This study demonstrates how playing a well-designed multitasking motion video game in a virtual reality (VR) environment can positively impact the cognitive and physical health of older players. We developed a video game that combines cognitive and physical training in a VR environment. The impact of playing the game was measured through a four-week longitudinal experiment. Twenty healthy older adults were randomly assigned to either an intervention group (i.e., game training) or a control group (i.e., no contact). Participants played three 45-min sessions per week completing cognitive tests for attention, working memory, reasoning and a test for physical balance before and after the intervention. Results showed that compared to the control group, the game group showed significant improvements in working memory and a potential for enhancing reasoning and balance ability. Furthermore, while the older adults enjoyed playing the video game, ability enhancements were associated with their intrinsic motivation to play. Overall, cognitive training with multitasking VR motion video games has positive impacts on the cognitive and physical health of older adults.

Virtual reality (VR) technology provides highly immersive depth perception experiences; nevertheless, stereoscopic visual fatigue (SVF) has become an important factor currently hindering the development of VR applications. However, there is scant research on the underlying neural mechanism of SVF, especially those induced by VR displays, which need further research. In this paper, a Go/NoGo paradigm based on disparity variations is proposed to induce SVF associated with depth perception, and the underlying neural mechanism of SVF in a VR environment was investigated. The effects of disparity variations as well as SVF on the temporal characteristics of visual evoked potentials (VEPs) were explored. Point-by-point permutation statistical with repeated measures ANOVA results revealed that the amplitudes and latencies of the posterior VEP component P2 were modulated by disparities, and posterior P2 amplitudes were modulated differently by SVF in different depth perception situations. Cortical source localization analysis was performed to explore the original cortex areas related to certain fatigue levels and disparities, and the results showed that posterior P2 generated from the precuneus could represent depth perception in binocular vision, and therefore could be performed to distinguish SVF induced by disparity variations. Our findings could help to extend an understanding of the neural mechanisms underlying depth perception and SVF as well as providing beneficial information for improving the visual experience in VR applications.

Stereoscopic visual fatigue (SVF) due to prolonged immersion in the virtual environment can lead to negative user experience, thus hindering the development of virtual reality (VR) industry. Previous studies have focused on investigating the evaluation indicators associated with SVF, while few studies have been conducted to reveal the underlying neural mechanism, especially in VR applications. In this paper, a modified Go/NoGo paradigm was adopted to induce SVF in VR environment with Go trials for maintaining participants’ attention and NoGo trials for investigating the neural effects under SVF. Random dot stereograms (RDSs) with 11 disparities were presented to evoke the depth-related visual evoked potentials (DVEPs) during 64-channel EEG recordings. EEG datasets collected from 15 participants in NoGo trials were selected to conduct individual processing and group analysis, in which the characteristics of the DVEPs components for various fatigue degrees were compared and independent components were clustered to explore the original cortex areas related to SVF. Point-by-point permutation statistics revealed that DVEPs sample points from 230 ms to 280 ms (component P2) in most brain areas changed significantly when SVF increased. Additionally, independent component analysis (ICA) identified that component P2 which originated from posterior cingulate cortex and precuneus, was associated statistically with SVF. We believe that SVF is rather a conscious status concerning the changes of self-awareness or self-location awareness than the performance reduction of retinal image processing. Moreover, we suggest that indicators representing higher conscious state may be a better indicator for SVF evaluation in VR environments.

Introduction: In this study, we propose a data-driven approach that integrates behavioral diagnosis with neuroimaging features to identify representative UWS and MCS patients from a large inpatient cohort. Methods: Clinical information was extracted using a subset of UWS patients with CRS-R scores ≤ 5. Neuroimaging biomarkers were established as the increased and decreased functional connectivity indices of anatomically defined regions covering the whole brain. The algorithm was implemented through an iterative refinement process that converged on a division of UWS and MCS patients into representative and excluded (or nonrepresentative) patient groups. Results: Thirty-one out of 58 UWS patients and 23 out of 30 MCS patients were identified as representative, with an average classification accuracy of 90.2% in differentiating between the two groups. In contrast, differentiating between excluded UWS patients ( n = 27) and representative MCS patients ( n = 23) and between all UWS ( n = 58) and MCS ( n = 30) patients produced average classification accuracies of 50.9 and 64.3%, respectively. Furthermore, altered DMN functional connectivity between representative UWS and MCS patients revealed a consistent pattern as shown in prior studies, while comparisons involving excluded patients did not. Discussion: These results highlight the value of integrating behavioral scores and neural connectivity features for DOC classification, providing a more coherent basis for downstream analysis and machine-learning applications in DOC classification.

Synchronizing the movement of a virtual hand with an unseen real hand in a virtual environment is an effective method to induce a sense of ownership of the virtual hand. Although several neuroimaging studies have revealed neural mechanisms related to the ongoing process of ownership illusion, the effect of the long-term experience of ownership illusion on brain activity remains to be investigated. Here, we developed an apparatus based on real-time image matting and virtual reality technology which allowed us to use the image of participants’ real hands as their virtual hands and synchronize the movement of the virtual hands with the unseen real hands in a virtual scene. Resting-state functional imaging data were acquired immediately after participants completed several light office tasks with the virtual hands in either the virtual environment (virtual hand condition) or real environment (real hand condition). Significant positive functional connectivity of the hippocampus with the primary somatosensory and motor cortex was only observed in the virtual hand condition. The results provided novel evidence for the involvement of hippocampal-sensorimotor connection in the long-term experience of virtual hand ownership. The functional connection reorganization of the hippocampus might promote multi-sensory information integration into memory and updated the sense of body ownership, which offered important insights into the neural network underlying the availability of long-term use of VR technology in healthcare and rehabilitation.

Depression, as a common mental disorder, has a high prevalence rate among college students and seriously influences their quality of life and social functi