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Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations
Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophren...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3549920/ https://www.ncbi.nlm.nih.gov/pubmed/23349665 http://dx.doi.org/10.1371/journal.pone.0050625 |
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author | Rish, Irina Cecchi, Guillermo Thyreau, Benjamin Thirion, Bertrand Plaze, Marion Paillere-Martinot, Marie Laure Martelli, Catherine Martinot, Jean-Luc Poline, Jean-Baptiste |
author_facet | Rish, Irina Cecchi, Guillermo Thyreau, Benjamin Thirion, Bertrand Plaze, Marion Paillere-Martinot, Marie Laure Martelli, Catherine Martinot, Jean-Luc Poline, Jean-Baptiste |
author_sort | Rish, Irina |
collection | PubMed |
description | Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests. |
format | Online Article Text |
id | pubmed-3549920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35499202013-01-24 Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations Rish, Irina Cecchi, Guillermo Thyreau, Benjamin Thirion, Bertrand Plaze, Marion Paillere-Martinot, Marie Laure Martelli, Catherine Martinot, Jean-Luc Poline, Jean-Baptiste PLoS One Research Article Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests. Public Library of Science 2013-01-21 /pmc/articles/PMC3549920/ /pubmed/23349665 http://dx.doi.org/10.1371/journal.pone.0050625 Text en © 2013 Rish 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 Rish, Irina Cecchi, Guillermo Thyreau, Benjamin Thirion, Bertrand Plaze, Marion Paillere-Martinot, Marie Laure Martelli, Catherine Martinot, Jean-Luc Poline, Jean-Baptiste Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations |
title | Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations |
title_full | Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations |
title_fullStr | Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations |
title_full_unstemmed | Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations |
title_short | Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations |
title_sort | schizophrenia as a network disease: disruption of emergent brain function in patients with auditory hallucinations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3549920/ https://www.ncbi.nlm.nih.gov/pubmed/23349665 http://dx.doi.org/10.1371/journal.pone.0050625 |
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