Intra- and inter-frequency brain network structure in health and schizophrenia.

Empirical studies over the past two decades have provided support for the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically mediated diagnostic biomarkers and are thought to underlie alter...

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Autores principales:	Felix Siebenhühner, Shennan A Weiss, Richard Coppola, Daniel R Weinberger, Danielle S Bassett
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4bfd335b15474578ac2c13af1489735a
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spelling	oai:doaj.org-article:4bfd335b15474578ac2c13af1489735a2021-11-18T08:58:13ZIntra- and inter-frequency brain network structure in health and schizophrenia.1932-620310.1371/journal.pone.0072351https://doaj.org/article/4bfd335b15474578ac2c13af1489735a2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23991097/?tool=EBIhttps://doaj.org/toc/1932-6203Empirical studies over the past two decades have provided support for the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically mediated diagnostic biomarkers and are thought to underlie altered cognitive functions such as working memory. However, the nature of this dysconnectivity remains far from understood. In this study, we perform an extensive analysis of functional connectivity patterns extracted from MEG data in 14 subjects with schizophrenia and 14 healthy controls during a 2-back working memory task. We investigate uni-, bi- and multivariate properties of sensor time series by computing wavelet entropy of and correlation between time series, and by constructing binary networks of functional connectivity both within and between classical frequency bands ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]). Networks are based on the mutual information between wavelet time series, and estimated for each trial window separately, enabling us to consider both network topology and network dynamics. We observed significant decreases in time series entropy and significant increases in functional connectivity in the schizophrenia group in comparison to the healthy controls and identified an inverse relationship between these measures across both subjects and sensors that varied over frequency bands and was more pronounced in controls than in patients. The topological organization of connectivity was altered in schizophrenia specifically in high frequency [Formula: see text] and [Formula: see text] band networks as well as in the [Formula: see text]-[Formula: see text] cross-frequency networks. Network topology varied over trials to a greater extent in patients than in controls, suggesting disease-associated alterations in dynamic network properties of brain function. Our results identify signatures of aberrant neurophysiological behavior in schizophrenia across uni-, bi- and multivariate scales and lay the groundwork for further clinical studies that might lead to the discovery of new intermediate phenotypes.Felix SiebenhühnerShennan A WeissRichard CoppolaDaniel R WeinbergerDanielle S BassettPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 8, p e72351 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Felix Siebenhühner Shennan A Weiss Richard Coppola Daniel R Weinberger Danielle S Bassett Intra- and inter-frequency brain network structure in health and schizophrenia.
description	Empirical studies over the past two decades have provided support for the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically mediated diagnostic biomarkers and are thought to underlie altered cognitive functions such as working memory. However, the nature of this dysconnectivity remains far from understood. In this study, we perform an extensive analysis of functional connectivity patterns extracted from MEG data in 14 subjects with schizophrenia and 14 healthy controls during a 2-back working memory task. We investigate uni-, bi- and multivariate properties of sensor time series by computing wavelet entropy of and correlation between time series, and by constructing binary networks of functional connectivity both within and between classical frequency bands ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]). Networks are based on the mutual information between wavelet time series, and estimated for each trial window separately, enabling us to consider both network topology and network dynamics. We observed significant decreases in time series entropy and significant increases in functional connectivity in the schizophrenia group in comparison to the healthy controls and identified an inverse relationship between these measures across both subjects and sensors that varied over frequency bands and was more pronounced in controls than in patients. The topological organization of connectivity was altered in schizophrenia specifically in high frequency [Formula: see text] and [Formula: see text] band networks as well as in the [Formula: see text]-[Formula: see text] cross-frequency networks. Network topology varied over trials to a greater extent in patients than in controls, suggesting disease-associated alterations in dynamic network properties of brain function. Our results identify signatures of aberrant neurophysiological behavior in schizophrenia across uni-, bi- and multivariate scales and lay the groundwork for further clinical studies that might lead to the discovery of new intermediate phenotypes.
format	article
author	Felix Siebenhühner Shennan A Weiss Richard Coppola Daniel R Weinberger Danielle S Bassett
author_facet	Felix Siebenhühner Shennan A Weiss Richard Coppola Daniel R Weinberger Danielle S Bassett
author_sort	Felix Siebenhühner
title	Intra- and inter-frequency brain network structure in health and schizophrenia.
title_short	Intra- and inter-frequency brain network structure in health and schizophrenia.
title_full	Intra- and inter-frequency brain network structure in health and schizophrenia.
title_fullStr	Intra- and inter-frequency brain network structure in health and schizophrenia.
title_full_unstemmed	Intra- and inter-frequency brain network structure in health and schizophrenia.
title_sort	intra- and inter-frequency brain network structure in health and schizophrenia.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/4bfd335b15474578ac2c13af1489735a
work_keys_str_mv	AT felixsiebenhuhner intraandinterfrequencybrainnetworkstructureinhealthandschizophrenia AT shennanaweiss intraandinterfrequencybrainnetworkstructureinhealthandschizophrenia AT richardcoppola intraandinterfrequencybrainnetworkstructureinhealthandschizophrenia AT danielrweinberger intraandinterfrequencybrainnetworkstructureinhealthandschizophrenia AT daniellesbassett intraandinterfrequencybrainnetworkstructureinhealthandschizophrenia
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Intra- and inter-frequency brain network structure in health and schizophrenia.

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