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

affective computing computational affective neuroscience deep learning ecological validity human machine learning naturalistic stimuli neuroscience

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
28 10 2021
Historique:
received: 11 11 2020
accepted: 27 10 2021
pubmed: 29 10 2021
medline: 27 1 2022
entrez: 28 10 2021
Statut: epublish

Résumé

Immersive virtual reality (VR) enables naturalistic neuroscientific studies while maintaining experimental control, but dynamic and interactive stimuli pose methodological challenges. We here probed the link between emotional arousal, a fundamental property of affective experience, and parieto-occipital alpha power under naturalistic stimulation: 37 young healthy adults completed an immersive VR experience, which included rollercoaster rides, while their EEG was recorded. They then continuously rated their subjective emotional arousal while viewing a replay of their experience. The association between emotional arousal and parieto-occipital alpha power was tested and confirmed by (1) decomposing the continuous EEG signal while maximizing the comodulation between alpha power and arousal ratings and by (2) decoding periods of high and low arousal with discriminative common spatial patterns and a long short-term memory recurrent neural network. We successfully combine EEG and a naturalistic immersive VR experience to extend previous findings on the neurophysiology of emotional arousal towards real-world neuroscience. Human emotions are complex and difficult to study. It is particularly difficult to study emotional arousal, this is, how engaging, motivating, or intense an emotional experience is. To learn how the human brain processes emotions, researchers usually show emotional images to participants in the laboratory while recording their brain activity. But viewing sequences of photos is not quite like experiencing the dynamic and interactive emotions people face in everyday life. New technologies, such as immersive virtual reality, allow individuals to experience dynamic and interactive situations, giving scientists the opportunity to study human emotions in more realistic settings. These tools could lead to new insights regarding emotions and emotional arousal. Hofmann, Klotzsche, Mariola et al. show that virtual reality can be a useful tool for studying emotions and emotional arousal. In the experiment, 37 healthy young adults put on virtual reality glasses and ‘experienced’ two virtual rollercoaster rides. During the virtual rides, Hofmann, Klotzsche, Mariola et al. measured the participants' brain activity using a technique called electroencephalography (EEG). Then, the participants rewatched their rides and rated how emotionally arousing each moment was. Three different computer modeling techniques were then used to predict the participant’s emotional arousal based on their brain activity. The experiments confirmed the results of traditional laboratory experiments and showed that the brain’s alpha waves can be used to predict emotional arousal. This suggests that immersive virtual reality is a useful tool for studying human emotions in circumstances that are more like everyday life. This may make future discoveries about human emotions more useful for real-life applications such as mental health care.

Autres résumés

Type: plain-language-summary (eng)
Human emotions are complex and difficult to study. It is particularly difficult to study emotional arousal, this is, how engaging, motivating, or intense an emotional experience is. To learn how the human brain processes emotions, researchers usually show emotional images to participants in the laboratory while recording their brain activity. But viewing sequences of photos is not quite like experiencing the dynamic and interactive emotions people face in everyday life. New technologies, such as immersive virtual reality, allow individuals to experience dynamic and interactive situations, giving scientists the opportunity to study human emotions in more realistic settings. These tools could lead to new insights regarding emotions and emotional arousal. Hofmann, Klotzsche, Mariola et al. show that virtual reality can be a useful tool for studying emotions and emotional arousal. In the experiment, 37 healthy young adults put on virtual reality glasses and ‘experienced’ two virtual rollercoaster rides. During the virtual rides, Hofmann, Klotzsche, Mariola et al. measured the participants' brain activity using a technique called electroencephalography (EEG). Then, the participants rewatched their rides and rated how emotionally arousing each moment was. Three different computer modeling techniques were then used to predict the participant’s emotional arousal based on their brain activity. The experiments confirmed the results of traditional laboratory experiments and showed that the brain’s alpha waves can be used to predict emotional arousal. This suggests that immersive virtual reality is a useful tool for studying human emotions in circumstances that are more like everyday life. This may make future discoveries about human emotions more useful for real-life applications such as mental health care.

Identifiants

pubmed: 34708689
doi: 10.7554/eLife.64812
pii: 64812
pmc: PMC8673835
doi:
pii:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2021, Hofmann et al.

Déclaration de conflit d'intérêts

SH, FK, AM, VN, AV, MG No competing interests declared

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Auteurs

Simon M Hofmann (SM)

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Felix Klotzsche (F)

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Humboldt-Universität zu Berlin, Faculty of Philosophy, Berlin School of Mind and Brain, Berlin, Germany.

Alberto Mariola (A)

Sackler Centre for Consciousness Science, School of Engineering and Informatics, University of Sussex, Brighton, United Kingdom.
Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.

Vadim Nikulin (V)

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.

Arno Villringer (A)

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Humboldt-Universität zu Berlin, Faculty of Philosophy, Berlin School of Mind and Brain, Berlin, Germany.

Michael Gaebler (M)

Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Humboldt-Universität zu Berlin, Faculty of Philosophy, Berlin School of Mind and Brain, Berlin, Germany.

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