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Identifying endophenotypes of autism: a multivariate approach
The existence of an endophenotype of autism spectrum condition (ASC) has been recently suggested by several commentators. It can be estimated by finding differences between controls and people with ASC that are also present when comparing controls and the unaffected siblings of ASC individuals. In t...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4047979/ https://www.ncbi.nlm.nih.gov/pubmed/24936183 http://dx.doi.org/10.3389/fncom.2014.00060 |
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author | Segovia, Fermín Holt, Rosemary Spencer, Michael Górriz, Juan M. Ramírez, Javier Puntonet, Carlos G. Phillips, Christophe Chura, Lindsay Baron-Cohen, Simon Suckling, John |
author_facet | Segovia, Fermín Holt, Rosemary Spencer, Michael Górriz, Juan M. Ramírez, Javier Puntonet, Carlos G. Phillips, Christophe Chura, Lindsay Baron-Cohen, Simon Suckling, John |
author_sort | Segovia, Fermín |
collection | PubMed |
description | The existence of an endophenotype of autism spectrum condition (ASC) has been recently suggested by several commentators. It can be estimated by finding differences between controls and people with ASC that are also present when comparing controls and the unaffected siblings of ASC individuals. In this work, we used a multivariate methodology applied on magnetic resonance images to look for such differences. The proposed procedure consists of combining a searchlight approach and a support vector machine classifier to identify the differences between three groups of participants in pairwise comparisons: controls, people with ASC and their unaffected siblings. Then we compared those differences selecting spatially collocated as candidate endophenotypes of ASC. |
format | Online Article Text |
id | pubmed-4047979 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40479792014-06-16 Identifying endophenotypes of autism: a multivariate approach Segovia, Fermín Holt, Rosemary Spencer, Michael Górriz, Juan M. Ramírez, Javier Puntonet, Carlos G. Phillips, Christophe Chura, Lindsay Baron-Cohen, Simon Suckling, John Front Comput Neurosci Neuroscience The existence of an endophenotype of autism spectrum condition (ASC) has been recently suggested by several commentators. It can be estimated by finding differences between controls and people with ASC that are also present when comparing controls and the unaffected siblings of ASC individuals. In this work, we used a multivariate methodology applied on magnetic resonance images to look for such differences. The proposed procedure consists of combining a searchlight approach and a support vector machine classifier to identify the differences between three groups of participants in pairwise comparisons: controls, people with ASC and their unaffected siblings. Then we compared those differences selecting spatially collocated as candidate endophenotypes of ASC. Frontiers Media S.A. 2014-06-06 /pmc/articles/PMC4047979/ /pubmed/24936183 http://dx.doi.org/10.3389/fncom.2014.00060 Text en Copyright © 2014 Segovia, Holt, Spencer, Górriz, Ramírez, Puntonet, Phillips, Chura, Baron-Cohen and Suckling. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Segovia, Fermín Holt, Rosemary Spencer, Michael Górriz, Juan M. Ramírez, Javier Puntonet, Carlos G. Phillips, Christophe Chura, Lindsay Baron-Cohen, Simon Suckling, John Identifying endophenotypes of autism: a multivariate approach |
title | Identifying endophenotypes of autism: a multivariate approach |
title_full | Identifying endophenotypes of autism: a multivariate approach |
title_fullStr | Identifying endophenotypes of autism: a multivariate approach |
title_full_unstemmed | Identifying endophenotypes of autism: a multivariate approach |
title_short | Identifying endophenotypes of autism: a multivariate approach |
title_sort | identifying endophenotypes of autism: a multivariate approach |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4047979/ https://www.ncbi.nlm.nih.gov/pubmed/24936183 http://dx.doi.org/10.3389/fncom.2014.00060 |
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