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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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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. |
format | Online Article Text |
id | pubmed-5648105 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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