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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
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.
Using Corticomuscular and Intermuscular Coherence to Assess Cortical Contribution to Ankle Plantar Flexor Activity During Gait
Published in Journal of Motor Behavior, 2019
Peter Jensen, Rasmus Frisk, Meaghan Elizabeth Spedden, Svend Sparre Geertsen, Laurent J. Bouyer, David M. Halliday, Jens Bo Nielsen
The observed corticomuscular coherence during gait is several magnitudes lower than that, which has been reported during static plantar flexion (Perez, Lundbye-Jensen, & Nielsen, 2007; Ushiyama, Takahashi, & Ushiba, 2010). Although Petersen et al. (2012) found reproducible corticomuscular coherence for the Tibialis anterior muscle in the swing phase of gait, the magnitude of this coherence was also several magnitudes lower than what is normally reported for static dorsiflexion (Petersen et al., 2012). This is not surprising since coherence between cortex and muscle will require relatively constant firing rates of the corticospinal neurons within a narrow band of frequencies, which is unlikely to occur to any large extent during a dynamic task like walking. Recordings from the cat motor cortex during gait or from monkey corticospinal neurons during hand movements rather suggest that the corticospinal neurons discharge at greatly varying rates and are only active for relatively brief periods of time. The fact that we have been able to detect significant corticomuscular coherence despite of the dynamic nature of the task is therefore noteworthy. There are a number of factors that could explain the low levels of coherence in this study. The estimates are pooled across subjects so may well be affected by variability between subjects. The task is highly dynamic in nature, this is clear from the time frequency and directionality plots which indicate changes in the strength of correlation and in the directional components can occur over time scales of around 200 ms. The analysis is based on coherence estimation which assumes linear interactions, application of nonlinear analysis may provide further insight into the complex interactions between cortical and spinal neurons (Cunningham et al., 2004).