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Wheels of Motion: Oscillatory Potentials in the Motor Cortex
Published in Alexa Riehle, Eilon Vaadia, Motor Cortex in Voluntary Movements, 2004
Mima and colleagues have shown that corticomuscular coherence is probably not due to reafferent signals from the contracting muscle.42 As subjects performed thumb and little finger apposition, vibration of the abductor pollicis brevis muscle tendon at 100 Hz had no significant effect on coherence (in either the mu or beta band). Similarly, functional deafferentation by ischemia failed to change corticomuscular coherence.6786 One may conclude that movement-related cortical oscillations reflect motor rather than sensory activity. Moreover, the location of peak beta corticomuscular coherence generally corresponds to the appropriate muscle representation in motor cortex, as determined by TMS.42
Coherence-based connectivity analysis of EEG and EMG signals during reach-to-grasp movement involving two weights
Published in Brain-Computer Interfaces, 2022
Cristian D. Guerrero-Mendez, Andres F. Ruiz-Olaya
Previous reports have shown that synchronization between neurons in the motor cortex and motor units occurs during the performance of a motor task [1]. That mechanism was shown using one Magnetoencephalography (MEG) channel recording the cortical motor activity and the surface electromyogram (EMG) of a contralateral active muscle during the execution of a muscular voluntary contraction; Corticomuscular connectivity between cortical rhythms and rectified EMG confined to the beta (15–30 Hz) frequency range was evidenced, applying coherence analysis [2]. Furthermore, movements have long been known to induce frequency-specific changes in Electroencephalography (EEG) [3]. Those works evidence that there is corticomuscular connectivity defined as a relationship, association, or statistical dependence between EEG and EMG signals resulting from the functional integration of the neural and muscular systems [4,5]. EEG–EMG coherence could be used to examine a functional connection between a human brain and muscles by calculating the linear relationship of frequency domain components of EEG and EMG signals. Corticomuscular coherence allows studying of the mechanism of the cerebral cortex’s control of muscle activity, which reveals the communication in corticospinal pathways between the primary motor cortex and muscles. Normally, cortical events propagate to the periphery, and the motor cortex also receives input from the periphery [6].
Toward improving functional recovery in spinal cord injury using robotics: a pilot study focusing on ankle rehabilitation
Published in Expert Review of Medical Devices, 2022
Rocco Salvatore Calabrò, Luana Billeri, Fabrizio Ciappina, Tina Balletta, Bruno Porcari, Antonino Cannavò, Loris Pignolo, Alfredo Manuli, Antonino Naro
It is hypothesizable that the entire sensory-motor amount provided by the robot-aided ankle rehab could entrain neuroplasticity mechanisms at spinal and supraspinal levels, which may favor motor recovery. To test this hypothesis, we conducted a pilot study to assess the neurophysiological underpinnings of robot-aided ankle rehabilitation (using the ankle rehabilitation platform-robot Hunova®; Movendo Technology, Genoa, Italy). In this regard, we estimated the muscle activation patterns by using surface EMG and the bidirectional functional connection (i.e. sensory feedback and motor output) between the cortex and muscles during muscle contractions as the result of the cerebral cortex control of muscle activity by computing corticomuscular coherence (CMC). Specifically, we expected that robot-aided ankle rehabilitation could selectively enhance CMC, i.e. they could favor a better communication between the structures located above and below SCI (i.e. a more synchronized corticospinal output) and, consequently, muscle activation patterns, i.e. better responsiveness of below-SCI motorneurons to corticospinal output. The changes in CMC and muscle activation patterns may reflect both supraspinal and spinal neuroplasticity mechanisms that would ultimately improve gait and balance. Furthermore, we assessed the efficacy of this type of robot-aided ankle rehabilitation in improving gait performance and balance by comparing the clinical outcomes (gait performance, balance, functional independence, and quality of life) in the ankle robotic rehab group with those coming from a retrospective conventional physiotherapy group, who consisted of persons with iSCI matched for the inclusion criteria and clinical-demographic characteristics.