Biology subjects

Siebert, T.

Publications and source records attributed to Siebert, T..

3 recordsLinked to original sources

bioRxiv2024

The stretch-shortening cycle effect is not associated with cortical or spinal excitability modulations

It is unclear whether cortical and spinal excitability modulations contribute to enhanced SSC performance. Therefore, this study investigated cortical and spinal excitability modulations during and following shortening of stretch-shortening cycle (SSC) contractions compared with pure shortening (SHO) contractions. Participants (N = 18) performed submaximal voluntary plantar flexion contractions while prone on the dynamometer bench. The right foot was strapped onto the dynamometers footplate attachment and the resultant ankle joint torque and crank arm angle were recorded. Cortical and spinal excitability modulations of the soleus muscle were analyzed by eliciting compound muscle actional potentials via electrical nerve stimulation, cervicomedullary motor-evoked potentials (CMEPs) via electrical stimulation of the spinal cord, and motor-evoked potentials (MEPs) via magnetic stimulation of the motor cortex. Mean torque following stretch was significantly increased by 7{+/-}3% (p=0.029) compared with the fixed-end reference (REF) contraction and mean torque during shortening of SSC compared with SHO was significantly increased by 12{+/-}24% (p=0.046). Mean steady-state torque was significantly lower by 13{+/-}3% (p=0.006) and 9{+/-}12% (p=0.011) following SSC compared with REF and SHO, respectively. Mean steady-state torque was not significantly lower following SHO compared with REF (7{+/-}8%, p=0.456). CMEPs and MEPs were also not significantly different during shortening of SSC compared with SHO (p[≥]0.885) or during the steady state of SSC, SHO, and REF (p[≥]0.727). Therefore, our results indicate that SSC performance was not associated with cortical or spinal excitability modulations during or after shortening, but rather driven by mechanical mechanisms triggered during active stretch. Key pointsO_LIA stretch-shortening cycle (SSC) effect of 12% was observed during EMG-matched submaximal voluntary contractions of the human plantar flexors C_LIO_LIThe SSC effect was neither associated with cortical or spinal excitability modulations nor with stretch-reflex activity C_LIO_LIThe SSC effect was likely driven by mechanical mechanisms related to active muscle stretch, which have long-lasting effects during shortening C_LIO_LIResidual force depression following SSC was not attenuated by the long-lasting mechanical mechanisms triggered during active muscle stretch C_LIO_LISteady-state torques were lower following shortening of SSCs versus pure shortening and fixed-end contractions at the same final ankle joint angle, but the torque differences were not correlated with cortical or spinal excitability modulations C_LI

neuroscience↗

bioRxiv2024

A benchmark of muscle models to length changes great and small

Digital human body models are used to simulate injuries that occur as a result of vehicle collisions, vibration, sports, and falls. Given enough time the bodys musculature can generate force, affect the bodys movements, and change the risk of some injuries. The finite-element code LS-DYNA is often used to simulate the movements and injuries sustained by the digital human body models as a result of an accident. In this work, we evaluate the accuracy of the three muscle models in LS-DYNA (MAT_156, EHTMM, and the VEXAT) when simulating a range of experiments performed on isolated muscle: force-length-velocity experiments on maximally and sub-maximally stimulated muscle, active-lengthening experiments, and vibration experiments. The force-length-velocity experiments are included because these conditions are typical of the muscle activity that precedes an accident, while the active-lengthening and vibration experiments mimic conditions that can cause injury. The three models perform similarly during the maximally and sub-maximally activated force-length-velocity experiments, but noticeably differ in response to the active-lengthening and vibration experiments. The VEXAT model is able to generate the enhanced forces of biological muscle during active lengthening, while both the MAT_156 and EHTMM produce too little force. In response to vibration, the stiffness and damping of the VEXAT model closely follows the experimental data while the MAT_156 and EHTMM models differ substantially. The accuracy of the VEXAT model comes from two additional mechanical structures that are missing in the MAT_156 and EHTMM models: viscoelastic cross-bridges, and an active titin filament. To help others build on our work we have made our benchmark simulations and model code publicly available.

bioengineering↗

bioRxiv2023

Muscle Preflex Response to Perturbations in locomotion: In-vitro experiments and simulations with realistic boundary conditions

1Neuromuscular control loops feature substantial communication delays, but mammals run robustly even in the most adverse conditions. In-vivo experiments and computer simulation results suggest that muscles preflex--an immediate mechanical response to a perturbation--could be the critical contributor. Muscle preflexes act within a few milliseconds, an order of magnitude faster than neural reflexes. Their short-lasting activity makes mechanical preflexes hard to quantify in-vivo. Muscle models, on the other hand, require further improvement of their prediction accuracy during the non-standard conditions of perturbed locomotion. Additionally, muscles mechanically adapt by increased damping force. Our study aims to quantify the mechanical preflex work and test its mechanical force adaptation. We performed in-vitro experiments with biological muscle fibers under physiological boundary conditions, which we determined in computer simulations of perturbed hopping. Our findings show that muscles initially resist impacts with a stereotypical stiffness response--identified as short-range stiffness--regardless of the exact perturbation condition. We then observe a velocity adaptation to the force related to the amount of perturbation. The main contributor to the preflex work adaptation is not the force difference but the muscle fiber stretch difference. We find that both muscle stiffness and damping are activity-dependent properties. These results indicate that neural control could tune the preflex properties of muscles in expectation of ground conditions leading to previously inexplicable neuromuscular adaptation speeds.

physiology↗