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Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder
BACKGROUND: Dysconnectivity in schizophrenia can be understood in terms of dysfunctional integration of a distributed network of brain regions. Here we propose a new methodology to analyze complex networks based on semi-metric behavior, whereby higher levels of semi-metricity may represent a higher...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4644247/ https://www.ncbi.nlm.nih.gov/pubmed/26740914 http://dx.doi.org/10.1016/j.nicl.2015.10.003 |
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author | Peeters, Sanne Simas, Tiago Suckling, John Gronenschild, Ed Patel, Ameera Habets, Petra van Os, Jim Marcelis, Machteld |
author_facet | Peeters, Sanne Simas, Tiago Suckling, John Gronenschild, Ed Patel, Ameera Habets, Petra van Os, Jim Marcelis, Machteld |
author_sort | Peeters, Sanne |
collection | PubMed |
description | BACKGROUND: Dysconnectivity in schizophrenia can be understood in terms of dysfunctional integration of a distributed network of brain regions. Here we propose a new methodology to analyze complex networks based on semi-metric behavior, whereby higher levels of semi-metricity may represent a higher level of redundancy and dispersed communication. It was hypothesized that individuals with (increased risk for) psychotic disorder would have more semi-metric paths compared to controls and that this would be associated with symptoms. METHODS: Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 unaffected siblings and 72 controls. Semi-metric percentages (SMP) at the whole brain, hemispheric and lobar level were the dependent variables in a multilevel random regression analysis to investigate group differences. SMP was further examined in relation to symptomatology (i.e., psychotic/cognitive symptoms). RESULTS: At the whole brain and hemispheric level, patients had a significantly higher SMP compared to siblings and controls, with no difference between the latter. In the combined sibling and control group, individuals with high schizotypy had intermediate SMP values in the left hemisphere with respect to patients and individuals with low schizotypy. Exploratory analyses in patients revealed higher SMP in 12 out of 42 lobar divisions compared to controls, of which some were associated with worse PANSS symptomatology (i.e., positive symptoms, excitement and emotional distress) and worse cognitive performance on attention and emotion processing tasks. In the combined group of patients and controls, working memory, attention and social cognition were associated with higher SMP. DISCUSSION: The results are suggestive of more dispersed network communication in patients with psychotic disorder, with some evidence for trait-based network alterations in high-schizotypy individuals. Dispersed communication may contribute to the clinical phenotype in psychotic disorder. In addition, higher SMP may contribute to neuro- and social cognition, independent of psychosis risk. |
format | Online Article Text |
id | pubmed-4644247 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-46442472016-01-06 Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder Peeters, Sanne Simas, Tiago Suckling, John Gronenschild, Ed Patel, Ameera Habets, Petra van Os, Jim Marcelis, Machteld Neuroimage Clin Regular Article BACKGROUND: Dysconnectivity in schizophrenia can be understood in terms of dysfunctional integration of a distributed network of brain regions. Here we propose a new methodology to analyze complex networks based on semi-metric behavior, whereby higher levels of semi-metricity may represent a higher level of redundancy and dispersed communication. It was hypothesized that individuals with (increased risk for) psychotic disorder would have more semi-metric paths compared to controls and that this would be associated with symptoms. METHODS: Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 unaffected siblings and 72 controls. Semi-metric percentages (SMP) at the whole brain, hemispheric and lobar level were the dependent variables in a multilevel random regression analysis to investigate group differences. SMP was further examined in relation to symptomatology (i.e., psychotic/cognitive symptoms). RESULTS: At the whole brain and hemispheric level, patients had a significantly higher SMP compared to siblings and controls, with no difference between the latter. In the combined sibling and control group, individuals with high schizotypy had intermediate SMP values in the left hemisphere with respect to patients and individuals with low schizotypy. Exploratory analyses in patients revealed higher SMP in 12 out of 42 lobar divisions compared to controls, of which some were associated with worse PANSS symptomatology (i.e., positive symptoms, excitement and emotional distress) and worse cognitive performance on attention and emotion processing tasks. In the combined group of patients and controls, working memory, attention and social cognition were associated with higher SMP. DISCUSSION: The results are suggestive of more dispersed network communication in patients with psychotic disorder, with some evidence for trait-based network alterations in high-schizotypy individuals. Dispersed communication may contribute to the clinical phenotype in psychotic disorder. In addition, higher SMP may contribute to neuro- and social cognition, independent of psychosis risk. Elsevier 2015-10-09 /pmc/articles/PMC4644247/ /pubmed/26740914 http://dx.doi.org/10.1016/j.nicl.2015.10.003 Text en © 2015 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Regular Article Peeters, Sanne Simas, Tiago Suckling, John Gronenschild, Ed Patel, Ameera Habets, Petra van Os, Jim Marcelis, Machteld Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder |
title | Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder |
title_full | Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder |
title_fullStr | Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder |
title_full_unstemmed | Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder |
title_short | Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder |
title_sort | semi-metric analysis of the functional brain network: relationship with familial risk for psychotic disorder |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4644247/ https://www.ncbi.nlm.nih.gov/pubmed/26740914 http://dx.doi.org/10.1016/j.nicl.2015.10.003 |
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