M P Veldman1, N M Maurits2, M A M Nijland3, N E Wolters3, J C Mizelle4, T Hortobágyi3. 1. University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, The Netherlands. Electronic address: m.p.veldman@umcg.nl. 2. University of Groningen, University Medical Center Groningen, Department of Neurology, Groningen, The Netherlands; University of Groningen, Neuroimaging Center, Groningen, The Netherlands. 3. University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, The Netherlands. 4. Department of Kinesiology, East Carolina University, Greenville, NC, USA.
Abstract
OBJECTIVE: Plasticity of the central nervous system likely underlies motor learning. It is however unclear, whether plasticity in cortical motor networks is motor learning stage-, activity-, or connectivity-dependent. METHODS: From electroencephalography (EEG) data, we quantified effective connectivity by the phase slope index (PSI), neuronal activity by event-related desynchronization, and sensorimotor integration by N30 during the stages of visuomotor skill acquisition, consolidation, and interlimb transfer. RESULTS: Although N30 amplitudes and event-related desynchronization in parietal electrodes increased with skill acquisition, changes in PSI correlated most with motor performance in all stages of motor learning. Specifically, changes in PSI between the premotor, supplementary motor, and primary motor cortex (M1) electrodes correlated with skill acquisition, whereas changes in PSI between electrodes representing M1 and the parietal and primary sensory cortex (S1) correlated with skill consolidation. The magnitude of consolidated interlimb transfer correlated with PSI between bilateral M1s and between S1 and M1 in the non-practiced hemisphere. CONCLUSIONS: Spectral and temporal EEG measures but especially PSI correlated with improvements in complex motor behavior and revealed distinct neural networks in the acquisition, consolidation, and interlimb transfer of motor skills. SIGNIFICANCE: A complete understanding of the neuronal mechanisms underlying motor learning can contribute to optimizing rehabilitation protocols.
RCT Entities:
OBJECTIVE: Plasticity of the central nervous system likely underlies motor learning. It is however unclear, whether plasticity in cortical motor networks is motor learning stage-, activity-, or connectivity-dependent. METHODS: From electroencephalography (EEG) data, we quantified effective connectivity by the phase slope index (PSI), neuronal activity by event-related desynchronization, and sensorimotor integration by N30 during the stages of visuomotor skill acquisition, consolidation, and interlimb transfer. RESULTS: Although N30 amplitudes and event-related desynchronization in parietal electrodes increased with skill acquisition, changes in PSI correlated most with motor performance in all stages of motor learning. Specifically, changes in PSI between the premotor, supplementary motor, and primary motor cortex (M1) electrodes correlated with skill acquisition, whereas changes in PSI between electrodes representing M1 and the parietal and primary sensory cortex (S1) correlated with skill consolidation. The magnitude of consolidated interlimb transfer correlated with PSI between bilateral M1s and between S1 and M1 in the non-practiced hemisphere. CONCLUSIONS: Spectral and temporal EEG measures but especially PSI correlated with improvements in complex motor behavior and revealed distinct neural networks in the acquisition, consolidation, and interlimb transfer of motor skills. SIGNIFICANCE: A complete understanding of the neuronal mechanisms underlying motor learning can contribute to optimizing rehabilitation protocols.
Authors: Sander Lindeman; Sungho Hong; Lieke Kros; Jorge F Mejias; Vincenzo Romano; Robert Oostenveld; Mario Negrello; Laurens W J Bosman; Chris I De Zeeuw Journal: Proc Natl Acad Sci U S A Date: 2021-01-12 Impact factor: 11.205
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