2025-10-14 ピッツバーグ大学
Web要約 の発言:
<関連情報>
- https://news.engineering.pitt.edu/these-pitt-researchers-are-making-steady-progress-toward-a-confident-gait/
- https://www.eneuro.org/content/12/5/ENEURO.0343-23.2025/tab-e-letters
歩行速度の違いに対する人間の知覚の特徴づけ:ドリフト拡散モデルからの洞察 Characterizing Human Perception of Speed Differences in Walking: Insights From a Drift Diffusion Model
Marcela Gonzalez-Rubio, Gelsy Torres-Oviedo and Pablo A. Iturralde
eNeuro Published:17 April 2025
DOI:https://doi.org/10.1523/ENEURO.0343-23.2025
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.
