Characterizing Human Perception of Speed Differences in Walking: Insights From a Drift Diffusion Model

Despite its central role in the proper functioning of the motor system, sensation has been less studied than motor outputs in sensorimotor adaptation paradigms. This is likely due to the difficulty of measuring sensation non-invasively: while motor outputs have easily observable consequences, sensation is inherently an internal variable of the motor system. In this study, we investigated how well participants can sense relevant sensory stimuli that induce locomotor adaptation. We addressed this question with a split-belt treadmill, which moves the legs at different speeds. We used a two-alternative forced-choice paradigm with multiple repetitions of various speed differences considering the probabilistic nature of perceptual responses. We found that the participants correctly identified a speed difference of 49.7 mm/s in 75% of the trials when walking at 1.05 m/s (i.e., 4.7% Weber Fraction). To gain insight into the perceptual process in walking, we applied a drift-diffusion model (DDM) relating the participants' identification of speed difference (i.e., stimulus identification) and their response time during walking. The implemented DDM was able to predict participants' stimulus identification for all speed differences by simply using the recorded reaction times (RTs) to fit a single set of model parameters. Taken together, our results indicate that individuals can accurately identify smaller speed differences than previously reported and that participants' stimulus perception follows the evidence accumulation process outlined by drift diffusion models, conventionally used for short-latency, static sensory tasks, rather than long-latency, and motor tasks such as walking.

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Publication Details

Journal
eNeuro
Published
2025-04-17
DOI
https://doi.org/10.1523/eneuro.0343-23.2025
Citations
1
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
1.43

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article

Characterizing Human Perception of Speed Differences in Walking: Insights From a Drift Diffusion Model

Pablo A. Iturralde, Gelsy Torres‐Oviedo, Marcela Gonzalez-Rubio
1 citations
eNeuro
Motor Control and Adaptation
1.43
article

Characterizing Human Perception of Speed Differences in Walking: Insights From a Drift Diffusion Model

Pablo A. Iturralde, Gelsy Torres‐Oviedo, Marcela Gonzalez-Rubio
article en
1 citations

Abstract

Despite its central role in the proper functioning of the motor system, sensation has been less studied than motor outputs in sensorimotor adaptation paradigms. This is likely due to the difficulty of measuring sensation non-invasively: while motor outputs have easily observable consequences, sensation is inherently an internal variable of the motor system. In this study, we investigated how well participants can sense relevant sensory stimuli that induce locomotor adaptation. We addressed this question with a split-belt treadmill, which moves the legs at different speeds. We used a two-alternative forced-choice paradigm with multiple repetitions of various speed differences considering the probabilistic nature of perceptual responses. We found that the participants correctly identified a speed difference of 49.7 mm/s in 75% of the trials when walking at 1.05 m/s (i.e., 4.7% Weber Fraction). To gain insight into the perceptual process in walking, we applied a drift-diffusion model (DDM) relating the participants' identification of speed difference (i.e., stimulus identification) and their response time during walking. The implemented DDM was able to predict participants' stimulus identification for all speed differences by simply using the recorded reaction times (RTs) to fit a single set of model parameters. Taken together, our results indicate that individuals can accurately identify smaller speed differences than previously reported and that participants' stimulus perception follows the evidence accumulation process outlined by drift diffusion models, conventionally used for short-latency, static sensory tasks, rather than long-latency, and motor tasks such as walking.

eNeuroVol. 12(5)
University of Pittsburgh (US), Center for the Neural Basis of Cognition (US), Universidad Católica del Uruguay (UY)
National Science Foundation
Openalex Percentile: Top 21%
Motor Control and Adaptation
1.43
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