Corticomuscular coherence relates to the synchrony in the neural activity of brain's cortical areas and muscle. The neural activities are picked up by electrophysiological recordings from the brain (e.g. EEG, MEG, ECoG, etc.) and muscle (EMG). It is a method to study the neural control of movement.
Physiology
editCorticomuscular coherence was initially reported between MEG and EMG[1] and is widely studied between EMG and EEG, MEG, etc.
The origins of corticomuscular coherence seem to be communication in corticospinal pathways between primary motor cortex and muscles. While the role of descending corticomuscular pathways in generation of coherence are more clear, the role of ascending sensory spinocortical pathways are less certain.
Corticomuscular coherence has been of special interest in alpha band (about 10 Hz), in Beta band (15–30 Hz), and in Gamma band (35–60 Hz).
Mathematics and statistics
editA classic and commonly used approach to assess the synchrony between neural signals is to use Coherence.[2]
Statistical significance of coherence is found as function of number of data segments with assumption of the signals' normal distribution.[3] Alternatively non-parametric techniques such as bootstrapping can be used.
Computational models
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Corticomuscular coherence has been simulated in models[4][5] which posit that motor commands are encoded in the spatial pattern of beta band synchronization patterns in motor cortex. Specific cortical oscillation patterns can be spatially filtered by the dendritic arbors of the corticospinal fibers to selectively shape the descending drive to the motoneurons in the spinal cord. Cortical oscillations can thus be translated into steady muscle forces which are maintained for the duration of the oscillation pattern. Although the oscillations serve only as the carrier for the motor command, weak traces of the beta oscillation are still transmitted to the muscle. These traces appear as weak levels of beta band corticomuscular coherence which are consistent with those observed in physiology.[6]
See also
editReferences
edit- ^ Conway, B. A., Halliday, D. M., Farmer, S. F., Shahani, U., Maas, P., Weir, A. I., & Rosenberg, J. R. (1995). Synchronization between motor cortex and spinal motoneuronal pool during the performance of a maintained motor task in man. J Physiol, 489 ( Pt 3), 917–924. http://doi.org/10.1113/jphysiol.1995.sp021104
- ^ Halliday DM, Rosenberg JR, Amjad AM, Breeze P, Conway BA, Farmer SF (1995). "A framework for the analysis of mixed time series/point process data—Theory and application to the study of physiological tremor, single motor unit discharges and electromyograms". Progress in Biophysics and Molecular Biology. 64 (2–3): 237–278. doi:10.1016/S0079-6107(96)00009-0. PMID 8987386.
- ^ Halliday, D. M., & Rosenberg, J. R. (1999). Time and frequency domain analysis of spike train and time series data. In Modern techniques in neuroscience research (pp. 503–543). Springer. Retrieved from http://doi.org/10.1007/978-3-642-58552-4_18
- ^ a b Heitmann S, Boonstra T, Gong P, Breakspear M, Ermentrout B (2015). "The rhythms of steady posture: Motor commands as spatially organized oscillation patterns". Neurocomputing. 170: 3–14. doi:10.1016/j.neucom.2015.01.088.
- ^ Heitmann S, Boonstra T, Breakspear M (2013). "A dendritic mechanism for decoding traveling waves: Principles and applications to motor cortex". PLOS Computational Biology. 9 (10): e1003260. Bibcode:2013PLSCB...9E3260H. doi:10.1371/journal.pcbi.1003260. PMC 3814333. PMID 24204220.
- ^ Baker SN, Kilner JM, Pinches RN, Lemon RN (1999). "The role of synchrony and oscillations in the motor output". Experimental Brain Research. 128 (1): 109–117. doi:10.1007/s002210050825. PMID 10473748. S2CID 13533875.