A comparative experimental study of visual brain event-related potentials to a working memory task: virtual reality head-mounted display versus a desktop computer screen

Abstract

Virtual reality head mounted display (VR HMD) systems are increasingly utilised in combination with electroencephalography (EEG) in the experimental study of cognitive tasks. The aim of our investigation was to determine the similarities/differences between VR HMD and the computer screen (CS) in response to an n-back working memory task by comparing visual electrophysiological event-related potential (ERP) waveforms (N1/P1/P3 components). The same protocol was undertaken for VR HMD and CS with participants wearing the same EEG headcap. ERP waveforms obtained with the VR HMD environment followed a similar time course to those acquired in CS. The P3 mean and peak amplitudes obtained in VR HMD were not significantly different to those obtained in CS. In contrast, the N1 component was significantly higher in mean and peak amplitudes for the VR HMD environment compared to CS at the frontal electrodes. Significantly higher P1 mean and peak amplitudes were found at the occipital region compared to the temporal for VR HMD. Our results show that successful acquisition of ERP components to a working memory task is achievable by combining VR HMD with EEG. In addition, the higher amplitude N1/P1 components seen in VR HMD indicates the potential utility of this VR modality in the investigation of early ERPs. In conclusion, the combination of VR HMD with EEG/ERP would be a useful approach to advance the study of cognitive function in experimental brain research.

An investigation of architectural design process in physical medium and VR

“…This situation may have negatively affected the design process in VR. Previous studies have shown that the weight and bulk of VR headsets can cause some level of discomfort among participants (Aksoy et al, 2021;Rupp et al, 2019), which is also consistent with questionnaire comments from two participants. Some level of frustration caused by the stress and the weight of the VR headsets may have prevented the participants from focusing on the design, resulting in longer design duration and slower design speed in virtuo.…”

Assessment of mental workload across cognitive tasks using a passive brain-computer interface based on mean negative theta-band amplitudes

“…Our feature extraction method relies on a general tendency that only appears by averaging large amounts of data belonging, ideally, to the largest possible number of subjects (and or tasks according to the case) to train the data. The literature of EEG has previously presented cases in which features are only observable after using grand averages of data, such as in the case of event related potentials (Hoehl and Wahl, 2012 ; Voigt-Antons et al, 2012 ; Kuncheva and Rodríguez, 2013 ), also including specific cognitive tasks such as n-back (Aksoy et al, 2021 ) and the readiness potential (“Bereitschaftspotential”) (Blankertz et al, 2007 ; Nann et al, 2019 ), where grand averages have a noise canceling effect in the signals, and some of these event related potentials, occurring at longer latencies after stimuli are more related to endogenous brain states (Nunez, 2012 ; Sellers et al, 2012 ), like the ones we are looking for. We have presented a simple classification method with channel selection based on a general tendency in the data obtained along the whole durations of trials which should relate mental workload to a more permanent or endogenous characteristic of mental activity.…”

“…cognitive tasks such as n-back (Aksoy et al, 2021) and the readiness potential ("Bereitschaftspotential") (Blankertz et al, 2007;Nann et al, 2019), where grand averages have a noise canceling effect in the signals, and some of these event related potentials, occurring at longer latencies after stimuli are more related to endogenous brain states (Nunez, 2012;Sellers et al, 2012), like the ones we are FIGURE Illustration of the "Theta Negative" Matrix TN ( × ), and vector mean_tr ( × ) corresponding to the total trials of task T . Collected from all the twelve subjects considered for analysis from our dataset (each subject performed trials of task T ), each trial (previously preprocessed, filtered through the theta frequency band, trimmed and scaled) is represented by a vector ( × ), obtained after finding an average per EEG channel of all the sample components that had a negative amplitude in that channel.…”

Working memory training and evaluation based on brain-computer interface and virtual reality: our opinion

“…Additionally, a study explored a cognitively adaptive VR training system incorporating realtime EEG to adjust task difficulty, revealing significant brain activity changes with increasing complexity while response times remained unchanged (Dey et al, 2019). Furthermore, a study explored the integration of VR headsets with EEG in cognitive tasks, confirming that VR head-mounted displays (HMDs) could successfully elicit ERP components similar to traditional computer screens, indicating their potential utility in early ERP investigations for cognitive research (Aksoy et al, 2021). These studies collectively demonstrate the evolving landscape of WMT, underscored by the promising prospects of BCI-VR, offering more immersive and quantifiable approaches to cognitive enhancement.…”