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Cortical beta oscillations are associated with motor performance following visuomotor learning.

  • S Espenhahn
  • , B. C. M. van Wijk
  • , HE Rossiter
  • , Berker AO de
  • , ND Redman
  • , J Rondina
  • , J Diedrichsen
  • , NS Ward

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points (45–60 min and 24 h after initial training). Scalp EEG was recorded during a separate simple motor task before each training and retest session.
Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45–60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes.
Original languageUndefined/Unknown
Pages (from-to)340-353
Number of pages14
JournalNeuroImage
Volume195
Early online date4 Apr 2019
DOIs
Publication statusPublished - 15 Jul 2019
Externally publishedYes

Funding

The authors are grateful to Joshua Hadwen for technical testing and assistance in EEG cap preparation. This work was supported by the Medical Research Council (S. E., A. O. d B.) , the Owerko Centre postdoctoral funding (S.E.), the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 795866 (B. C. M. v W.) and the Wellcome Trust strategic award for CUBRIC at Cardiff University (H. E. R.).

FundersFunder number
Owerko Centre
Wellcome Trust
Horizon 2020 Framework Programme
H2020 Marie Skłodowska-Curie Actions795866
Medical Research Council
Cardiff University
Horizon 2020

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