Multisensory processing in spatial orientation: An inverse probabilistic approach
Number of pages
SourceThe Journal of Neuroscience, 31, 14, (2011), pp. 5365-5377
Article / Letter to editor
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SW OZ DCC CO
The Journal of Neuroscience
SubjectAction, intention, and motor control; DI-BCB_DCC_Theme 2: Perception, Action and Control
Most evidence that the brain uses Bayesian inference to integrate noisy sensory signals optimally has been obtained by showing that the noise levels in each modality separately can predict performance in combined conditions. Such a forward approach is difficult to implement when the various signals cannot be measured in isolation, as in spatial orientation, which involves the processing of visual, somatosensory, and vestibular cues. Instead, we applied an inverse probabilistic approach, based on optimal observer theory. Our goal was to investigate whether the perceptual differences found when probing two different states-body-in-space and head-in-space orientation-can be reconciled by a shared scheme using all available sensory signals. Using a psychometric approach, seven human subjects were tested on two orientation estimates at tilts < 120 degrees: perception of body tilt [subjective body tilt (SBT)] and perception of visual vertical [subjective visual vertical (SVV)]. In all subjects, the SBT was more accurate than the SVV, which showed substantial systematic errors for tilt angles beyond 60 degrees. Variability increased with tilt angle in both tasks, but was consistently lower in the SVV. The sensory integration model fitted both datasets very nicely. A further experiment, in which supine subjects judged their head orientation relative to the body, independently confirmed the predicted head-on-body noise by the model. Model predictions based on the derived noise properties from the various modalities were also consistent with previously published deficits in vestibular and somatosensory patients. We conclude that Bayesian computations can account for the typical differences in spatial orientation judgments associated with different task requirements.
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