Literature DB >> 26790485

EEG Alpha and Gamma Modulators Mediate Motion Sickness-Related Spectral Responses.

Shang-Wen Chuang1, Chun-Hsiang Chuang1,2, Yi-Hsin Yu1, Jung-Tai King1, Chin-Teng Lin1,2.   

Abstract

Motion sickness (MS) is a common experience of travelers. To provide insights into brain dynamics associated with MS, this study recruited 19 subjects to participate in an electroencephalogram (EEG) experiment in a virtual-reality driving environment. When riding on consecutive winding roads, subjects experienced postural instability and sensory conflict between visual and vestibular stimuli. Meanwhile, subjects rated their level of MS on a six-point scale. Independent component analysis (ICA) was used to separate the filtered EEG signals into maximally temporally independent components (ICs). Then, reduced logarithmic spectra of ICs of interest, using principal component analysis, were decomposed by ICA again to find spectrally fixed and temporally independent modulators (IMs). Results demonstrated that a higher degree of MS accompanied increased activation of alpha (r = 0.421) and gamma (r =0.478) IMs across remote-independent brain processes, covering motor, parietal and occipital areas. This co-modulatory spectral change in alpha and gamma bands revealed the neurophysiological demand to regulate conflicts among multi-modal sensory systems during MS.

Entities:  

Keywords:  EEG; alpha; co-modulation; gamma; motion sickness; sensory conflict theory

Mesh:

Year:  2016        PMID: 26790485     DOI: 10.1142/S0129065716500076

Source DB:  PubMed          Journal:  Int J Neural Syst        ISSN: 0129-0657            Impact factor:   5.866


  7 in total

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Authors:  Carey D Balaban; Bill J Yates
Journal:  Auton Neurosci       Date:  2016-07-16       Impact factor: 3.145

2.  Temporal Dynamics of Visually Induced Motion Perception and Neural Evidence of Alterations in the Motion Perception Process in an Immersive Virtual Reality Environment.

Authors:  Min-Hee Ahn; Jeong Hye Park; Hanjae Jeon; Hyo-Jeong Lee; Hyung-Jong Kim; Sung Kwang Hong
Journal:  Front Neurosci       Date:  2020-11-19       Impact factor: 4.677

3.  Changes in Electroencephalography Activity of Sensory Areas Linked to Car Sickness in Real Driving Conditions.

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4.  Multi-Dimensional and Objective Assessment of Motion Sickness Susceptibility Based on Machine Learning.

Authors:  Cong-Cong Li; Zhuo-Ru Zhang; Yu-Hui Liu; Tao Zhang; Xu-Tao Zhang; Han Wang; Xiao-Cheng Wang
Journal:  Front Neurol       Date:  2022-04-01       Impact factor: 4.086

Review 5.  Detection of unrecognized spatial disorientation: A theoretical perspective.

Authors:  Chenru Hao; Li Cheng; Lisha Guo; Ruibin Zhao; Yanru Wu; Xiuyuan Li; Ziqiang Chi; Jingjing Zhang; Xu Liu; Xiaohan Ma; Anqi Wang; Chunnan Dong; Jing Li
Journal:  Technol Health Care       Date:  2022       Impact factor: 1.205

6.  Electroencephalogram microstates and functional connectivity of cybersickness.

Authors:  Sungu Nam; Kyoung-Mi Jang; Moonyoung Kwon; Hyun Kyoon Lim; Jaeseung Jeong
Journal:  Front Hum Neurosci       Date:  2022-08-22       Impact factor: 3.473

Review 7.  Machine learning methods for the study of cybersickness: a systematic review.

Authors:  Alexander Hui Xiang Yang; Nikola Kasabov; Yusuf Ozgur Cakmak
Journal:  Brain Inform       Date:  2022-10-09
  7 in total

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