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Updated: Jun 17, 2026

Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane
Published on: August 22, 2025
Dynamic reweighting of visual and vestibular cues during self-motion perception
Christopher R Fetsch1, Amanda H Turner, Gregory C DeAngelis
1Department of Anatomy and Neurobiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA.
None:
The perception of self-motion direction, or heading, relies on integration of multiple sensory cues, especially from the visual and vestibular systems. However, the reliability of sensory information can vary rapidly and unpredictably, and it remains unclear how the brain integrates multiple sensory signals given this dynamic uncertainty. Human psychophysical studies have shown that observers combine cues by weighting them in proportion to their reliability, consistent with statistically optimal integration schemes derived from Bayesian probability theory. Remarkably, because cue reliability is varied randomly across trials, the perceptual weight assigned to each cue must change from trial to trial. Dynamic cue reweighting has not been examined for combinations of visual and vestibular cues, nor has the Bayesian cue integration approach been applied to laboratory animals, an important step toward understanding the neural basis of cue integration. To address these issues, we tested human and monkey subjects in a heading discrimination task involving visual (optic flow) and vestibular (translational motion) cues. The cues were placed in conflict on a subset of trials, and their relative reliability was varied to assess the weights that subjects gave to each cue in their heading judgments. We found that monkeys can rapidly reweight visual and vestibular cues according to their reliability, the first such demonstration in a nonhuman species. However, some monkeys and humans tended to over-weight vestibular cues, inconsistent with simple predictions of a Bayesian model. Nonetheless, our findings establish a robust model system for studying the neural mechanisms of dynamic cue reweighting in multisensory perception.
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