Immersion in virtual reality is a powerful sensory experience. It often leads to striking situations, such as experiencing virtual contacts on your avatar, despite the absence of physical contact on your real body. However, as of today, it is still unknown whether purely-virtual touch remains fictive/imaginative, or whether our brain processes it the same way as real touch. In this paper, we conducted an experiment comparing purely visual touch simulation (a virtual robot arm touching the avatar’s hand) with a congruent visuo-tactile simulation (visual feedback is coupled with a real robot arm touching the participant’s hand in the physical world). Using this setup, we investigated the neural responses to purely-virtual and visuo-tactile touch, and examined how these responses were modulated by cognitive workload induced by tasks within the virtual environment. The analysis of the electroencephalography (EEG recording) revealed a strong activation of the sensorimotor cortex in both conditions, although stronger and faster when physical touch occurs. Our results also revealed a decrease in evoked potentials under high cognitive workload, with the reduction being more pronounced for physical touch. Our results show that a purely-virtual touch is processed similarly to a physical touch, i.e, engaging sensorimotor regions despite the absence of direct somatosensory stimulation. This suggests that the perception of the body in virtual environments can extend beyond simple illusions, involving neural processes similar to those engaged during real physical experiences. Besides, in the age of metaverses becoming accessible to a wider audience, knowing that our brain perceives virtual contacts in VR similarly to physical contacts further underlines the need to design immersive environments that prioritize physical integrity and user safety.

Does seeing avatars during social interaction in virtual reality (VR) affect the neural synchrony of interacting people? To address this question, we assessed inter-brain synchronization (IBS), which reflects synchronization of brain activities among interacting people and is linked to interaction success. We designed a social interaction task in VR where participants' appearances were represented by virtual cursors only or additional human avatars on them. Participants performed a finger position tracking interaction under both conditions. We compared the IBS across interaction conditions by collecting electroencephalography (EEG), positional data, and virtual embodiment questionnaires. The results from 30 participants (15 pairs) show that seeing the avatars resulted in significantly higher virtual body ownership but comparable agency and positional synchronization compared to the virtual cursors-only condition. In the inter-brain analysis, we found a significant increase in IBS strength and an increasing trend in the number of IBS in the alpha band after interacting with avatar-embodied virtual cursors. Correlation analyses further revealed a significant association between alpha-band IBS and subjective body ownership, and a trend with social inclusion scores. While the influence of visual complexity cannot be ruled out, these findings suggest that avatar-induced embodiment may contribute to enhanced inter-brain synchrony during VR-mediated social interaction.

Technological developments provide solutions to alleviate the tremendous impact on the health and autonomy due to the impact of dementia on navigation abilities. We systematically reviewed the literature on devices tested to provide assistance to people with dementia during indoor, outdoor and virtual navigation (PROSPERO ID number: 215585). Medline and Scopus databases were searched from inception. Our aim was to summarize the results from the literature to guide future developments. Twenty-three articles were included in our study. Three types of information were extracted from these studies. First, the types of navigation advice the devices provided were assessed through: (i) the sensorial modality of presentation, e.g., visual and tactile stimuli, (ii) the navigation content, e.g., landmarks, and (iii) the timing of presentation, e.g., systematically at intersections. Second, we analyzed the technology that the devices were based on, e.g., smartphone. Third, the experimental methodology used to assess the devices and the navigation outcome was evaluated. We report and discuss the results from the literature based on these three main characteristics. Finally, based on these considerations, recommendations are drawn, challenges are identified and potential solutions are suggested. Augmented reality-based devices, intelligent tutoring systems and social support should particularly further be explored.

In this paper, we propose and compare multiple criteria for selecting ElectroEncephaloGraphic (EEG) channels over the Riemannian manifold, for EEG classification in Brain- Computer Interfaces (BCI). These criteria aim to promote EEG covariance matrix classifiers to generalize well by considering EEG data non-stationarity. Our approach consists of both increasing the discriminative information between classes over the manifold and reducing the dispersion within classes. We also reduce the influence of outliers in both discriminative and dispersion measures. Using the proposed criteria, channel selection is done automatically in a backward elimination process. The criteria are evaluated on EEG signals recorded from a tetraplegic subject and dataset IVa from BCI competition III. Experimental evidences confirm that considering the dispersion within each class as a measure for quantifying the effects of non-stationarity and removing the most affected channels can improve the performance of BCI by 5% on the tetraplegic subject and by 12 % on dataset IVa.