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The Statistical Neuroanatomy of Frontal Networks in the Macaque

We were interested in gaining insight into the functional properties of frontal networks based upon their anatomical inputs. We took a neuroinformatics approach, carrying out maximum likelihood hierarchical cluster analysis on 25 frontal cortical areas based upon their anatomical connections, with 6...

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Detalles Bibliográficos
Autores principales: Averbeck, Bruno B., Seo, Moonsang
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2268011/
https://www.ncbi.nlm.nih.gov/pubmed/18389057
http://dx.doi.org/10.1371/journal.pcbi.1000050
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author Averbeck, Bruno B.
Seo, Moonsang
author_facet Averbeck, Bruno B.
Seo, Moonsang
author_sort Averbeck, Bruno B.
collection PubMed
description We were interested in gaining insight into the functional properties of frontal networks based upon their anatomical inputs. We took a neuroinformatics approach, carrying out maximum likelihood hierarchical cluster analysis on 25 frontal cortical areas based upon their anatomical connections, with 68 input areas representing exterosensory, chemosensory, motor, limbic, and other frontal inputs. The analysis revealed a set of statistically robust clusters. We used these clusters to divide the frontal areas into 5 groups, including ventral-lateral, ventral-medial, dorsal-medial, dorsal-lateral, and caudal-orbital groups. Each of these groups was defined by a unique set of inputs. This organization provides insight into the differential roles of each group of areas and suggests a gradient by which orbital and ventral-medial areas may be responsible for decision-making processes based on emotion and primary reinforcers, and lateral frontal areas are more involved in integrating affective and rational information into a common framework.
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spelling pubmed-22680112008-04-04 The Statistical Neuroanatomy of Frontal Networks in the Macaque Averbeck, Bruno B. Seo, Moonsang PLoS Comput Biol Research Article We were interested in gaining insight into the functional properties of frontal networks based upon their anatomical inputs. We took a neuroinformatics approach, carrying out maximum likelihood hierarchical cluster analysis on 25 frontal cortical areas based upon their anatomical connections, with 68 input areas representing exterosensory, chemosensory, motor, limbic, and other frontal inputs. The analysis revealed a set of statistically robust clusters. We used these clusters to divide the frontal areas into 5 groups, including ventral-lateral, ventral-medial, dorsal-medial, dorsal-lateral, and caudal-orbital groups. Each of these groups was defined by a unique set of inputs. This organization provides insight into the differential roles of each group of areas and suggests a gradient by which orbital and ventral-medial areas may be responsible for decision-making processes based on emotion and primary reinforcers, and lateral frontal areas are more involved in integrating affective and rational information into a common framework. Public Library of Science 2008-04-04 /pmc/articles/PMC2268011/ /pubmed/18389057 http://dx.doi.org/10.1371/journal.pcbi.1000050 Text en Averbeck, Seo. 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
Averbeck, Bruno B.
Seo, Moonsang
The Statistical Neuroanatomy of Frontal Networks in the Macaque
title The Statistical Neuroanatomy of Frontal Networks in the Macaque
title_full The Statistical Neuroanatomy of Frontal Networks in the Macaque
title_fullStr The Statistical Neuroanatomy of Frontal Networks in the Macaque
title_full_unstemmed The Statistical Neuroanatomy of Frontal Networks in the Macaque
title_short The Statistical Neuroanatomy of Frontal Networks in the Macaque
title_sort statistical neuroanatomy of frontal networks in the macaque
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2268011/
https://www.ncbi.nlm.nih.gov/pubmed/18389057
http://dx.doi.org/10.1371/journal.pcbi.1000050
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