Literature DB >> 15647398

Muscle activity determined by cosine tuning with a nontrivial preferred direction during isometric force exertion by lower limb.

Daichi Nozaki1, Kimitaka Nakazawa, Masami Akai.   

Abstract

We investigated how the CNS selects a unique muscle activation pattern under a redundant situation resulting from the existence of bi-articular muscles. Surface electromyographic (EMG) activity was recorded from eight lower limb muscles while 11 subjects were exerting isometric knee and hip joint torque simultaneously (T(k) and T(h), respectively. Extension torque was defined as positive). The knee joint was kept at either 90 or 60 degrees. Various combinations of torque were imposed on both joints by pulling a cable attached to an ankle brace with approximately three levels of isometric force in 16 directions. The distribution of the data in the three-dimensional plot (muscle activation level quantified by the root mean squared value of EMG vs. T(k) and T(h)) demonstrates that the muscle activation level M can be approximated by a single model as M = left flooraT(k) + bT(h) right floor where left floorx right floor = max (x,0) and a and b are constants. The percentage of variance explained by this model averaged over all muscles was 82.3 +/- 14.0% (mean +/- SD), indicating that the degree of fit of the data to the plane was high. This model suggests that the CNS uses a cosine tuning function on the torque plane (T(k), T(h)) to recruit muscles. Interestingly, the muscle's preferred direction (PD) defined as the direction where it is maximally active on the torque plane deviated from its own mechanical pulling direction (MD). This deviation was apparent in the mono-articular knee extensor (MD = 0 degrees , whereas PD = 14.1 +/- 3.7 degrees for vastus lateralis) and in the mono-articular hip extensor (MD = 90 degrees, whereas PD = 53.4 +/- 6.4 degrees for gluteus maximus). Such misalignment between MD and PD indicates that the mono-articular muscle's activation level depends on the torque of the joint that it does not span. Practical implications of this observation for the motor control studies were discussed. We also demonstrated that the observed shift from the MD to the PD is plausible in the configuration of our musculo-skeletal system and that the experimental results are likely to be explained by the CNS process to minimize the variability of the endpoint force vector under the existence of signal-dependent noise.

Entities:  

Mesh:

Year:  2005        PMID: 15647398     DOI: 10.1152/jn.00960.2004

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  13 in total

1.  The mechanical actions of muscles predict the direction of muscle activation during postural perturbations in the cat hindlimb.

Authors:  Claire F Honeycutt; T Richard Nichols
Journal:  J Neurophysiol       Date:  2013-12-04       Impact factor: 2.714

2.  Optimal feedback control to describe multiple representations of primary motor cortex neurons.

Authors:  Yuki Ueyama
Journal:  J Comput Neurosci       Date:  2017-06-01       Impact factor: 1.621

3.  Modularity speeds up motor learning by overcoming mechanical bias in musculoskeletal geometry.

Authors:  Shota Hagio; Motoki Kouzaki
Journal:  J R Soc Interface       Date:  2018-10-10       Impact factor: 4.118

4.  Cosine tuning determines plantarflexors' activities during human upright standing and is affected by incomplete spinal cord injury.

Authors:  Kai Lon Fok; Jae W Lee; Janelle Unger; Katherine Chan; Daichi Nozaki; Kristin E Musselman; Kei Masani
Journal:  J Neurophysiol       Date:  2020-05-13       Impact factor: 2.714

5.  Neck muscle biomechanics and neural control.

Authors:  Jason B Fice; Gunter P Siegmund; Jean-Sébastien Blouin
Journal:  J Neurophysiol       Date:  2018-04-18       Impact factor: 2.714

Review 6.  The coordination of movement: optimal feedback control and beyond.

Authors:  Jörn Diedrichsen; Reza Shadmehr; Richard B Ivry
Journal:  Trends Cogn Sci       Date:  2009-12-11       Impact factor: 20.229

7.  Changes in muscle and joint coordination in learning to direct forces.

Authors:  Christopher J Hasson; Graham E Caldwell; Richard E A van Emmerik
Journal:  Hum Mov Sci       Date:  2008-04-10       Impact factor: 2.161

8.  Cerebellar damage diminishes long-latency responses to multijoint perturbations.

Authors:  Isaac Kurtzer; Paxson Trautman; Russell J Rasquinha; Nasir H Bhanpuri; Stephen H Scott; Amy J Bastian
Journal:  J Neurophysiol       Date:  2013-02-06       Impact factor: 2.714

9.  Differences in postural sway among healthy adults are associated with the ability to perform steady contractions with leg muscles.

Authors:  Leah A Davis; Stephen P Allen; Landon D Hamilton; Alena M Grabowski; Roger M Enoka
Journal:  Exp Brain Res       Date:  2020-01-20       Impact factor: 1.972

10.  Learning with slight forgetting optimizes sensorimotor transformation in redundant motor systems.

Authors:  Masaya Hirashima; Daichi Nozaki
Journal:  PLoS Comput Biol       Date:  2012-06-28       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.