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Studying cognitive processes using mobile EEG in VR: studying possible artifacts and signal validation

Poster Session A - Saturday, March 7, 2026, 3:00 – 5:00 pm PST, Fairview/Kitsilano Ballrooms

Cezary Zając¹ (zajac.cezary@gmail.com), Karina Maciejewska¹; ¹University of Silesia in Katowice, Poland

Event-related potentials (ERPs), measured via electroencephalography (EEG), are central to studying cognitive processes, especially attention, in cognitive neuroscience. Yet, traditional paradigms relying on static displays and minimal movement may limit ecological validity. Integrating virtual reality (VR) technologies with mobile EEG systems enables more naturalistic interaction but raises concerns about the impact of VR head-mounted displays (HMDs) on EEG signal integrity. The present study examines potential disturbances in the P3 component (ERP component related to attention) and overall EEG signal quality caused by the mechanical and electrical impact of VR HMDs on electrodes. Two HMDs (Pimax Innovation Inc., China; Meta, USA) are being tested with two EEG systems (g.tec, Austria; ANT Neuro, Netherlands). The experiment includes two phases. In the first phase, we have evaluated how the HMD affects EEG signals by comparing the P3 waveform and EEG power spectrum during a visual oddball task across two conditions: stimuli presented on a standard computer screen versus within a VR HMD. The second phase will investigate motion artifacts using a dynamic 3D VR environment. Preliminary findings suggest similar P3 waveforms across conditions. Electrical interference from the HMD appears negligible and outside the range of interest, leaving the P3 component unaffected. While we anticipate some artifacts in mobile, dynamic testing, these are expected to be correctable through suitable preprocessing. Such an evaluation of the impact of VR headsets on EEG signal quality is critical for accurate interpretation of data in attention research employing VR-based simulations of real-world cognitive processes.

Topic Area: METHODS: Electrophysiology