@inproceedings{f4aa6095a55247dcb2efc4141acf5bb1,
title = "Spatiooral analysis of EEG signal during consciousness using convolutional neural network",
abstract = "Electroencephalogram (EEG) measurement could help to distinguish the level of consciousness in an individual without requiring a behavioral response, which could be useful as a diagnostic aid in patients with disorders of consciousness. In this study, we explored the EEG-evoked perturbation and analyzed consciousness using event-related spectral perturbation and convolutional neural network. We observed a novel EEG neurophysiological signature that can be used to monitor brain activity during unconsciousness. Also, the performance accuracy in the parietal region was higher than in the frontal region. The sensitivity for conscious experience was 90.9%, whereas sensitivity for unconscious experience was at the chance level in the parietal region. These results could be evidence for the importance of the posterior hot zone and could help shed light on the internal neural dynamics related to conscious experience.",
keywords = "classification, consciousness, sedation, sleep, transcranial magnetic stimulation",
author = "Minji Lee and Yeom, {Seul Ki} and Benjamin Baird and Olivia Gosseries and Nieminen, {Jakko O.} and Giulio Tononi and Lee, {Seong Whan}",
note = "Funding Information: This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Publisher Copyright: {\textcopyright} 2018 IEEE.; 6th International Conference on Brain-Computer Interface, BCI 2018 ; Conference date: 15-01-2018 Through 17-01-2018",
year = "2018",
month = mar,
day = "9",
doi = "10.1109/IWW-BCI.2018.8311489",
language = "English",
series = "2018 6th International Conference on Brain-Computer Interface, BCI 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--3",
booktitle = "2018 6th International Conference on Brain-Computer Interface, BCI 2018",
}