Reactive and predictive processes during unpredictable driving hazards in virtual reality: an exploratory brain and body study with multimodal neurophysiological monitoring
Anticipatory neurophysiological activity before unpredictable emotional events has been reported for decades, but the effects are small, difficult to replicate, and obtained almost exclusively in stripped-down laboratory paradigms: brief, repetitive screen stimuli in a single modality. Whether they reflect genuine predictive processes or methodological artefacts remains debated. One possibility rarely tested is that the settings themselves mute the effect: the brain prepares for events that unfold in time and engage multiple senses, not for static images. We examined anticipation in an immersive virtual reality (VR) driving simulation whose collision outcomes were assigned by a quantum random number generator, while electroencephalography (EEG), photoplethysmography (PPG), electromyography (EMG), electrooculography (EOG) and inertial measurement (IMU) signals were recorded simultaneously from a single wireless dry-electrode headset built into the VR display. Sixteen participants passively observed 120 driving sequences ending in a collision or no collision. A minimum-phase causal filter kept post-stimulus activity from leaking into the pre-stimulus window, and length-matched pre- and post-stimulus windows were analysed identically with mass-univariate hierarchical general linear models under permutation cluster correction, complemented by machine learning classification across held-out participants. Two post-stimulus clusters differentiated the conditions, the largest peaking at 451.6 ms (d = -1.35), with broadband power modulation robust to baseline modelling and decoded from held-out participants with up to 93.8% accuracy. No time-domain effect or decodable information preceded stimulus onset, but a broadband spectral difference did, surviving preregistered controls for gambler's-fallacy, expectation bias (run length), time-on-task build-up and ocular or facial-muscle artefact: directionally consistent in 13 of 15 participants, with pre- and post-stimulus power coupled in all 16. Heart rate differentiated the conditions neither alone nor when added to the classifier. The study was preregistered; the BIDS-format data, analysis code and a new open-source EEGLAB plugin are publicly available. Because data collection ended early, all findings are exploratory.