Yamin, Hagar Grazya, Gazit, Tomer, Tchemodanov, Natalia, Raz, Gal, Jackont, Gilan, Charles, Fred, Fried, Itzhak, Hendler, Talma and Cavazza, Marc ORCID: 0000-0001-6113-9696 (2017) Depth electrode neurofeedback with a virtual reality interface. Brain-Computer Interfaces, 4 (4). pp. 201-213. ISSN 2326-263X (Print), 2326-2621 (Online) (doi:https://doi.org/10.1080/2326263X.2017.1338008)

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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
Additional Information:	© 2017 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Uncontrolled Keywords:	Brain–computer interface (BCI), neurofeedback (NF), electroencephalogram (EEG), intracranial depth electrodes
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Last Modified:	04 Mar 2022 13:07
URI:	http://gala.gre.ac.uk/id/eprint/19813

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