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Auditory induced vestibular (otolithic) processing revealed by an independent component analysis: an fMRI parametric analysis

J Neurol. 2017 Mar 7. doi: 10.1007/s00415-017-8430-2. [Epub ahead of print]

Authors/Editors: Oh SY, Boegle R, Ertl M, Eulenburg PZ, Stephan T, Dieterich M.
Publication Date: 2017



Neuroimaging studies in humans using galvanic or caloric vestibular stimulation revealed widely distributed cortical activations in a bilateral network located in the insular and retroinsular region, superior temporal gyrus, inferior parietal lobule, somatosensory cortex, cingulate gyrus, frontal cortex, and hippocampus, which subserve higher vestibular cognitive functions [1, 2, 3, 4]. Multisensory convergence and sensorimotor integration are important aspects for the mediation of higher vestibular cognitive functions at cortical level. Sounds with specific characteristics are able to induce otolith stimulation as used for cervical and ocular vestibular evoked myogenic potentials (VEMPs) in the routine neurootological examination. General problems when trying to elicit a vestibular response with sound pressure stimulation are the concurrent stimulation of the auditory system, and the differentiation of auditory from vestibular (otolith) responses and from auditory-vestibular interactions. To overcome this auditory-confounding problem we used a parametric sound pressure stimulation design that takes into account each subject’s vestibular stimulation threshold. With this parametric design approach, we applied independent component analysis (ICA) which is a data-driven method based on the assumption that the causes of responses are statistically independent sources (spatial patterns) that are allowed to mix linearly. This approach does not assume a temporal model and allows us to segregate functional elements into separate maps, which may even overlap spatially and correlate temporally. Therefore, ICA is useful for decomposing activation during complex tasks where multiple operations occur simultaneously, and each component can provide a grouping of brain activity into regions that share the same response pattern, thus providing a natural measure of functional connectivity.

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