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A single muscle's multifunctional control potential of body dynamics for postural control and running
Author(s) -
Simon Sponberg,
Andrew J. Spence,
Chris H. Mullens,
Robert J. Full
Publication year - 2011
Publication title -
philosophical transactions of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.753
H-Index - 272
eISSN - 1471-2970
pISSN - 0962-8436
DOI - 10.1098/rstb.2010.0367
Subject(s) - kinematics , dynamics (music) , context (archaeology) , computer science , artificial neural network , motor control , acceleration , work (physics) , nonlinear system , control theory (sociology) , accelerometer , control (management) , artificial intelligence , physics , neuroscience , psychology , acoustics , classical mechanics , biology , thermodynamics , quantum mechanics , operating system , paleontology
A neuromechanical approach to control requires understanding how mechanics alters the potential of neural feedback to control body dynamics. Here, we rewrite activation of individual motor units of a behaving animal to mimic the effects of neural feedback without concomitant changes in other muscles. We target a putative control muscle in the cockroach, Blaberus discoidalis (L.), and simultaneously capture limb and body dynamics through high-speed videography and a micro-accelerometer backpack. We test four neuromechanical control hypotheses. We supported the hypothesis that mechanics linearly translates neural feedback into accelerations and rotations during static postural control. However, during running, the same neural feedback produced a nonlinear acceleration control potential restricted to the vertical plane. Using this, we reject the hypothesis from previous work that this muscle acts primarily to absorb energy from the body. The conversion of the control potential is paralleled by nonlinear changes in limb kinematics, supporting the hypothesis that significant mechanical feedback filters the graded neural feedback for running control. Finally, we insert the same neural feedback signal but at different phases in the dynamics. In this context, mechanical feedback enables turning by changing the timing and direction of the accelerations produced by the graded neural feedback.

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