Spatial and temporal EEG dynamics of motion sickness

Neuroimage. 2010 Feb 1;49(3):2862-70. doi: 10.1016/j.neuroimage.2009.10.005. Epub 2009 Oct 13.

Abstract

This study investigates motion-sickness-related brain responses using a VR-based driving simulator on a motion platform with six degrees of freedom, which provides both visual and vestibular stimulations to induce motion sickness in a manner that is close to that in daily life. Subjects' brain dynamics associated with motion sickness were measured using a 32-channel EEG system. Their degree of motion sickness was simultaneously and continuously reported using an onsite joystick, providing non-stop behavioral references to the recorded EEG changes. The acquired EEG signals were parsed by independent component analysis (ICA) into maximally independent processes. The decomposition enables the brain dynamics that are induced by the motion of the platform and motion sickness to be disassociated. Five MS-related brain processes with equivalent dipoles located in the left motor, the parietal, the right motor, the occipital and the occipital midline areas were consistently identified across all subjects. The parietal and motor components exhibited significant alpha power suppression in response to vestibular stimuli, while the occipital components exhibited MS-related power augmentation in mainly theta and delta bands; the occipital midline components exhibited a broadband power increase. Further, time series cross-correlation analysis was employed to evaluate relationships between the spectral changes associated with different brain processes and the degree of motion sickness. According to our results, it is suggested both visual and vestibular stimulations should be used to induce motion sickness in brain dynamic studies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / physiopathology*
  • Brain Mapping*
  • Electroencephalography
  • Female
  • Humans
  • Male
  • Motion Sickness / physiopathology*
  • Signal Processing, Computer-Assisted
  • Young Adult