Sensorimotor cortex beta oscillations reflect motor skill learning ability after stroke

Author:

Espenhahn Svenja12ORCID,Rossiter Holly E3,van Wijk Bernadette C M4,Redman Nell2,Rondina Jane M2,Diedrichsen Joern5,Ward Nick S2

Affiliation:

1. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 1N4, Canada

2. Department of Clinical and Movement Neurosciences, Institute of Neurology, University College London, London WC1N 3BG, UK

3. School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff CF24 4HQ, UK

4. Integrative Model-based Cognitive Neuroscience Research Unit, Department of Psychology, University of Amsterdam, Amsterdam 1018 WT, The Netherlands

5. Department of Computer Science, Department of Statistical and Actuarial Sciences, Brain and Mind Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada

Abstract

Abstract Recovery of skilled movement after stroke is assumed to depend on motor learning. However, the capacity for motor learning and factors that influence motor learning after stroke have received little attention. In this study, we first compared motor skill acquisition and retention between well-recovered stroke patients and age- and performance-matched healthy controls. We then tested whether beta oscillations (15–30 Hz) from sensorimotor cortices contribute to predicting training-related motor performance. Eighteen well-recovered chronic stroke survivors (mean age 64 ± 8 years, range: 50–74 years) and 20 age- and sex-matched healthy controls were trained on a continuous tracking task and subsequently retested after initial training (45–60 min and 24 h later). Scalp electroencephalography was recorded during the performance of a simple motor task before each training and retest session. Stroke patients demonstrated capacity for motor skill learning, but it was diminished compared to age- and performance-matched healthy controls. Furthermore, although the properties of beta oscillations prior to training were comparable between stroke patients and healthy controls, stroke patients did show less change in beta measures with motor learning. Lastly, although beta oscillations did not help to predict motor performance immediately after training, contralateral (ipsilesional) sensorimotor cortex post-movement beta rebound measured after training helped predict future motor performance, 24 h after training. This finding suggests that neurophysiological measures such as beta oscillations can help predict response to motor training in chronic stroke patients and may offer novel targets for therapeutic interventions.

Funder

Medical Research Council

Marie Sklodowska-Curie

Wellcome Trust

CUBRIC at Cardiff University

Publisher

Oxford University Press (OUP)

Subject

General Earth and Planetary Sciences,General Environmental Science

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