Center of mass states render multijoint torques throughout standing balance recovery

Successful reactive balance control requires coordinated modulation of hip, knee, and ankle torques. Stabilizing joint torques arise from neurally-mediated feedforward tonic muscle activation that modulates muscle short-range stiffness, which provides instantaneous "mechanical feedback" to the perturbation. In contrast, neural feedback pathways activate muscles in response to sensory input, generating joint torques after a delay. However, the specific contributions from feedforward and feedback pathways to the balance-correcting torque response are poorly understood. As feedforward- and feedback-mediated torque responses to balance perturbations act at different delays, we modified the sensorimotor response model (SRM), previously used to analyze the muscle activation response, to reconstruct joint torques using parallel feedback loops. Each loop is driven by the same information, center of mass (CoM) kinematics, but each loop has an independent delay. We evaluated whether a torque-SRM could decompose the reactive torques during balance-correcting responses to backward support surface translations at four magnitudes into the instantaneous "mechanical feedback" torque modulated by feedforward neural commands before the perturbation and neurally-delayed feedback components. The SRM accurately reconstructed torques at the hip, knee, and ankle, across all perturbation magnitudes (<i>R</i><sup>2</sup> > 0.84 and VAF > 0.83). Moreover, the hip and knee exhibited feedforward and feedback components, while the ankle only exhibited feedback components. The lack of a feedforward component at the ankle may occur because the compliance of the Achilles tendon attenuates muscle short-range stiffness. Our model may provide a framework for evaluating changes in the feedforward and feedback contributions to balance that occur due to aging, injury, or disease.<b>NEW & NOTEWORTHY</b> Reactive balance control requires coordination of neurally-mediated feedforward and feedback pathways to generate stabilizing joint torques at the hip, knee, and ankle. Using a sensorimotor response model, we decomposed reactive joint torques into feedforward and feedback contributions based on delays relative to the center of mass kinematics. Responses across joints were driven by the same signals, but contributions from feedforward versus feedback pathways differed, likely due to differences in musculotendon properties between proximal and distal muscles.

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Publication Details

Journal
Journal of Neurophysiology
Published
2024-12-11
DOI
https://doi.org/10.1152/jn.00367.2024
Citations
3
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.55

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article

Center of mass states render multijoint torques throughout standing balance recovery

Kristen L. Jakubowski, Lena H. Ting, Giovanni Martino, Owen N. Beck et al.
3 citations
Journal of Neurophysiology
Muscle activation and electromyography studies
0.55
article

Center of mass states render multijoint torques throughout standing balance recovery

Kristen L. Jakubowski, Lena H. Ting, Giovanni Martino, Owen N. Beck, Gregory S. Sawicki
article en
3 citations

Abstract

Successful reactive balance control requires coordinated modulation of hip, knee, and ankle torques. Stabilizing joint torques arise from neurally-mediated feedforward tonic muscle activation that modulates muscle short-range stiffness, which provides instantaneous "mechanical feedback" to the perturbation. In contrast, neural feedback pathways activate muscles in response to sensory input, generating joint torques after a delay. However, the specific contributions from feedforward and feedback pathways to the balance-correcting torque response are poorly understood. As feedforward- and feedback-mediated torque responses to balance perturbations act at different delays, we modified the sensorimotor response model (SRM), previously used to analyze the muscle activation response, to reconstruct joint torques using parallel feedback loops. Each loop is driven by the same information, center of mass (CoM) kinematics, but each loop has an independent delay. We evaluated whether a torque-SRM could decompose the reactive torques during balance-correcting responses to backward support surface translations at four magnitudes into the instantaneous "mechanical feedback" torque modulated by feedforward neural commands before the perturbation and neurally-delayed feedback components. The SRM accurately reconstructed torques at the hip, knee, and ankle, across all perturbation magnitudes (<i>R</i><sup>2</sup> > 0.84 and VAF > 0.83). Moreover, the hip and knee exhibited feedforward and feedback components, while the ankle only exhibited feedback components. The lack of a feedforward component at the ankle may occur because the compliance of the Achilles tendon attenuates muscle short-range stiffness. Our model may provide a framework for evaluating changes in the feedforward and feedback contributions to balance that occur due to aging, injury, or disease.<b>NEW & NOTEWORTHY</b> Reactive balance control requires coordination of neurally-mediated feedforward and feedback pathways to generate stabilizing joint torques at the hip, knee, and ankle. Using a sensorimotor response model, we decomposed reactive joint torques into feedforward and feedback contributions based on delays relative to the center of mass kinematics. Responses across joints were driven by the same signals, but contributions from feedforward versus feedback pathways differed, likely due to differences in musculotendon properties between proximal and distal muscles.

Journal of NeurophysiologyVol. 133(1)
Georgia Institute of Technology (US), Florida Institute for Human and Machine Cognition (US), University of Padua (IT), Emory University (US), The Wallace H. Coulter Department of Biomedical Engineering (US), The University of Texas at Austin (US)
National Institute on Aging, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Openalex Percentile: Top 36%
Muscle activation and electromyography studies
0.55
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