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Repetitive Transcranial Magnetic Stimulation to the Unilateral Hemisphere of Rat Brain
Published on: October 22, 2016
Brain state dependent repetitive transcranial magnetic stimulation improves motor learning outcomes
Ian Daly1, Roshan Withanage1, Joao Oliveira2,3,4
1Brain-Computer Interfacing and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom.
Abstract:
Objective.Motor learning is key to successful neuro-rehabilitation. Combinations of brain-computer interfaces (BCIs) and repetitive transcranial magnetic stimulation (rTMS) have been proposed for neurorehabilitation following conditions such as stroke. However, rTMS is typically delivered via a fixed protocol without taking into consideration the current brain states of participants. We propose a new BCI-based rTMS delivery protocol for supporting motor learning. Specifically, we propose BCI-based brain state dependent delivery of rTMS, in which a BCI system measures the event-related desynchronisation (ERD; a neural marker of motor learning in the alpha band, selected because it is a robust, well-established real-time EEG correlate of motor activity and cortical excitability) in order to determine when to deliver rTMS.Approach.We compare our proposed rTMS delivery protocol with two state of the art comparable protocols: delivery of rTMS prior to the BCI-based motor learning and delivery of rTMS at fixed times throughout the experiment, as well as a control condition in which no rTMS was used. Each protocol is tested with a different group (n = 8) of participants (n = 32 total participants).Main results. Our results reveal a significant effect of changing the rTMS delivery protocol (p = 0.005) and that our proposed rTMS delivery protocol delivers better motor learning outcomes than other state of the art rTMS delivery protocols (e.g. BCI group vs fixed times group:p = 0.003, BCI group vs no rTMS group:p = 0.03). Inspection of ERD dynamics from each of our participant groups demonstrates that our BCI-based rTMS paradigm keeps corticospinal excitability relatively stable throughout the learning period, keeping the brain in a more optimal learning state for longer.Significance. These findings suggest potential applications for adaptive rTMS-BCI systems in clinical neurorehabilitation, sports skill learning, and neuroprosthetic control.
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