Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

The authors propose an explainable consciousness indicator using deep learning to quantify arousal and awareness under sleep, anesthesia, and in patients with disorders of consciousness.

Bibliographische Detailangaben
Hauptverfasser: Minji Lee, Leandro R. D. Sanz, Alice Barra, Audrey Wolff, Jaakko O. Nieminen, Melanie Boly, Mario Rosanova, Silvia Casarotto, Olivier Bodart, Jitka Annen, Aurore Thibaut, Rajanikant Panda, Vincent Bonhomme, Marcello Massimini, Giulio Tononi, Steven Laureys, Olivia Gosseries, Seong-Whan Lee
Format: Artikel
Sprache:English
Veröffentlicht: Nature Portfolio 2022-02-01
Schriftenreihe:Nature Communications
Online Zugang:https://doi.org/10.1038/s41467-022-28451-0

Online

https://doi.org/10.1038/s41467-022-28451-0

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