Path integration is a widely-studied sensorimotor computation to infer latent dynamical states. How different sensory pathways and movement dynamics constrain this computation is unclear. 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 was highly sensitive to the underlying control dynamics, a result that was well explained by a bias in the dynamics estimation. This work demonstrates that people need an accurate internal model of control dynamics when navigating in volatile environments.
bioRxiv Subject Collection: Neuroscience