncbi.nlm.nih.gov/pubmed/29196666 http://dx.doi.org/10.1038/s41598-017-12489-y |
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author | Berencsi, Andrea Bódizs, Róbert Gombos, Ferenc László, Szandra Kovács, Ilona |
author_facet | Berencsi, Andrea Bódizs, Róbert Gombos, Ferenc László, Szandra Kovács, Ilona |
author_sort | Berencsi, Andrea |
collection | PubMed |
description | There are two basic stages of fine motor learning: performance gain might occur during practice (online learning), and improvement might take place without any further practice (offline learning). Offline learning, also called consolidation, has a sleep-dependent stage in terms of both speed and accuracy of the learned movement. Sleep spindle or sigma band characteristics affect motor learning in typically developing individuals. Here we ask whether the earlier found, altered sigma activity in a neurodevelopmental disorder (Williams syndrome, WS) predicts motor learning. TD and WS participants practiced in a sequential finger tapping (FT) task for two days. Although WS participants started out at a lower performance level, TD and WS participants had a comparable amount of online and offline learning in terms of the accuracy of movement. Spectral analysis of WS sleep EEG recordings revealed that motor accuracy improvement is intricately related to WS-specific NREM sleep EEG features in the 8–16 Hz range profiles: higher 11–13.5 Hz z-transformed power is associated with higher offline FT accuracy improvement; and higher oscillatory peak frequencies are associated with lower offline accuracy improvements. These findings indicate a fundamental relationship between sleep spindle (or sigma band) activity and motor learning in WS. |
format | Online Article Text |
id | pubmed-5711805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57118052017-12-06 Sigma frequency dependent motor learning in Williams syndrome Berencsi, Andrea Bódizs, Róbert Gombos, Ferenc László, Szandra Kovács, Ilona Sci Rep Article There are two basic stages of fine motor learning: performance gain might occur during practice (online learning), and improvement might take place without any further practice (offline learning). Offline learning, also called consolidation, has a sleep-dependent stage in terms of both speed and accuracy of the learned movement. Sleep spindle or sigma band characteristics affect motor learning in typically developing individuals. Here we ask whether the earlier found, altered sigma activity in a neurodevelopmental disorder (Williams syndrome, WS) predicts motor learning. TD and WS participants practiced in a sequential finger tapping (FT) task for two days. Although WS participants started out at a lower performance level, TD and WS participants had a comparable amount of online and offline learning in terms of the accuracy of movement. Spectral analysis of WS sleep EEG recordings revealed that motor accuracy improvement is intricately related to WS-specific NREM sleep EEG features in the 8–16 Hz range profiles: higher 11–13.5 Hz z-transformed power is associated with higher offline FT accuracy improvement; and higher oscillatory peak frequencies are associated with lower offline accuracy improvements. These findings indicate a fundamental relationship between sleep spindle (or sigma band) activity and motor learning in WS. Nature Publishing Group UK 2017-12-01 /pmc/articles/PMC5711805/ /pubmed/29196666 http://dx.doi.org/10.1038/s41598-017-12489-y Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Berencsi, Andrea Bódizs, Róbert Gombos, Ferenc László, Szandra Kovács, Ilona Sigma frequency dependent motor learning in Williams syndrome |
title | Sigma frequency dependent motor learning in Williams syndrome |
title_full | Sigma frequency dependent motor learning in Williams syndrome |
title_fullStr | Sigma frequency dependent motor learning in Williams syndrome |
title_full_unstemmed | Sigma frequency dependent motor learning in Williams syndrome |
title_short | Sigma frequency dependent motor learning in Williams syndrome |
title_sort | sigma frequency dependent motor learning in williams syndrome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711805/ https://www.ncbi.nlm.nih.gov/pubmed/29196666 http://dx.doi.org/10.1038/s41598-017-12489-y |
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