Online Detection of Real-World Faces in ECoG Signals

Previous neuroimaging studies have reported that the ventral temporal cortex (VTC) processes visual stimuli and thereby establish visual categories, which can be detected in electrophysiological signals such as electrocorticography (ECoG). However, most of the studies are based on visual stimulation...

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Bibliographic Details
Main Authors: Kapeller, Christoph, Grunwald, Johannes, Kamada, Kyousuke, Ogawa, Hiroshi, Fukuyama, Shusei, Sanada, Takahiro, Pruckl, Robert, Guger, Christoph
Format: Conference Proceeding
Language:English
Subjects:
Band-pass filters
BCI
Biomedical imaging
Broadband Gamma
Calibration
Decoding
ECoG
Face
IIR filters
Kanji
Real-time systems
Visualization
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Summary:Previous neuroimaging studies have reported that the ventral temporal cortex (VTC) processes visual stimuli and thereby establish visual categories, which can be detected in electrophysiological signals such as electrocorticography (ECoG). However, most of the studies are based on visual stimulation through a computer. Thus, the degree to which those categories can be generalized is unclear under real-world conditions. This study extends the findings of a previous experiment, which aimed in real-time detection of visual perception, and investigated whether neural face and kanji categories obtained by computer stimuli can be confirmed in a real-world scenario. The real-time decoder accuracy and latency of two patients with epilepsy revealed that real-world faces and kanji can be detected with 79.9% and 28.4% accuracy, respectively, showing an average online detection latency of 447 ms with respect to presentation time. Hence, the VTC cortex elicits robust and similar responses to computer stimuli and real-world face, leading to a powerful brain-computer interface to track a person's attention in a real-world scenario.
ISSN:2577-1655
DOI:10.1109/SMC.2018.00030