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Neurophysiological correlates of passive movements are speed- and type-dependent

Veldman, M. P.; Kwant, J. Z.; Lommerse, J.; Feenstra, M.; Lamoth, C. J. C.; Volkers, A. H. M.; Drenth, H.; Zuidema, S.; Bautmans, I.; Hobbelen, H.

2025-07-14 neuroscience
10.1101/2025.07.09.663910 bioRxiv
Show abstract

IntroductionThe supraspinal involvement in the control of passive movements remains elusive. Mechanoreceptor properties, their change in the context of ageing and the somatotopically organized supraspinal connections between sensory and motor systems provide a neuroanatomical basis for the prediction that cortical structures are involved in the control of passive movements. Previous electromyographic evidence indeed show movement speed and - type-dependent changes in muscle activity. This study aimed to provide electrophysiological evidence for the involvement of frontal cortex inhibition and corticomotor interactions in the control of passive movements. MethodsContinuous and discontinuous passive elbow movements were performed in healthy younger (n = 20, 22.5 {+/-} 2.31 y) and older (n = 20, 72.7 {+/-} 5.73 y) adults at three movement speeds (20, 60, and 100 bpm) while electro-encephalographic (EEG) and electromyographic (EMG) data were acquired. Alpha power and beta corticomuscular connectivity were used as measures of frontal cortex inhibition and brain-muscle connectivity, respectively. ResultsFrontal cortex inhibition decreased (p = 0.036) and brain-muscle connectivity increased (p < 0.001) with increasing movement speeds. In addition, frontal cortex inhibition was 17% higher in the discontinuous condition as compared to the continuous condition (p = 0.005) while corticomuscular coherence was 25.9% higher in the continuous vs. the discontinuous condition (p < 0.001). These effects were independent of age. ConclusionThe present results provide insights into the control of passive movements and show that frontal cortex inhibition and brain-muscle interactions depend on movement speed and movement type.

Published in European Journal of Applied Physiology (predicted rank #24) · training set

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