EEG oscillatory signatures of increased cognitive control at intersections: a virtual reality driving simulation

Senftleben, Ulrike; Kessler, Klaus · 2024 · Crossref

DOI: 10.3389/frvir.2024.1433829

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Summary

This study investigates the cognitive control processes underlying driver behavior at intersections, a high-risk traffic scenario often associated with accidents. The research addresses the challenge of balancing ecological validity with experimental control in driving research. While naturalistic studies lack control and traditional simulators restrict field of view, fully immersive virtual reality (VR) offers a realistic environment where specific factors can be manipulated. The authors aimed to determine how right of way, traffic volume, and unexpected critical events (a pedestrian crossing) affect driving behavior and associated brain activity, specifically focusing on EEG oscillatory signatures of cognitive control. The researchers developed a VR driving simulation using a head-mounted display and recorded electroencephalography (EEG) data from 20 participants (after 14 dropouts due to cybersickness). Participants navigated a series of intersections in a fully factorial within-subjects design manipulating three factors: right of way versus give way, presence versus absence of traffic, and an idle versus running pedestrian. Driving behavior, including speed, braking, and acceleration, was recorded alongside EEG data. The EEG analysis focused on theta power (4–7 Hz), an indicator of cognitive control and mental effort, and alpha power (8–12 Hz), an indicator of attention. Data were preprocessed to remove artifacts, and time-frequency analyses were conducted using cluster-based permutation tests. The results demonstrated that participants engaged cognitive control processes when approaching intersections with high traffic volume and when reacting to a critical event involving a pedestrian. These cognitive demands were indexed behaviorally by adjusted driving speeds and proactively by increased theta power in the EEG data. Specifically, participants reduced driving speed when required to yield to traffic and braked in response to the running pedestrian. However, no significant differences were found in the EEG data regarding the right of way condition, although driving behavior showed the expected speed reduction when participants had to yield. The study confirms that theta power increases during situations requiring heightened cognitive control, such as managing high traffic loads or reacting to sudden hazards. The significance of this work lies in demonstrating that immersive VR driving simulations can robustly capture EEG data, particularly in the theta and alpha bands, despite potential movement and electronic artifacts from head-mounted displays. The findings provide novel insights into the neural mechanisms of cognitive control during realistic driving tasks. By validating the use of VR combined with EEG, the study offers a powerful methodological tool for future research into driver attention, fatigue, and decision-making processes in complex traffic environments, potentially aiding in the development of safer driving interfaces and training protocols.

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• cognitive capacity variation

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• Empirical Findings: physiological data
• Methodological Resource: tool software
• Theoretical Contribution: computational model