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History-dependent muscle resistance to stretch remains high after small, posturally-relevant pre-movements.

Brian C HorslenGregory N MilburnKyle P BlumSurabhi N SimhaKenneth S CampbellLena H Ting
Published in: The Journal of experimental biology (2023)
The contributions of intrinsic muscle fiber resistance during mechanical perturbations to standing and other postural behaviors are unclear. Muscle short-range stiffness is known to vary depending on the current level and history of the muscle's activation, as well as the muscle's recent movement history; this property has been referred to as history dependence or muscle thixotropy. However, we currently lack sufficient data about the degree to which muscle stiffness is modulated across posturally-relevant characteristics of muscle stretch and activation. We characterized the history dependence of muscle's resistance to stretch in single, permeabilized, activated, muscle fibers in posturally-relevant stretch conditions and activation levels. We used a classic paired muscle stretch paradigm, varying the amplitude of a "conditioning" triangular stretch-shorten cycle followed by a "test" ramp-and-hold imposed after a variable inter-stretch interval. We tested low (<15%), intermediate (15-50%) and high (>50%) muscle fiber activation levels, evaluating short-range stiffness and total impulse in the test stretch. Muscle fiber resistance to stretch remained high at conditioning amplitudes of <1% L0 and inter-stretch intervals of >1 s, characteristic of healthy standing postural sway. A ∼70% attenuation of muscle resistance to stretch was reached at conditioning amplitudes of >3% L0 and inter-stretch intervals of <0.1s, characteristic of larger, faster postural sway in balance-impaired individuals. The thixotropic changes cannot be predicted solely on muscle force at the time of stretch. Consistent with the disruption of muscle cross-bridges, muscle resistance to stretch during behavior can be substantially attenuated if the prior motion is large enough and/or frequent enough.
Keyphrases
  • skeletal muscle
  • artificial intelligence
  • electronic health record
  • data analysis