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Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes

This article presents a novel connectivity analysis method that is suitable for multi-node networks such as EEG, MEG or EcOG electrode recordings. Its diagnostic power and ability to interpret brain states in schizophrenia is demonstrated on a set of 50 subjects that constituted of 25 healthy and 25...

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Detalles Bibliográficos
Autores principales: Dvey-Aharon, Zack, Fogelson, Noa, Peled, Abraham, Intrator, Nathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648105/
https://www.ncbi.nlm.nih.gov/pubmed/29049302
http://dx.doi.org/10.1371/journal.pone.0185852
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author Dvey-Aharon, Zack
Fogelson, Noa
Peled, Abraham
Intrator, Nathan
author_facet Dvey-Aharon, Zack
Fogelson, Noa
Peled, Abraham
Intrator, Nathan
author_sort Dvey-Aharon, Zack
collection PubMed
description This article presents a novel connectivity analysis method that is suitable for multi-node networks such as EEG, MEG or EcOG electrode recordings. Its diagnostic power and ability to interpret brain states in schizophrenia is demonstrated on a set of 50 subjects that constituted of 25 healthy and 25 diagnosed with schizophrenia and treated with medication. The method can also be used for the automatic detection of schizophrenia; it exhibits higher sensitivity than state-of-the-art methods with no false positives. The detection is based on an analysis from a minute long pattern-recognition computer task. Moreover, this connectivity analysis leads naturally to an optimal choice of electrodes and hence to highly statistically significant results that are based on data from only 3–5 electrodes. The method is general and can be used for the diagnosis of other psychiatric conditions, provided an appropriate computer task is devised.
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spelling pubmed-56481052017-11-03 Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes Dvey-Aharon, Zack Fogelson, Noa Peled, Abraham Intrator, Nathan PLoS One Research Article This article presents a novel connectivity analysis method that is suitable for multi-node networks such as EEG, MEG or EcOG electrode recordings. Its diagnostic power and ability to interpret brain states in schizophrenia is demonstrated on a set of 50 subjects that constituted of 25 healthy and 25 diagnosed with schizophrenia and treated with medication. The method can also be used for the automatic detection of schizophrenia; it exhibits higher sensitivity than state-of-the-art methods with no false positives. The detection is based on an analysis from a minute long pattern-recognition computer task. Moreover, this connectivity analysis leads naturally to an optimal choice of electrodes and hence to highly statistically significant results that are based on data from only 3–5 electrodes. The method is general and can be used for the diagnosis of other psychiatric conditions, provided an appropriate computer task is devised. Public Library of Science 2017-10-19 /pmc/articles/PMC5648105/ /pubmed/29049302 http://dx.doi.org/10.1371/journal.pone.0185852 Text en © 2017 Dvey-Aharon et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dvey-Aharon, Zack
Fogelson, Noa
Peled, Abraham
Intrator, Nathan
Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes
title Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes
title_full Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes
title_fullStr Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes
title_full_unstemmed Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes
title_short Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes
title_sort connectivity maps based analysis of eeg for the advanced diagnosis of schizophrenia attributes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648105/
https://www.ncbi.nlm.nih.gov/pubmed/29049302
http://dx.doi.org/10.1371/journal.pone.0185852
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