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  Neurophysiophenomenology – predicting emotional arousal from brain arousal in a virtual reality roller coaster

Mariola, A., Klotzsche, F., Hofmann, S., Nikulin, V. V., Villringer, A., & Gaebler, M. (2018). Neurophysiophenomenology – predicting emotional arousal from brain arousal in a virtual reality roller coaster. Poster presented at MindBrainBody Symposium, Berlin, Germany.

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Mariola et al (2018) - Poster Neurophysiophenomenology.pdf (Postprint), 7MB
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Mariola et al (2018) - Poster Neurophysiophenomenology.pdf
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 Creators:
Mariola, Alberto1, 2, Author
Klotzsche, Felix1, 3, Author           
Hofmann, Simon3, 4, Author                 
Nikulin, Vadim V.3, Author           
Villringer, Arno1, 3, Author           
Gaebler, Michael1, 3, Author           
Affiliations:
1Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              
2Sussex Neuroscience, University of Sussex, Brighton, United Kingdom, ou_persistent22              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
4Amsterdam Brain and Cognition (ABC), University of Amsterdam, the Netherlands, ou_persistent22              

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Free keywords: Human-centered computing; Human computer interaction (HCI); HCI design and evaluation methods; Laboratory experiments; Applied computing; Life and medical sciences; Consumer health
 Abstract: Arousal is a core affect constituted of both bodily and subjective states that prepares an agent to respond to events of the natural environment. While the peripheral physiological components of arousal have been examined also under naturalistic conditions, its neural correlates were suggested mainly on the basis of simplifed experimental designs.  
We used virtual reality (VR) to present a highly immersive and contextually rich scenario of roller coaster rides to evoke naturalistic states of emotional arousal.
Simultaneously, we recorded EEG to validate the suggested neural correlates of arousal in alpha frequency oscillations (8-12Hz) over temporo-parietal cortical areas. To fnd the complex link between these alpha components and the participants’ continuous subjective reports of arousal,
we employed a set of complementary analytical methods coming from machine learning and deep learning.

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 Dates: 2018-03
 Publication Status: Not specified
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Title: MindBrainBody Symposium
Place of Event: Berlin, Germany
Start-/End Date: 2018-03-15 - 2018-03-16
Invited: Yes

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