Introduction Arachnophobia, the fear of spiders, is one of the most common phobias globally that induce anxiety and other mental illnesses if left untreated. Virtual reality (VR)-based exposure therapy (VRET) has recently emerged as a viable solution for treating different phobias. In this work, we present a proof-of-concept study toward the development of a neuroadaptive and individualized VRET system (VRSpi) that integrates virtual reality with real-time neurophysiological monitoring, intended as a future tool for personalized arachnophobia treatment. VRSpi is designed to monitor brain and heart rate (HR) responses in real-time to automatically control the intensity of the fear stimulus in an adaptive manner. Methods Twenty-one healthy participants not clinically diagnosed with arachnophobia attended the study, indicating no or moderate fear of spiders. The moderate fear group tested the efficacy of our system towards treating their arachnophobia. Since fear-related emotions are primarily processed in the right frontal hemisphere of the brain, the study used the frontal alpha asymmetry (FAA) index from frontal electroencephalography (EEG) channels, along with HR, to automatically assess the participant’s fear level during VR spider exposure. Results We could demonstrate that incorporating FAA index measurements could improve personalization in VRET by allowing the VR environment to automatically adapt to each individual’s fear level, potentially improving treatment effectiveness, though its direct impact on clinical outcomes require further study. Moreover, our findings indicate that escalating spider scene exposure is associated with reduced oscillatory power in faster bands (alpha, beta, and gamma) and increased frontal theta activity, reflecting a neural state characterized by heightened vigilance, emotional reactivity, and regulatory effort. In addition, these effects were accompanied by systematic right-frontal EEG shifts, characteristic HR changes, and reliable discrimination between low and high fear states. Discussion Future work should address the clinical integration of neuroadaptive exposure systems. In practice, EEG-based adaptations must be reliable, stable across sessions, and robust to artifacts so therapists can use them as decision-support tools rather than replacements for clinical judgment. Conservative thresholds, transparent logic, and clinician override options may be essential. While this work focuses on feasibility, these practical factors are key to translating neuroadaptive VRET into usable therapies.
Wriessnegger et al. (Wed,) studied this question.