Spatiooral analysis of EEG signal during consciousness using convolutional neural network

Minji Lee; Seul Ki Yeom; Benjamin Baird; Olivia Gosseries; Jakko O. Nieminen; Giulio Tononi; Seong Whan Lee

doi:10.1109/IWW-BCI.2018.8311489

Spatiooral analysis of EEG signal during consciousness using convolutional neural network

Minji Lee, Seul Ki Yeom, Benjamin Baird, Olivia Gosseries, Jakko O. Nieminen, Giulio Tononi, Seong Whan Lee

Department of Brain and Cognitive Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

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.

Original language	English
Title of host publication	2018 6th International Conference on Brain-Computer Interface, BCI 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-3
Number of pages	3
Volume	2018-January
ISBN (Electronic)	9781538625743
DOIs	https://doi.org/10.1109/IWW-BCI.2018.8311489
Publication status	Published - 2018 Mar 9
Event	6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of Duration: 2018 Jan 15 → 2018 Jan 17

Other

Other	6th International Conference on Brain-Computer Interface, BCI 2018
Country	Korea, Republic of
City	GangWon
Period	18/1/15 → 18/1/17

Keywords

classification
consciousness
sedation
sleep
transcranial magnetic stimulation

ASJC Scopus subject areas

Artificial Intelligence
Human-Computer Interaction
Behavioral Neuroscience

Access to Document

10.1109/IWW-BCI.2018.8311489

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Cite this

Lee, M., Yeom, S. K., Baird, B., Gosseries, O., Nieminen, J. O., Tononi, G., & Lee, S. W. (2018). Spatiooral analysis of EEG signal during consciousness using convolutional neural network. In 2018 6th International Conference on Brain-Computer Interface, BCI 2018 (Vol. 2018-January, pp. 1-3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2018.8311489

Spatiooral analysis of EEG signal during consciousness using convolutional neural network. / Lee, Minji; Yeom, Seul Ki; Baird, Benjamin; Gosseries, Olivia; Nieminen, Jakko O.; Tononi, Giulio; Lee, Seong Whan.

2018 6th International Conference on Brain-Computer Interface, BCI 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-3.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, M, Yeom, SK, Baird, B, Gosseries, O, Nieminen, JO, Tononi, G & Lee, SW 2018, Spatiooral analysis of EEG signal during consciousness using convolutional neural network. in 2018 6th International Conference on Brain-Computer Interface, BCI 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-3, 6th International Conference on Brain-Computer Interface, BCI 2018, GangWon, Korea, Republic of, 18/1/15. https://doi.org/10.1109/IWW-BCI.2018.8311489

Lee, Minji ; Yeom, Seul Ki ; Baird, Benjamin ; Gosseries, Olivia ; Nieminen, Jakko O. ; Tononi, Giulio ; Lee, Seong Whan. / Spatiooral analysis of EEG signal during consciousness using convolutional neural network. 2018 6th International Conference on Brain-Computer Interface, BCI 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-3

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