Journal
CORTEX
Volume 78, Issue -, Pages 55-69Publisher
ELSEVIER MASSON, CORPORATION OFFICE
DOI: 10.1016/j.cortex.2016.02.004
Keywords
Vestibular cortex; Parietal operculum; Time-to-contact; Subjective visual vertical; Interception; Stroke
Funding
- Italian Ministry of Health [RF-10.057]
- Italian Ministry of University and Research (PRIN) [2010MEFNF7_002]
- Italian Space Agency (COREA) [2013-084-R.0]
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Rich behavioral evidence indicates that the brain estimates the visual direction and acceleration of gravity quite accurately, and the underlying mechanisms have begun to be unraveled. While the neuroanatomical substrates of gravity direction processing have been studied extensively in brain-damaged patients, to our knowledge no such study exists for the processing of visual gravitational motion. Here we asked 31 stroke patients to intercept a virtual ball moving along the vertical under either natural gravity or artificial reversed gravity. Twenty-seven of them also aligned a luminous bar to the vertical direction (subjective visual vertical, SVV). Using voxel-based lesion-symptom mapping as well as lesion subtraction analysis, we found that lesions mainly centered on the posterior insula are associated with greater deviations of SW, consistent with several previous studies. Instead, lesions mainly centered on the parietal operculum decrease the ability to discriminate natural from unnatural gravitational acceleration with a timed motor response in the interception task. Both the posterior insula and the parietal operculum belong to the vestibular cortex, and presumably receive multisensory information about the gravity vector. We speculate that an internal model estimating the effects of gravity on visual objects is constructed by transforming the vestibular estimates of mechanical gravity, which are computed in the brainstem and cerebellum, into internalized estimates of virtual gravity, which are stored in the cortical vestibular network. The present lesion data suggest a specific role for the parietal operculum in detecting the mismatch between predictive signals from the internal model and the online visual signals. (C) 2016 Elsevier Ltd. All rights reserved.
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