Driving with Intuition: A Preregistered Study about the EEG Anticipation of Simulated Random Car Accidents

Duma, Gian Marco; Mento, Giovanni; Manari, Tommaso; Martinelli, Massimiliano; Tressoldi, Patrizio · 2017 · Crossref

DOI: 10.1371/journal.pone.0170370

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Summary

This preregistered study investigates whether the brain exhibits anticipatory neural activity preceding statistically unpredictable, dichotomic events within an ecological context. While previous research has established that the brain actively constructs reality through predictive mechanisms, most paradigms rely on predictable stimuli. The authors aimed to determine if Event-Related Potentials (ERPs) could differentiate between two random outcomes—simulated car crashes and non-crashes—before the events occurred, thereby testing the hypothesis of Predictive Psychophysiological Anticipatory Activity (PPAA) in a realistic driving simulation. The experiment involved 40 university students who participated in a simplified driving simulation using EEG recording. The design included a baseline task, a passive task, and an active task. In the passive task, participants observed a car moving along a street where trials randomly ended in either a crash or a safe termination, with no cues predicting the outcome. In the active task, participants attempted to avoid crashes by decelerating based on intuition. EEG data were analyzed for the passive task, focusing on pre-stimulus activity from -3,000 ms to stimulus onset. Statistical analyses included cluster-based permutation tests and Bayesian parameter estimation to compare ERP amplitudes across conditions. Behavioral performance in the active task was also assessed to determine if predictions exceeded chance levels. Behavioral results from the active task showed no statistical evidence of above-chance performance for predicting either crashes or non-crashes. However, ERP analysis of the passive task revealed distinct pre-stimulus neural patterns. Approximately 1,000 ms before the onset of a crash, a fronto-central negativity emerged, distinguishing crash trials from other conditions. Conversely, trials ending without a crash were characterized by a whole-scalp distributed positivity during the same pre-stimulus window. No significant differences were observed in the earlier interval (-3,000 to -1,000 ms). Exploratory time-on-task and spectral density analyses further characterized the dynamics of this anticipatory activity, though the primary finding remained the differential ERP signatures preceding the random outcomes. The findings suggest that the brain generates distinct anticipatory neural signals even for statistically unpredictable, dichotomic events, supporting the view that the brain actively constructs forthcoming reality rather than passively processing stimuli. The presence of specific pre-stimulus ERPs for threatening versus safe outcomes implies that the brain may utilize different neural mechanisms to anticipate potential dangers. These results have implications for the development of human-machine smart systems, suggesting that EEG-based markers could potentially be integrated into vehicle safety technologies to detect driver anticipation of imminent accidents.

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