3D graphics, virtual reality, and motion-onset visual evoked potentials in neurogaming

• Published in: Progress in brain research Vol. 228; pp. 329 - 353
• Main Authors: Beveridge, R, Wilson, S, Coyle, D
• Format: Journal Article
• Language: English
• Published: Netherlands 2016
• Subjects: Adult; Algorithms; Brain - diagnostic imaging; Brain - physiology; Brain-Computer Interfaces; Computer Simulation; Electroencephalography; Evoked Potentials, Visual - physiology; Female; Humans; Imaging, Three-Dimensional; Male; Motion Perception - physiology; Neuroimaging; Photic Stimulation; User-Computer Interface; Video Games; Graphics; Oculus rift; 3-Dimensional; Video gaming; Liquid crystal display; Brain–computer interface; Virtual reality; Electroencephalography; Motion-onset visually evoked potentials
• ISSN: 1875-7855
• DOI: 10.1016/bs.pbr.2016.06.006

A brain-computer interface (BCI) offers movement-free control of a computer application and is achieved by reading and translating the cortical activity of the brain into semantic control signals. Motion-onset visual evoked potentials (mVEP) are neural potentials employed in BCIs and occur when motion-related stimuli are attended visually. mVEP dynamics are correlated with the position and timing of the moving stimuli. To investigate the feasibility of utilizing the mVEP paradigm with video games of various graphical complexities including those of commercial quality, we conducted three studies over four separate sessions comparing the performance of classifying five mVEP responses with variations in graphical complexity and style, in-game distractions, and display parameters surrounding mVEP stimuli. To investigate the feasibility of utilizing contemporary presentation modalities in neurogaming, one of the studies compared mVEP classification performance when stimuli were presented using the oculus rift virtual reality headset. Results from 31 independent subjects were analyzed offline. The results show classification performances ranging up to 90% with variations in conditions in graphical complexity having limited effect on mVEP performance; thus, demonstrating the feasibility of using the mVEP paradigm within BCI-based neurogaming.