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Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG

BACKGROUND: The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchro...

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Autores principales: Jalili, Mahdi, Lavoie, Suzie, Deppen, Patricia, Meuli, Reto, Do, Kim Q., Cuénod, Michel, Hasler, Martin, De Feo, Oscar, Knyazeva, Maria G.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2020441/
https://www.ncbi.nlm.nih.gov/pubmed/17957243
http://dx.doi.org/10.1371/journal.pone.0001059
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author Jalili, Mahdi
Lavoie, Suzie
Deppen, Patricia
Meuli, Reto
Do, Kim Q.
Cuénod, Michel
Hasler, Martin
De Feo, Oscar
Knyazeva, Maria G.
author_facet Jalili, Mahdi
Lavoie, Suzie
Deppen, Patricia
Meuli, Reto
Do, Kim Q.
Cuénod, Michel
Hasler, Martin
De Feo, Oscar
Knyazeva, Maria G.
author_sort Jalili, Mahdi
collection PubMed
description BACKGROUND: The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals. METHODS/RESULTS: To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels) EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series—the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity. CONCLUSION/SIGNIFICANCE: The new method of multivariate synchronization significantly boosts the potential of EEG as an imaging technique compatible with other imaging modalities. Its application to schizophrenia research shows that schizophrenia can be explained within the concept of neural dysconnection across and within large-scale brain networks.
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spelling pubmed-20204412007-10-24 Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG Jalili, Mahdi Lavoie, Suzie Deppen, Patricia Meuli, Reto Do, Kim Q. Cuénod, Michel Hasler, Martin De Feo, Oscar Knyazeva, Maria G. PLoS One Research Article BACKGROUND: The dysconnection hypothesis has been proposed to account for pathophysiological mechanisms underlying schizophrenia. Widespread structural changes suggesting abnormal connectivity in schizophrenia have been imaged. A functional counterpart of the structural maps would be the EEG synchronization maps. However, due to the limits of currently used bivariate methods, functional correlates of dysconnection are limited to the isolated measurements of synchronization between preselected pairs of EEG signals. METHODS/RESULTS: To reveal a whole-head synchronization topography in schizophrenia, we applied a new method of multivariate synchronization analysis called S-estimator to the resting dense-array (128 channels) EEG obtained from 14 patients and 14 controls. This method determines synchronization from the embedding dimension in a state-space domain based on the theoretical consequence of the cooperative behavior of simultaneous time series—the shrinking of the state-space embedding dimension. The S-estimator imaging revealed a specific synchronization landscape in schizophrenia patients. Its main features included bilaterally increased synchronization over temporal brain regions and decreased synchronization over the postcentral/parietal region neighboring the midline. The synchronization topography was stable over the course of several months and correlated with the severity of schizophrenia symptoms. In particular, direct correlations linked positive, negative, and general psychopathological symptoms to the hyper-synchronized temporal clusters over both hemispheres. Along with these correlations, general psychopathological symptoms inversely correlated within the hypo-synchronized postcentral midline region. While being similar to the structural maps of cortical changes in schizophrenia, the S-maps go beyond the topography limits, demonstrating a novel aspect of the abnormalities of functional cooperation: namely, regionally reduced or enhanced connectivity. CONCLUSION/SIGNIFICANCE: The new method of multivariate synchronization significantly boosts the potential of EEG as an imaging technique compatible with other imaging modalities. Its application to schizophrenia research shows that schizophrenia can be explained within the concept of neural dysconnection across and within large-scale brain networks. Public Library of Science 2007-10-24 /pmc/articles/PMC2020441/ /pubmed/17957243 http://dx.doi.org/10.1371/journal.pone.0001059 Text en Jalili 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Jalili, Mahdi
Lavoie, Suzie
Deppen, Patricia
Meuli, Reto
Do, Kim Q.
Cuénod, Michel
Hasler, Martin
De Feo, Oscar
Knyazeva, Maria G.
Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
title Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
title_full Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
title_fullStr Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
title_full_unstemmed Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
title_short Dysconnection Topography in Schizophrenia Revealed with State-Space Analysis of EEG
title_sort dysconnection topography in schizophrenia revealed with state-space analysis of eeg
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2020441/
https://www.ncbi.nlm.nih.gov/pubmed/17957243
http://dx.doi.org/10.1371/journal.pone.0001059
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