Abstract
Modulation of beta-band neural oscillations during and following movement is a robust marker of brain function. In particular, the post-movement beta rebound (PMBR), which occurs on movement cessation, has been related to inhibition and connectivity in the healthy brain, and is perturbed in disease. However, to realise the potential of the PMBR as a biomarker, its modulation by task parameters must be characterised and its functional role determined. Here, we used MEG to image brain electrophysiology during and after a grip-force task, with the aim to characterise how task duration, in the form of an isometric contraction, modulates beta responses. Fourteen participants exerted a 30% maximum voluntary grip-force for 2, 5 and 10 s. Our results showed that the amplitude of the PMBR is modulated by task duration, with increasing duration significantly reducing PMBR amplitude and increasing its time-to-peak. No variation in the amplitude of the movement related beta decrease (MRBD) with task duration was observed. To gain insight into what may underlie these trial-averaged results, we used a Hidden Markov Model to identify the individual trial dynamics of a brain network encompassing bilateral sensorimotor areas. The rapidly evolving dynamics of this network demonstrated similar variation with task parameters to the ‘classical’ rebound, and we show that the modulation of the PMBR can be well-described in terms of increased frequency of beta events on a millisecond timescale rather than modulation of beta amplitude during this time period. Our results add to the emerging picture that, in the case of a carefully controlled paradigm, beta modulation can be systematically controlled by task parameters and such control can reveal new information as to the processes that generate the average beta timecourse. These findings will support design of clinically relevant paradigms and analysis pipelines in future use of the PMBR as a marker of neuropathology.
Original language | English |
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Article number | 116288 |
Number of pages | 15 |
Journal | NeuroImage |
Volume | 206 |
Early online date | 22 Oct 2019 |
DOIs | |
Publication status | Published - 1 Feb 2020 |
Bibliographical note
Funding Information:This work was supported by the Medical Research Council [MR/M006301/1, MR/K005464/1] and the Wellcome Trust [106183/Z/14/Z, 203139/Z/16/Z]. DOP was funded by a research studentship from the School of Physics and Astronomy, University of Nottingham, UK. This research was supported by Nottingham Birmingham strategic collaboration fund. This research was supported by the NIHR Oxford Health Biomedical Research Centre. Appendix 1
Publisher Copyright:
© 2019 The Authors
ASJC Scopus subject areas
- Neurology
- Cognitive Neuroscience