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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 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 languageEnglish
Title of host publication2018 6th International Conference on Brain-Computer Interface, BCI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-3
Number of pages3
ISBN (Electronic)9781538625743
DOIs
Publication statusPublished - 2018 Mar 9
Event6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of
Duration: 2018 Jan 152018 Jan 17

Publication series

Name2018 6th International Conference on Brain-Computer Interface, BCI 2018
Volume2018-January

Other

Other6th International Conference on Brain-Computer Interface, BCI 2018
Country/TerritoryKorea, Republic of
CityGangWon
Period18/1/1518/1/17

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • classification
  • consciousness
  • sedation
  • sleep
  • transcranial magnetic stimulation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Behavioral Neuroscience

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