文章基本信息

标题：Sigma frequency dependent motor learning in Williams syndrome
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作者：Andrea Berencsi ; Róbert Bódizs ; Ferenc Gombos 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2017
卷号：7
期号：1
页码：16759
DOI：10.1038/s41598-017-12489-y
语种：English
出版社：Springer Nature
摘要：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.