Depth electrode neurofeedback with a virtual reality interface*. Issue 4 (2nd October 2017)

• Record Type: Journal Article
• Authors: Yamin, Hagar Grazya; Gazit, Tomer; Tchemodanov, Natalia; Raz, Gal; Jackont, Gilan; Charles, Fred; Fried, Itzhak; Hendler, Talma; Cavazza, Marc
• Is Part Of: Brain-computer interfaces. Volume 4:Issue 4(2017)
• Page Start: 201
• Page End: 213
• Publication Date: 2017-10-02
• Subjects: Brain–computer interface (BCI) -- neurofeedback (NF) -- electroencephalogram (EEG) -- intracranial depth electrodes; Application development and evaluation -- neurosurgical approaches and methods, affective computing -- signal acquisition: EEG (other); Brain-computer interfaces -- Periodicals; Neurology -- Periodicals; 616.800285
• DOI: 10.1080/2326263X.2017.1338008
• Languages: English
• ISSNs: 2326-263X

Abstract

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.