Abstract
Path integration is a sensorimotor computation that can be used to infer latent dynamical states by integrating self-motion cues. We studied the influence of sensory observation (visual/ vestibular) and latent control dynamics (velocity/acceleration) on human path integration using a novel motion-cueing algorithm. Sensory modality and control dynamics were both varied randomly across trials, as participants controlled a joystick to steer to a memorized target location in virtual reality. Visual and vestibular steering cues allowed comparable accuracies only when participants controlled their acceleration, suggesting that vestibular signals, on their own, fail to support accurate path integration in the absence of sustained acceleration. Nevertheless, performance in all conditions reflected a failure to fully adapt to changes in the underlying control dynamics, a result that was well explained by a bias in the dynamics estimation. This work demonstrates how an incor-rect internal model of control dynamics affects navigation in volatile environments in spite of contin-uous sensory feedback.
Original language | English (US) |
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Article number | e63405 |
Journal | eLife |
Volume | 11 |
DOIs | |
State | Published - Feb 2022 |
ASJC Scopus subject areas
- General Neuroscience
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology