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Updated: Nov 6, 2025
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Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
Published on: August 23, 2017
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Time-series changes in intramuscular coherence associated with split-belt treadmill adaptation in humans
Atsushi Oshima1, Taku Wakahara2,3, Yasuo Nakamura2
1Graduate School of Health and Sports Science, Doshisha University, Kyoto, Japan.
Experimental Brain Research
|May 7, 2021
Summary
Locomotor adaptation involves changes in muscle coordination. This study shows that during split-belt treadmill walking, cortical control of the tibialis anterior muscle weakens as the body adapts to new walking patterns.
Area of Science:
- Neuroscience
- Biomechanics
- Motor Control
Background:
- Humans exhibit adaptable walking patterns, often studied using split-belt treadmills.
- Previous research focused on spatiotemporal gait changes, leaving intramuscular coherence during adaptation less understood.
Purpose of the Study:
- To investigate time-series changes in intramuscular coherence within the tibialis anterior muscle during and after split-belt walking adaptation.
- To explore the role of cortical involvement in adapting locomotor patterns.
Main Methods:
- Utilized coherence analysis on paired surface electromyography (EMG) signals from the tibialis anterior muscle in twelve healthy males.
- Recorded EMG data during split-belt treadmill walking and subsequent normal walking to assess intramuscular coherence in beta and gamma frequency bands.
Main Results:
- Intramuscular coherence in the beta and gamma bands of the tibialis anterior muscle in the slow leg decreased gradually during split-belt walking.
- Coherence in the fast leg's tibialis anterior muscle temporarily increased during the initial minute of re-adapting to normal walking post-split-belt exposure.
Conclusions:
- Cortical involvement in tibialis anterior muscle activity diminishes as individuals adapt to altered walking patterns on a split-belt treadmill.
- Upon returning to normal walking, cortical involvement may transiently increase before returning to baseline levels, suggesting a dynamic neural adjustment process.
