Article (Scientific journals)
Granger causality analysis of steady-state electroencephalographic signals during propofol-induced anaesthesia.
Barrett, Adam B.; Murphy, Michael; Bruno, Marie-Aurélie et al.
2012In PLoS ONE, 7 (1), p. 29072
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Copyright: © 2012 Barrett et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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Keywords :
Anesthesia; Computer Simulation; Consciousness/drug effects; Cortical Synchronization/drug effects; Electroencephalography/instrumentation/methods; Gyrus Cinguli/drug effects/physiology; Humans; Propofol/administration & dosage/pharmacology; Signal Processing, Computer-Assisted; Statistics as Topic; Wakefulness/drug effects
Abstract :
[en] Changes in conscious level have been associated with changes in dynamical integration and segregation among distributed brain regions. Recent theoretical developments emphasize changes in directed functional (i.e., causal) connectivity as reflected in quantities such as 'integrated information' and 'causal density'. Here we develop and illustrate a rigorous methodology for assessing causal connectivity from electroencephalographic (EEG) signals using Granger causality (GC). Our method addresses the challenges of non-stationarity and bias by dividing data into short segments and applying permutation analysis. We apply the method to EEG data obtained from subjects undergoing propofol-induced anaesthesia, with signals source-localized to the anterior and posterior cingulate cortices. We found significant increases in bidirectional GC in most subjects during loss-of-consciousness, especially in the beta and gamma frequency ranges. Corroborating a previous analysis we also found increases in synchrony in these ranges; importantly, the Granger causality analysis showed higher inter-subject consistency than the synchrony analysis. Finally, we validate our method using simulated data generated from a model for which GC values can be analytically derived. In summary, our findings advance the methodology of Granger causality analysis of EEG data and carry implications for integrated information and causal density theories of consciousness.
Disciplines :
Anesthesia & intensive care
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Barrett, Adam B.;  University of Sussex (United Kingdom) > Department of Informatics > Sackler Centre for Consciousness Science
Murphy, Michael;  University of Wisconsin-Madison > Department of Psychiatry
Bruno, Marie-Aurélie ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Noirhomme, Quentin ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Boly, Mélanie ;  Université de Liège - ULiège > Département des sciences cliniques > Neurologie
Laureys, Steven  ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Seth, Anil K.
Language :
English
Title :
Granger causality analysis of steady-state electroencephalographic signals during propofol-induced anaesthesia.
Publication date :
2012
Journal title :
PLoS ONE
eISSN :
1932-6203
Publisher :
Public Library of Science, San Franscisco, United States - California
Volume :
7
Issue :
1
Pages :
e29072
Peer reviewed :
Peer Reviewed verified by ORBi
Funding text :
AKS and ABB are supported by Engineering and Physical Sciences Research Council Leadership Fellowship EP/G007543/1. Support is also gratefully acknowledged from the Dr. Mortimer and Theresa Sackler Foundation. SL is a Belgian Funds for Scientific Research (FRS) Senior Research Associate and MAB, QN and MB are FRS Postdoctoral Researchers. This work was also supported by the European Commission (DECODER), Fondazione Europea di Ricerca Biomedica, McDonnell Foundation, Mind Science Foundation, Public Utility Foundation “Université Européenne du Travail” and the University of Liège. Possible inaccuracies of information are the responsibility of the project team. The text reflects solely the views of its authors. The European Commission is not liable for any use that may be made of the information contained herein. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Available on ORBi :
since 18 February 2012

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