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Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder
INTRODUCTION: The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-met...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4550361/ https://www.ncbi.nlm.nih.gov/pubmed/26308854 http://dx.doi.org/10.1371/journal.pone.0136388 |
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author | Simas, Tiago Chattopadhyay, Shayanti Hagan, Cindy Kundu, Prantik Patel, Ameera Holt, Rosemary Floris, Dorothea Graham, Julia Ooi, Cinly Tait, Roger Spencer, Michael Baron-Cohen, Simon Sahakian, Barbara Bullmore, Ed Goodyer, Ian Suckling, John |
author_facet | Simas, Tiago Chattopadhyay, Shayanti Hagan, Cindy Kundu, Prantik Patel, Ameera Holt, Rosemary Floris, Dorothea Graham, Julia Ooi, Cinly Tait, Roger Spencer, Michael Baron-Cohen, Simon Sahakian, Barbara Bullmore, Ed Goodyer, Ian Suckling, John |
author_sort | Simas, Tiago |
collection | PubMed |
description | INTRODUCTION: The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric), such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric), where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC) and major depressive disorder (MDD). RESULTS: Significance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome. CONCLUSION: These encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders. |
format | Online Article Text |
id | pubmed-4550361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45503612015-09-01 Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder Simas, Tiago Chattopadhyay, Shayanti Hagan, Cindy Kundu, Prantik Patel, Ameera Holt, Rosemary Floris, Dorothea Graham, Julia Ooi, Cinly Tait, Roger Spencer, Michael Baron-Cohen, Simon Sahakian, Barbara Bullmore, Ed Goodyer, Ian Suckling, John PLoS One Research Article INTRODUCTION: The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric), such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric), where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC) and major depressive disorder (MDD). RESULTS: Significance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome. CONCLUSION: These encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders. Public Library of Science 2015-08-26 /pmc/articles/PMC4550361/ /pubmed/26308854 http://dx.doi.org/10.1371/journal.pone.0136388 Text en © 2015 Simas 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 Simas, Tiago Chattopadhyay, Shayanti Hagan, Cindy Kundu, Prantik Patel, Ameera Holt, Rosemary Floris, Dorothea Graham, Julia Ooi, Cinly Tait, Roger Spencer, Michael Baron-Cohen, Simon Sahakian, Barbara Bullmore, Ed Goodyer, Ian Suckling, John Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder |
title | Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder |
title_full | Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder |
title_fullStr | Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder |
title_full_unstemmed | Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder |
title_short | Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder |
title_sort | semi-metric topology of the human connectome: sensitivity and specificity to autism and major depressive disorder |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4550361/ https://www.ncbi.nlm.nih.gov/pubmed/26308854 http://dx.doi.org/10.1371/journal.pone.0136388 |
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