Rapid reconfiguration of cortical networks after repeated exposure to visual-vestibular conflicts.

Visual-vestibular conflicts can induce motion sickness and further postural instability. Visual-vestibular habituation is recommended to reduce the symptoms of motion sickness and improve postural stability with an altered multisensory reweighting progress. However, it is unclear how the human brain reweights multisensory information after repeated exposure to visual-vestibular conflicts. Therefore, we synchronized a rotating platform and a virtual scene to present visual-vestibular congruent (natural visual stimulation) and incongruent (conflicted visual stimulation) conditions and collected EEG and center of pressure (COP) data. We constructed the effective brain connectivity of region of interest (ROI) derived from source-space EEG in theta-band activity, and quantified the postural stability and the inflow and outflow of each ROI. We found repeated exposure to congruent and incongruent conditions both decreased COP path length and increased COP complexity. Besides, we found that repeated exposure to the incongruent environment decreased the inflow into visual cortex, suggesting the brain down-weighted the less reliable visual information for postural stability. In contrast, repeated exposure to the congruent environment increased the inflow into posterior parietal cortex and the outflow from visual cortex and S1, suggesting an increase in efficiency of multisensory integration. We concluded that repeated exposure to congruent and incongruent conditions both improved postural stability with different multisensory reweighting patterns as revealed by different dynamic changes of brain networks.

Effects of within-day intervals on adaptation to visually induced motion sickness in a virtual-reality motorcycling simulator.

This study investigated the effects of the time interval between virtual reality (VR) sessions on visually induced motion sickness (VIMS) reduction to better understand adaptation to and recovery from a nauseating VR experience. The participants experienced two 6-min VR sessions of a first-person motorcycle ride through a head-mounted display with (1) a 6-min interval, (2) an interval until the VIMS score reached zero, and (3) a 60-min interval. The results showed that for each condition, VIMS in the second session was aggravated, unchanged, or attenuated, respectively, indicating that additional resting time was necessary for VIMS adaptation. This study suggests that a certain type of multisensory learning attenuates VIMS symptoms within a relatively short time, requiring at least 20 min of additional resting time after subjective recovery from VIMS symptoms. This finding has important implications for reducing the time interval between repeated challenges when adapting to nauseating stimuli during VR experiences.

Neuro-ophthalmic and Neuro-otologic Evaluation in Individuals with Motion Sickness Susceptibility.

Since the physiological background of motion sickness is not entirely clear, it was aimed to examine the physiological differences in groups consisting of individuals susceptible and non-susceptible to motion sickness. Sixty subjects [motion sickness (MS) group: 33 female, 3 male; 28.8 ± 8.1 years; control group: 19 female, 5 male; 24.5 ± 4.3 years] were included in the study. Near visual acuity test on the treadmill in the presence of visual stimulation, pattern visual-evoked potentials, oculomotor tests, and computerized dynamic posturography were applied. Receiver operating characteristic analysis was performed to determine the parameter that provides the excellent discrimination between the groups. The most effective parameter in differentiating the study groups was determined as dynamic visual acuity with 77.8% sensitivity and 95.8% specificity. Significant differences were found in the vestibular (mean ± standard deviation: 0.63 ± 0.17), visual (0.77 ± 0.18), and composite scores (73.11 ± 11.89) of the patients (P=.000) in posturographic evaluation. In the visual-evoked potential examination, a significant decrease was found in the amplitude values between the P100-N145 waves in the binocular (5.0 ± 2.8, P=.002), right eye (7.6 ± 3.2, P=.009) and left eye (7.9 ± 2.9, P=.016) in the symptomatic patients. In binocular oculomotor evaluation, directional asymmetric findings were obtained. It has been shown that the most effective test parameter that distinguishes the MS susceptible and non-susceptible individuals is the dynamic visual acuity value. Based on the results of neuro-physiological tests, it was suggested that a possible visual-vestibular integration disorder in individuals susceptible to motion sickness may affect visual and vestibular performance.

Detection of virtual reality motion sickness based on EEG using asymmetry of entropy and cross-frequency coupling.

The existence of Virtual Reality Motion Sickness (VRMS) is a key factor restricting the further development of the VR industry, and the premise to solve this problem is to be able to accurately and effectively detect its occurrence. In view of the current lack of high-accuracy and effective detection methods, this paper proposes a VRMS detection method based on entropy asymmetry and cross-frequency coupling value asymmetry of EEG. First of all, the EEG of the four selected pairs of electrodes on the bilateral brain are subjected to Multivariate Variational Mode Decomposition (MVMD) respectively, and three types of entropy values on the low-frequency and high-frequency components are calculated, namely approximate entropy, fuzzy entropy and permutation entropy, as well as three types of phase-amplitude coupling features between the low-frequency and high-frequency components, namely the mean value, standard deviation and correlation coefficient; Secondly, the difference of the entropies and the cross-frequency coupling features between the left electrodes and the right electrodes are calculated; Finally, the final feature set are selected via t-test and fed into the SVM for classification, thus realizing the automatic detection of VRMS. The results show that the three classification indexes under this method, i.e., accuracy, sensitivity and specificity, reach 99.5 %, 99.3 % and 99.7 %, respectively, and the value of the area under the ROC curve reached 1, which proves that this method can be an effective indicator for detecting the occurrence of VRMS.

Alpha tACS on Parieto-Occipital Cortex Mitigates Motion Sickness Based on Multiple Physiological Observation.

Approximately one third of the population is prone to motion sickness (MS), which is associated with the dysfunction in the integration of sensory inputs. Transcranial alternating current stimulation (tACS) has been widely used to modulate neurological functions by affecting neural oscillation. However, it has not been applied in the treatment of motion sickness. This study aims to investigate changes in brain oscillations during exposure to MS stimuli and to further explore the potential impact of tACS with the corresponding frequency and site on MS symptoms. A total of 19 subjects were recruited to be exposed to Coriolis stimuli to complete an inducing session. After that, they were randomly assigned to tACS stimulation group or sham stimulation group to complete a stimulation session. Electroencephalography (EEG), electrocardiogram, and galvanic skin response were recorded during the experiment. All the subjects suffering from obvious MS symptoms after inducing session were observed that alpha power of four channels of parieto-occipital lobe significantly decreased (P7: t =3.589, p <0.001; P8: t =2.667, p <0.05; O1: t =3.556, p <0.001; O2: t =2.667, p <0.05). Based on this, tACS group received the tACS stimulation at 10Hz from Oz to CPz. Compared to sham group, tACS stimulation significantly improved behavioral performance and entrained the alpha oscillation in individuals whose alpha power decrease during the inducing session. The findings show that parieto-occipital alpha oscillation plays a critical role in the integration of sensory inputs, and alpha tACS on parieto-occipital can become a potential method to mitigate MS symptoms.

Feature extraction method of EEG based on wavelet packet reconstruction and deep learning model of VR motion sickness feature classification and prediction.

The surging popularity of virtual reality (VR) technology raises concerns about VR-induced motion sickness, linked to discomfort and nausea in simulated environments. Our method involves in-depth analysis of EEG data and user feedback to train a sophisticated deep learning model, utilizing an enhanced GRU network for identifying motion sickness patterns. Following comprehensive data pre-processing and feature engineering to ensure input accuracy, a deep learning model is trained using supervised and unsupervised techniques for classifying and predicting motion sickness severity. Rigorous training and validation procedures confirm the model's robustness across diverse scenarios. Research results affirm our deep learning model's 84.9% accuracy in classifying and predicting VR-induced motion sickness, surpassing existing models. This information is vital for improving the VR experience and advancing VR technology.

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

To effectively detect motion sickness induced by virtual reality environments, we developed a classification model specifically designed for visually induced motion sickness, employing a phase-locked value (PLV) functional connectivity matrix and a CNN-LSTM architecture. This model addresses the shortcomings of traditional machine learning algorithms, particularly their limited capability in handling nonlinear data. We constructed PLV-based functional connectivity matrices and network topology maps across six different frequency bands using EEG data from 25 participants. Our analysis indicated that visually induced motion sickness significantly alters the synchronization patterns in the EEG, especially affecting the frontal and temporal lobes. The functional connectivity matrix served as the input for our CNN-LSTM model, which was used to classify states of visually induced motion sickness. The model demonstrated superior performance over other methods, achieving the highest classification accuracy in the gamma frequency band. Specifically, it reached a maximum average accuracy of 99.56% in binary classification and 86.94% in ternary classification. These results underscore the model's enhanced classification effectiveness and stability, making it a valuable tool for aiding in the diagnosis of motion sickness.

Data augmentation for generating synthetic electrogastrogram time series.

To address an emerging need for large number of diverse datasets for rigor evaluation of signal processing techniques, we developed and evaluated a new method for generating synthetic electrogastrogram time series. We used electrogastrography (EGG) data from an open database to set model parameters and statistical tests to evaluate synthesized data. Additionally, we illustrated method customization for generating artificial EGG time series alterations caused by the simulator sickness. Proposed data augmentation method generates synthetic EGG data with specified duration, sampling frequency, recording state (postprandial or fasting state), overall noise and breathing artifact injection, and pauses in the gastric rhythm (arrhythmia occurrence) with statistically significant difference between postprandial and fasting states in > 70% cases while not accounting for individual differences. Features obtained from the synthetic EGG signal resembling simulator sickness occurrence displayed expected trends. The code for generation of synthetic EGG time series is not only freely available and can be further customized to assess signal processing algorithms but also may be used to increase data diversity for training artificial intelligence (AI) algorithms. The proposed approach is customized for EGG data synthesis but can be easily utilized for other biosignals with similar nature such as electroencephalogram.

Visual vertigo and motion sickness is different between persistent postural-perceptual dizziness and vestibular migraine.

INTRODUCTION: Persistent postural-perceptual dizziness (PPPD) and vestibular migraine (VM) share symptoms of visual vertigo and motion sickness that can be confusing for clinicians to distinguish. We compare the severity of these symptoms and dynamic subjective visual vertical (dSVV) in these two common vestibular conditions. METHOD: Twenty-nine patients with PPPD, 37 with VM, and 29 controls were surveyed for subjective symptoms using the visual vertigo analogue scale (VVAS) and motion sickness susceptibility questionnaire during childhood (MSA) and the past 10 years (MSB). dSVV is a measure of visual dependence measures perception of verticality against a rotating background (5 deg./s). RESULTS: VVAS revealed contextual differences for dizziness between those with PPPD and VM. Ratings of visual vertigo were most severe in PPPD, less in VM, and mild in controls (VVAS PPPD 27.1, VM 11.2, control 4.6, p < 0.001). MSA was more severe in VM than in PPPD or control (12.8 vs 7.6 vs 8.5, p = 0.01). MSB was more severe in VM than controls (MSB score 12.9 VS 8.1 p = 0.009) but was not different than PPPD (MSB score 10.0, p = 0.10). dSVV alignment was similar among the three groups (p = 0.83). Both VM and PPPD groups had greater simulator sickness than controls after completing the dSVV. CONCLUSIONS: Patients with PPPD report more visual vertigo than those with VM, but a history of motion sickness as a child is more common in VM. Additionally, the environmental context that induces visual vertigo is different between PPPD and VM.

EEG classification model for virtual reality motion sickness based on multi-scale CNN feature correlation.

BACKGROUND: Virtual reality motion sickness (VRMS) is a key issue hindering the development of virtual reality technology, and accurate detection of its occurrence is the first prerequisite for solving the issue. OBJECTIVE: In this paper, a convolutional neural network (CNN) EEG detection model based on multi-scale feature correlation is proposed for detecting VRMS. METHODS: The model uses multi-scale 1D convolutional layers to extract multi-scale temporal features from the multi-lead EEG data, and then calculates the feature correlations of the extracted multi-scale features among all the leads to form the feature adjacent matrixes, which converts the time-domain features to correlation-based brain network features, thus strengthen the feature representation. Finally, the correlation features of each layer are fused. The fused features are then fed into the channel attention module to filter the channels and classify them using a fully connected network. Finally, we recruit subjects to experience 6 different modes of virtual roller coaster scenes, and collect resting EEG data before and after the task to verify the model. RESULTS: The results show that the accuracy, precision, recall and F1-score of this model for the recognition of VRMS are 98.66 %, 98.65 %, 98.68 %, and 98.66 %, respectively. The proposed model outperforms the current classic and advanced EEG recognition models. SIGNIFICANCE: It shows that this model can be used for the recognition of VRMS based on the resting state EEG.

Concussion can increase the risk of visually induced motion sickness.

Concussion can lead to various symptoms such as balance problems, memory impairments, dizziness, and/or headaches. It has been previously suggested that during self-motion relevant tasks, individuals with concussion may rely heavily on visual information to compensate for potentially less reliable vestibular inputs and/or problems with multisensory integration. As such, concussed individuals may also be more sensitive to other visually-driven sensations such as visually induced motion sickness (VIMS). To investigate whether concussed individuals are at elevated risk of experiencing VIMS, we exposed participants with concussion (n = 16) and healthy controls (n = 15) to a virtual scene depicting visual self-motion down a grocery store aisle at different speeds. Participants with concussion were further separated into symptomatic and asymptomatic groups. VIMS was measured with the SSQ before and after stimulus exposure, and visual dependence, self-reported dizziness, and somatization were recorded at baseline. Results showed that concussed participants who were symptomatic demonstrated significantly higher SSQ scores after stimulus presentation compared to healthy controls and those who were asymptomatic. Visual dependence was positively correlated with the level of VIMS in healthy controls and participants with concussion. Our results suggest that the presence of concussion symptoms at time of testing significantly increased the risk and severity of VIMS. This finding is of relevance with regards to the use of visual display devices such as Virtual Reality applications in the assessment and rehabilitation of individuals with concussion.

Effects of passenger body movements in a visual task during and after vehicle rotation on post-rotatory illusion and motion sickness.

We explored how body movements influence illusory body motion intensity and their association with motion sickness. Twelve individuals who were seated in the back of a passenger car, performed a visual task and were subjected to continuous rotations followed by driving in a straight line. The body movements during and immediately after rotation were categorized as follows: (A) upright posture; (B) leaning the body in the yaw direction towards the rotation center, returning the yaw angle to zero upon transitioning to straight line travel, and tilting in the roll condition and gradually returning to upright; and (C) tilting in roll conditions towards the centripetal direction during rotation and becoming upright upon transitioning to straight line travel. In experiment-1, after spanning half a lap, participants reported the intensity of the illusory motion experienced during straight line travel immediately after rotation. In experiment-2, after travelling up to eight laps, the participants reported the symptom level of motion sickness experienced during two straight sections per lap using the MIsery SCale (MISC). Experiment-1 revealed that condition (C) had significantly larger illusions than Conditions (A) and (B). Experiment-2 revealed that motion sickness progressed significantly more in Condition (C) than in Condition (A). A significant positive correlation was found between the observed MISC and the illusion strength. Our findings suggest that body movements during and immediately after continuous rotation have a significant impact on the illusion strength. Additionally, illusory motion could serve as an indicator of impending motion sickness.

A computational model of motion sickness dynamics during passive self-motion in the dark.

Predicting the time course of motion sickness symptoms enables the evaluation of provocative stimuli and the development of countermeasures for reducing symptom severity. In pursuit of this goal, we present an Observer-driven model of motion sickness for passive motions in the dark. Constructed in two stages, this model predicts motion sickness symptoms by bridging sensory conflict (i.e., differences between actual and expected sensory signals) arising from the Observer model of spatial orientation perception (stage 1) to Oman's model of motion sickness symptom dynamics (stage 2; presented in 1982 and 1990) through a proposed "Normalized Innovation Squared" statistic. The model outputs the expected temporal development of human motion sickness symptom magnitudes (mapped to the Misery Scale) at a population level, due to arbitrary, 6-degree-of-freedom, self-motion stimuli. We trained model parameters using individual subject responses collected during fore-aft translations and off-vertical axis of rotation motions. Improving on prior efforts, we only used datasets with experimental conditions congruent with the perceptual stage (i.e., adequately provided passive motions without visual cues) to inform the model. We assessed model performance by predicting an unseen validation dataset, producing a Q2 value of 0.91. Demonstrating this model's broad applicability, we formulate predictions for a host of stimuli, including translations, earth-vertical rotations, and altered gravity, and we provide our implementation for other users. Finally, to guide future research efforts, we suggest how to rigorously advance this model (e.g., incorporating visual cues, active motion, responses to motion of different frequency, etc.).

Suspected Mal de Debarquement Syndrome: A Case Report Highlighting the Difficulty in Diagnosis and Management.

MdDS is syndrome of oscillating vertigo following cessation of passive motion. The pathogenesis of this disorder is not well understood, but functional imaging studies suggest cortical connectivity dysfunction in feedback loops of the vestibulo-ocular system and visuo-spatial system. Patients go through multiple appointments and often specialist referrals before being diagnosed. After diagnosis, optimal management is difficult. Several treatment modalities, including medication, vestibular rehabilitation, and neuromodulation, have had variable success in management. We present the case of a young, female active duty Air Force Captain who developed symptoms while deployed. She underwent multiple treatments with variable success. Her clinical course highlights the difficulties for patients and providers posed by suspected MdDS.

Effect of screen configuration on the neck angle, muscle activity, and simulator sickness symptoms in virtual reality.

BACKGROUND: There is a lack of information about the optimal setup of multiple screen configurations in virtual reality (VR) office work. OBJECTIVE: The objective of this study was to evaluate the effects of different screen configurations on neck flexion, rotation, neck muscle activity, and simulator sickness symptoms during Virtual Reality (VR) office work. METHODS: Twelve participants (7 males; 21 to 27 years old) performed copy-paste and drag-drop tasks in three different screen configurations (single screen, primary-secondary screen, and double screen) in a randomized order. Optical motion capture system, electromyography (EMG) device, and simulator sickness questionnaire (SSQ) were used to measure the users' responses. RESULTS: Neck rotation angles, muscle activities, and VR sickness were significantly affected by the screen configurations (p < 0.021). The primary-secondary screen showed the highest right rotation angle (median: -33.47°) and left sternocleidomastoid (SCM) muscle activities (median: 12.57% MVC). Both single (median: 22.42) and primary-secondary (median: 22.40) screen showed the highest value of SSQ. CONCLUSIONS: The screen configurations in VR could be an important design factor affecting the users' physical demands of the neck and VR sickness symptoms. Asymmetric neck rotations caused by the primary-secondary screen conditions should be avoided.

Oxidative stress and motion sickness in one crew during competitive offshore sailing.

Competitive Offshore Ocean Sailing is a highly demanding activity in which subjects are exposed to psychophysical stressors for a long time. To better define the physiological adaptations, we investigated the stress response of subjects exposed to 3-days long ocean navigation with disruption of circadian rhythms. 6 male subjects were involved in the study and provided urine and saliva samples before setting sail, during a single day of inshore sailing, during 3-days long ocean navigation, and at the arrival, to measure oxidative stress, cortisol, nitric oxide metabolites (NOx) and metabolic response. Motion Sickness questionnaires were also administered during the navigation. The crew suffered a mean weight loss of 1.58 kg. After the long navigation, a significant increase in ROS production and decrease in total antioxidant capacity and uric acid levels were observed. Lipid peroxidation, NO metabolites, ketones, creatinine, and neopterin levels were also increased. Furthermore, a significant increase in cortisol levels was measured. Finally, we found a correlation between motion sickness questionnaires with the increase of NOx, and no correlation with cortisol levels. Physical and psychological stress response derived from offshore sailing resulted in increased oxidative stress, nitric oxide metabolites, and cortisol levels, unbalanced redox status, transient renal function impairment, and ketosis. A direct correlation between motion sickness symptoms evaluated through questionnaires and NOx levels was also found.

Left parietal involvement in motion sickness susceptibility revealed by multimodal magnetic resonance imaging.

Susceptibility to motion sickness varies greatly across individuals. However, the neural mechanisms underlying this susceptibility remain largely unclear. To address this gap, the current study aimed to identify the neural correlates of motion sickness susceptibility using multimodal MRI. First, we compared resting-state functional connectivity between healthy individuals who were highly susceptible to motion sickness (N = 36) and age/sex-matched controls who showed low susceptibility (N = 36). Seed-based analysis revealed between-group differences in functional connectivity of core vestibular regions in the left posterior Sylvian fissure. A data-driven approach using intrinsic connectivity contrast found greater network centrality of the left intraparietal sulcus in high- rather than in low-susceptible individuals. Moreover, exploratory structural connectivity analysis uncovered an association between motion sickness susceptibility and white matter integrity in the left inferior fronto-occipital fasciculus. Taken together, our data indicate left parietal involvement in motion sickness susceptibility.

Idiosyncratic multisensory reweighting as the common cause for motion sickness susceptibility and adaptation to postural perturbation.

Numerous empirical and modeling studies have been done to find a relationship between postural stability and the susceptibility to motion sickness (MS). However, while the demonstration of a causal relationship between postural stability and the susceptibility to MS is still lacking, recent studies suggest that motion sick individuals have genuine deficits in selecting and reweighting multimodal sensory information. Here we investigate how the adaptation to changing postural situations develops and how the dynamics in multisensory integration is modulated on an individual basis along with MS susceptibility. We used a postural task in which participants stood on a posturographic platform with either eyes open (EO) or eyes closed (EC) during three minutes. The platform was static during the first minute (baseline phase), oscillated harmonically during the second minute (perturbation phase) and returned to its steady state for the third minute (return phase). Principal component (PC) analysis was applied to the sequence of short-term power density spectra of the antero-posterior position of the center of pressure. Results showed that the less motion-sick a participant is, the more similar is his balance between high and low frequencies for EO and EC conditions (as calculated from the eigenvector of the first PC). By fitting exponential decay models to the first PC score in the return phase, we estimated, for each participant in each condition, the sluggishness to return to the baseline spectrum. We showed that the de-adaptation following platform oscillation depends on the susceptibility to MS. These results suggest that non motion-sick participants finely adjust their spectrum in the perturbation phase (i.e. reweighting) and therefore take longer to return to their initial postural control particularly with eyes closed. Thus, people have idiosyncratic ways of doing sensory reweighting for postural control, these processes being tied to MS susceptibility.

Pyruvate accumulation may contribute to acceleration-induced impairment of physical and cognitive abilities: an experimental study.

BACKGROUND: Fatigue can be induced after acceleration exposure, however its mechanism is still unclear. The aim of the present study was to examine whether metabolites' changes can decrease cognitive and physical function after acceleration. METHODS: Graybiel scale and Fatigue Self-rating scale were used to assess the seasickness and fatigue degrees of 87 male seafarers respectively after sailing. To test the effect of pyruvate on cognitive and physical functions, five different doses of pyruvate were administrated into rats. Insulin can reduce the accumulation of pyruvate. To observe the insulin effect on pyruvate, cognitive and physical functions after acceleration, insulin administration or treatment of promoting insulin secretion was used. Physical and cognitive functions were assessed using open field test (OFT), morris water maze (MWM) and loaded swimming test (LST) in animals. RESULTS: Physical and cognitive abilities were decreased obviously, and serum pyruvate increased mostly in human and rats after acceleration. Compared with vehicle group, physical and cognitive abilities were significantly decreased after pyruvate administration. Besides, we found a significant decline in adenosine triphosphate (ATP) concentration and pyruvate dehydrogenase (PDH) activity in the hippocampus, prefrontal cortex, liver, and muscle of rats treated with acceleration or pyruvate injection, while insulin administration or treatment of promoting insulin secretion markedly alleviated this decline and the impairment of physical and cognitive abilities, compared with the control group. CONCLUSION: Our results indicate that pyruvate has a negative effect on physical and cognitive abilities after acceleration. Insulin can inhibit pyruvate accumulation and cognitive and physical function after acceleration exposure.