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Narrative Review: Quantitative EEG in Disorders of Consciousness.
Wutzl, Betty; Golaszewski, Stefan M; Leibnitz, Kenji; Langthaler, Patrick B; Kunz, Alexander B; Leis, Stefan; Schwenker, Kerstin; Thomschewski, Aljoscha; Bergmann, Jürgen; Trinka, Eugen.
Afiliación
  • Wutzl B; Graduate School of Information Science and Technology, Osaka University, Suita 565-0871, Japan.
  • Golaszewski SM; Symbiotic Intelligent Systems Research Center, Osaka University, Suita 565-0871, Japan.
  • Leibnitz K; Department of Neurology, Christian Doppler Medical Center, and Centre for Cognitive Neuroscience, Paracelsus Medical University, Affiliated Member of the European Reference Network EpiCARE, 5020 Salzburg, Austria.
  • Langthaler PB; Karl Landsteiner Institute for Neurorehabilitation and Space Neurology, 5020 Salzburg, Austria.
  • Kunz AB; Neuroscience Institute, Christian Doppler Medical Center, and Centre for Cognitive Neuroscience, Paracelsus Medical University, 5020 Salzburg, Austria.
  • Leis S; Graduate School of Information Science and Technology, Osaka University, Suita 565-0871, Japan.
  • Schwenker K; Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita 565-0871, Japan.
  • Thomschewski A; Department of Neurology, Christian Doppler Medical Center, and Centre for Cognitive Neuroscience, Paracelsus Medical University, Affiliated Member of the European Reference Network EpiCARE, 5020 Salzburg, Austria.
  • Bergmann J; Department of Mathematics, Paris Lodron University of Salzburg, 5020 Salzburg, Austria.
  • Trinka E; Team Biostatistics and Big Medical Data, IDA Lab Salzburg, Paracelsus Medical University, 5020 Salzburg, Austria.
Brain Sci ; 11(6)2021 May 25.
Article en En | MEDLINE | ID: mdl-34070647
In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Brain Sci Año: 2021 Tipo del documento: Article País de afiliación: Japón

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Brain Sci Año: 2021 Tipo del documento: Article País de afiliación: Japón
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