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Identification of neural networks that contribute to motion sickness through principal components analysis of fos labeling induced by galvanic vestibular stimulation

Balaban, CD and Ogburn, SW and Warshafsky, SG and Ahmed, A and Yates, BJ (2014) Identification of neural networks that contribute to motion sickness through principal components analysis of fos labeling induced by galvanic vestibular stimulation. PLoS ONE, 9 (1).

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Abstract

Motion sickness is a complex condition that includes both overt signs (e.g., vomiting) and more covert symptoms (e.g., anxiety and foreboding). The neural pathways that mediate these signs and symptoms are yet to identified. This study mapped the distribution of c-fos protein (Fos)-like immunoreactivity elicited during a galvanic vestibular stimulation paradigm that is known to induce motion sickness in felines. A principal components analysis was used to identify networks of neurons activated during this stimulus paradigm from functional correlations between Fos labeling in different nuclei. This analysis identified five principal components (neural networks) that accounted for greater than 95% of the variance in Fos labeling. Two of the components were correlated with the severity of motion sickness symptoms, and likely participated in generating the overt signs of the condition. One of these networks included neurons in locus coeruleus, medial, inferior and lateral vestibular nuclei, lateral nucleus tractus solitarius, medial parabrachial nucleus and periaqueductal gray. The second included neurons in the superior vestibular nucleus, precerebellar nuclei, periaqueductal gray, and parabrachial nuclei, with weaker associations of raphe nuclei. Three additional components (networks) were also identified that were not correlated with the severity of motion sickness symptoms. These networks likely mediated the covert aspects of motion sickness, such as affective components. The identification of five statistically independent component networks associated with the development of motion sickness provides an opportunity to consider, in network activation dimensions, the complex progression of signs and symptoms that are precipitated in provocative environments. Similar methodology can be used to parse the neural networks that mediate other complex responses to environmental stimuli. © 2014 Balaban et al.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Balaban, CDCBALABAN@pitt.eduCBALABAN
Ogburn, SWsaw81@pitt.eduSAW81
Warshafsky, SG
Ahmed, A
Yates, BJBYATES@pitt.eduBYATES0000-0001-6819-097X
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorSiegel, AllanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 23 January 2014
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 9
Number: 1
DOI or Unique Handle: 10.1371/journal.pone.0086730
Schools and Programs: Dietrich School of Arts and Sciences > Communication Science and Disorders
Dietrich School of Arts and Sciences > Neuroscience
School of Medicine > Neurobiology
School of Medicine > Otolaryngology
Swanson School of Engineering > Bioengineering
Refereed: Yes
Date Deposited: 17 Jun 2014 15:43
Last Modified: 15 May 2024 10:55
URI: http://d-scholarship.pitt.edu/id/eprint/21881

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