Human standing balance relies on self-motion estimates that are used by the nervous system to detect unexpected movements and enable corrective responses and adaptations in control. These estimates must accommodate for inherent delays in sensory and motor pathways. Here, we used a robotic system to simulate human standing in the anteroposterior direction about the ankles and impose sensorimotor delays into the control of balance. Imposed delays destabilized standing, but through training, participants adapted and re-learned to balance with the delays. Before training, imposed delays attenuated vestibular contributions to balance and triggered perceptions of unexpected standing motion, suggesting increased uncertainty in the internal self-motion estimates. After training, vestibular contributions partially returned to baseline levels and larger delays were needed to evoke perceptions of unexpected standing motion. Through learning, the nervous system accommodates balance sensorimotor delays by causally linking whole-body sensory feedback (initially interpreted as imposed motion) to self-generated balance motor commands.
Bibliographical noteFunding Information:
participated in this research. This study was funded by the Natural Sciences and Engineering
Research Council of Canada, grant number RGPIN-2020-05438, awarded to Jean-Sébastien
Engineering Research Council of Canada. Patrick A Forbes received funding from the
Blouin. Brandon G Rasman received graduate student funding from the Natural Sciences and
The authors thank Hasrit Sidhu for his help with data collection and all the participants who participated in this research. This study was funded by the Natural Sciences and Engineering Research Council of Canada, grant number RGPIN-2020-05438, awarded to Jean-S?bastien Blouin. Brandon G Rasman received graduate student funding from the Natural Sciences and Engineering Research Council of Canada. Patrick A Forbes received funding from the Netherlands Organization for Scientific Research (NWO #016. Veni. 188.049). Ryan M Peters was funded by a Natural Sciences and Engineering Research Council Grant to J Timothy Inglis.
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