Intermuscular coherence

Intermuscular Coherence is a measure to quantify correlations between the activity of two muscles, which is often assessed using electromyography. The correlations in muscle activity are quantified in frequency domain,[1] and therefore referred to as intermuscular coherence.[2]

History

The synchronisation of motor units of a single muscle in animals and humans are known for decades. The early studies that investigated the relationship of EMG activity used time-domain cross-correlation to quantify common input.[3][4] The explicit notion of presence of synchrony between motor units of two different muscles was reported at a later time.[5] In the 1990s, coherence analysis was introduced to examine in frequency content of common input.[2]

Physiology

Intermuscular coherence can be used to investigate the neural circuitry involved in motor control. Correlated muscle activity indicates common input to the motor unit pools of both muscles[6][7] and reflects shared neural pathways (including cortical, subcortical and spinal) that contribute to muscle activity and movement.[8] The strength of intermuscular coherence is dependent on the relationship between muscles and is generally stronger between muscle pairs that are anatomically and functionally closely related.[9][10] Intermuscular coherence can therefore be used to identify impairments in motor pathways.[11][12]

See also
  • Corticomuscular coherence
  • Corticocortical coherence

References
  1. Rosenberg, J. R., Amjad, A. M., Breeze, P., Brillinger, D. R., & Halliday, D. M. (1989). The Fourier approach to the identification of functional coupling between neuronal spike trains. Progress in Biophysics and Molecular Biology, 53(1), 1–31.
  2. Farmer, S. F., Bremner, F. D., Halliday, D. M., Rosenberg, J. R., & Stephens, J. A. (1993). The frequency content of common synaptic inputs to motoneurones studied during voluntary isometric contraction in man. The Journal of Physiology, 470(1), 127–155
  3. Person, R. S.; Kudina, L. P. (1968). "Cross-correlation of electromyograms showing interference patterns". Electroencephalography and Clinical Neurophysiology. 25 (1): 58–68. doi:10.1016/0013-4694(68)90087-4. ISSN 0013-4694. PMID 4174784.
  4. Kirkwood, P. A.; Sears, T. A. (1978). "The synaptic connexions to intercostal motoneurones as revealed by the average common excitation potential". The Journal of Physiology. 275: 103–134. doi:10.1113/jphysiol.1978.sp012180. ISSN 0022-3751. PMC 1282535. PMID 633094.
  5. Bremner, F. D., Baker, J. R., & Stephens, J. A. (1991). Correlation between the discharges of motor units recorded from the same and from different finger muscles in man. The Journal of Physiology, 432(1), 355–380. http://doi.org/10.1113/jphysiol.1991.sp018389
  6. Negro, Francesco; Farina, Dario (2011-01-28). "Linear transmission of cortical oscillations to the neural drive to muscles is mediated by common projections to populations of motoneurons in humans". The Journal of Physiology. 589 (3): 629–637. doi:10.1113/jphysiol.2010.202473. ISSN 0022-3751. PMC 3055547. PMID 21135042.
  7. Boonstra, Tjeerd W.; Breakspear, Michael (2012). "Neural mechanisms of intermuscular coherence: implications for the rectification of surface electromyography". Journal of Neurophysiology. 107 (3): 796–807. doi:10.1152/jn.00066.2011. ISSN 1522-1598. PMID 22072508.
  8. Boonstra, Tjeerd W.; Farmer, Simon F.; Breakspear, Michael (2016). "Using Computational Neuroscience to Define Common Input to Spinal Motor Neurons". Frontiers in Human Neuroscience. 10: 313. doi:10.3389/fnhum.2016.00313. ISSN 1662-5161. PMC 4914567. PMID 27445753.
  9. Gibbs, J.; Harrison, L. M.; Stephens, J. A. (1995-05-15). "Organization of inputs to motoneurone pools in man". The Journal of Physiology. 485 ( Pt 1): 245–256. doi:10.1113/jphysiol.1995.sp020727. ISSN 0022-3751. PMC 1157987. PMID 7658378.
  10. Kerkman, Jennifer N.; Daffertshofer, Andreas; Gollo, Leonardo L.; Breakspear, Michael; Boonstra, Tjeerd W. (2018). "Network structure of the human musculoskeletal system shapes neural interactions on multiple time scales". Science Advances. 4 (6): eaat0497. Bibcode:2018SciA....4..497K. doi:10.1126/sciadv.aat0497. ISSN 2375-2548. PMC 6021138. PMID 29963631.
  11. Nishimura, Yukio; Morichika, Yosuke; Isa, Tadashi (2009-03-01). "A subcortical oscillatory network contributes to recovery of hand dexterity after spinal cord injury". Brain. 132 (3): 709–721. doi:10.1093/brain/awn338. ISSN 0006-8950. PMC 2664448. PMID 19155271.
  12. Fisher, Karen M.; Zaaimi, Boubker; Williams, Timothy L.; Baker, Stuart N.; Baker, Mark R. (2012-09-01). "Beta-band intermuscular coherence: a novel biomarker of upper motor neuron dysfunction in motor neuron disease". Brain. 135 (9): 2849–2864. doi:10.1093/brain/aws150. ISSN 0006-8950. PMC 3437020. PMID 22734124.


This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.