Electroencephalogram microstates and functional connectivity of cybersickness

Abstract

Virtual reality (VR) is a rapidly developing technology that simulates the real world. However, for some cybersickness-susceptible people, VR still has an unanswered problem—cybersickness—which becomes the main obstacle for users and content makers. Sensory conflict theory is a widely accepted theory for cybersickness. It proposes that conflict between afferent signals and internal models can cause cybersickness. This study analyzes the brain states that determine cybersickness occurrence and related uncomfortable feelings. Furthermore, we use the electroencephalogram (EEG) microstates and functional connectivity approach based on the sensory conflict theory. The microstate approach is a time–space analysis method that allows signals to be divided into several temporarily stable states, simultaneously allowing for the exploration of short- and long-range signals. These temporal dynamics can show the disturbances in mental processes associated with neurological and psychiatric conditions of cybersickness. Furthermore, the functional connectivity approach gives us in-depth insight and relationships between the sources related to cybersickness. We recruited 40 males (24.1 ± 2.3 years), and they watched a VR video on a curved computer monitor for 10 min to experience cybersickness. We recorded the 5-min resting state EEG (baseline condition) and 10-min EEG while watching the VR video (task condition). Then, we performed a microstate analysis, focusing on two temporal parameters: mean duration and global explained variance (GEV). Finally, we obtained the functional connectivity data using eLoreta and lagged phase synchronization (LPS). We discovered five sets of microstates (A–E), including four widely reported canonical microstates (A–D), during baseline and task conditions. The average duration increased in microstates A and B, which is related to the visual and auditory networks. The GEV and duration decreased in microstate C, whereas those in microstate D increased. Microstate C is related to the default mode network (DMN) and D to the attention network. The temporal dynamics of the microstate parameters are from cybersickness disturbing the sensory, DMN, and attention networks. In the functional connectivity part, the LPS between the left and right parietal operculum (OP) significantly decreased (p < 0.05) compared with the baseline condition. Furthermore, the connectivity between the right OP and V5 significantly decreased (p < 0.05). These results also support the disturbance of the sensory network because a conflict between the visual (V5) and vestibular system (OP) causes cybersickness. Changes in the microstates and functional connectivity support the sensory conflict theory. These results may provide additional information in understanding brain dynamics during cybersickness.

Classification of Visually Induced Motion Sickness Based on Phase-Locked Value Functional Connectivity Matrix and CNN-LSTM

“…However, the results of the mean SSQ scores before and after the experiment were significantly different (t = −10.17, p < 0.001), indicating that the subjects did experience visually induced motion sickness during the task state. This conclusion was consistent with the one found by Sungu Nam et al [ 31 ]. Therefore, the grade of motion sickness can be classified according to the time of the subjects’ oral report.…”

Who says you are so sick? An investigation on individual susceptibility to cybersickness triggers using EEG, EGG and ECG

“…Among these steps, artifact rejection is particularly critical because it involves manual selection, which relies heavily on the experience and expertise of the researchers. Notably, some previous studies have failed to completely remove eye-related artifacts, leading to noisy results [32,46,49]. The data processing stage often involves categorizing results into either cybersickness or no cybersickness, grouping electrodes based on their positions, and classifying them into four or five distinct areas (e.g., PreFrontal, Frontal, Occipital, Central Parietal, Temporal).…”

Temporal and spatial variability of dynamic microstate brain network in disorders of consciousness

“…Thus, brain connectivity and microstates provide complementary perspectives on the neural dynamics underlying DOC. At present, some studies have explored the neurodynamic characteristics of stroke patients, cyber sickness, and Alzheimer's disease by combining microstates and FC 15–17 . However, there are few studies on the neural dynamics of DOC functional connectivity combined with microstates.…”