Decoding subjective emotional arousal from EEG during an immersive virtual reality experience

Area of Science:

• Neuroscience
• Psychology
• Virtual Reality

Background:

• Immersive virtual reality (VR) offers naturalistic experimental control for neuroscientific studies.
• Dynamic VR stimuli present methodological challenges for studying affective experiences.
• Emotional arousal is a fundamental aspect of affective experience.

Purpose of the Study:

• To investigate the relationship between emotional arousal and parieto-occipital alpha power.
• To explore neurophysiological correlates of emotional arousal in naturalistic settings.
• To validate methods combining VR, EEG, and subjective ratings.

Main Methods:

• 37 healthy adults underwent an immersive VR experience (e.g., rollercoaster rides) with concurrent electroencephalography (EEG) recording.
• Participants continuously rated their subjective emotional arousal during a replay of their VR experience.
• EEG signals were analyzed using signal decomposition and machine learning (LSTM RNN) to link alpha power and arousal.

Main Results:

• A significant association was confirmed between emotional arousal and parieto-occipital alpha power.
• Methods successfully maximized comodulation between alpha power and arousal ratings.
• Machine learning models could decode periods of high and low emotional arousal.

Conclusions:

• The study successfully combined EEG and immersive VR for neuroscientific research.
• Findings extend understanding of the neurophysiology of emotional arousal in real-world contexts.
• This approach validates naturalistic methods for studying affective neuroscience.