Evidence map›Paper›PMID 24466215›Full record

ArticlePloS one2014

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

Carey D Balaban, Sarah W Ogburn, Susan G Warshafsky, Abdul Ahmed, Bill J Yates

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.6field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Article
  3. The gut feeling in motion sickness.Communications biology · 2025
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  12. Effects of the LPAFrontiers in molecular neuroscience · 2019
    Article
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  15. Article
  16. Article
  17. What is nausea? A historical analysis of changing views.Autonomic neuroscience : basic & clinical · 2017
    Review
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Carey D BalabanDepartment of Otolaryngology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America ; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America ; Department of Communication Sciences and Disorders, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America ; Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Sarah W OgburnDepartment of Otolaryngology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Susan G WarshafskyDepartment of Otolaryngology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Abdul AhmedDepartment of Otolaryngology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America ; Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Bill J YatesDepartment of Otolaryngology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America ; Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
University of Pittsburgh · US

Funding

VESTIBULAR REGULATION OF RESPIRATORY MUSCLE ACTIVITYR01DC003732 · NIDCD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BALABAN, CAREY DAVID, YATES, BILL J · 1998 to 2014
$4.0M
NIDCD NIH HHS R01 DC003732NIDCD NIH HHS R01-DC003732
6 · The paper itself

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.

Indexed as

Electric StimulationNeural Networks, ComputerPrincipal Component AnalysisAnimalsCatsFemaleMaleMotion SicknessProto-Oncogene Proteins c-fosVestibular NucleiProto-Oncogene Proteins c-fos

Identifiers

PMID24466215
PMCPMC3900607
OpenAlexW2056981214

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.