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Depth electrode neurofeedback with a virtual reality interface

Yamin, Hagar Grazya, Gazit, Tomer, Tchemodanov, Natalia, Raz, Gal, Jackont, Gilan, Charles, Fred, Fried, Itzhak, Hendler, Talma, Cavazza, Marc (2017) Depth electrode neurofeedback with a virtual reality interface. Brain-Computer Interfaces, 4 (4). pp. 201-213. ISSN 2326-263X. E-ISSN 2326-2621. (doi:10.1080/2326263X.2017.1338008) (KAR id:62139)

Abstract

Invasive brain–computer interfaces (BCI) provide better signal quality in terms of spatial localization, frequencies and signal/noise ratio, in addition to giving access to deep brain regions that play important roles in cognitive or affective processes. Despite some anecdotal attempts, little work has explored the possibility of integrating such BCI input into more sophisticated interactive systems like those which can be developed with game engines. In this article, we integrated an amygdala depth electrode recorder with a virtual environment controlling a virtual crowd. Subjects were asked to down regulate their amygdala using the level of unrest in the virtual room as feedback on how successful they were. We report early results which suggest that users adapt very easily to this paradigm and that the timing and fluctuations of amygdala activity during self-regulation can be matched by crowd animation in the virtual room. This suggests that depth electrodes could also serve as high-performance affective interfaces, notwithstanding their strictly limited availability, justified on medical grounds only.

Item Type: Article
DOI/Identification number: 10.1080/2326263X.2017.1338008
Uncontrolled keywords: Brain–computer interface (BCI); neurofeedback (NF); electroencephalogram (EEG); intracranial depth electrodes
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.9.H85 Human computer interaction
R Medicine > RC Internal medicine > RC321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Marc Cavazza
Date Deposited: 24 Jun 2017 14:47 UTC
Last Modified: 05 Nov 2024 10:56 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/62139 (The current URI for this page, for reference purposes)

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