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Behavioral/Systems/Cognitive Dynamic Reweighting of Visual and Vestibular Cues during
 

Summary: Behavioral/Systems/Cognitive
Dynamic Reweighting of Visual and Vestibular Cues during
Self-Motion Perception
Christopher R. Fetsch,1 Amanda H. Turner,1 Gregory C. DeAngelis,2* and Dora E. Angelaki1*
1Department of Anatomy and Neurobiology, Washington University School of Medicine, Saint Louis, Missouri 63110, and 2Department of Brain and
Cognitive Sciences, Center for Visual Science, University of Rochester, Rochester, New York 14627
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
ofcueintegration.Toaddresstheseissues,wetestedhumanandmonkeysubjectsinaheadingdiscriminationtaskinvolvingvisual(optic
flow) and vestibular (translational motion) cues. The cues were placed in conflict on a subset of trials, and their relative reliability was
variedtoassesstheweightsthatsubjectsgavetoeachcueintheirheadingjudgments.Wefoundthatmonkeyscanrapidlyreweightvisual
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.
Introduction

  

Source: Angelaki, Dora - Department of Anatomy and Neurobiology, Washington University in St. Louis
DeAngelis, Gregory - Department of Brain and Cognitive Sciences, University of Rochester

 

Collections: Biology and Medicine