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Brain Anatomical Network and Intelligence
Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in i...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2683575/ https://www.ncbi.nlm.nih.gov/pubmed/19492086 http://dx.doi.org/10.1371/journal.pcbi.1000395 |
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author | Li, Yonghui Liu, Yong Li, Jun Qin, Wen Li, Kuncheng Yu, Chunshui Jiang, Tianzi |
author_facet | Li, Yonghui Liu, Yong Li, Jun Qin, Wen Li, Kuncheng Yu, Chunshui Jiang, Tianzi |
author_sort | Li, Yonghui |
collection | PubMed |
description | Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. |
format | Text |
id | pubmed-2683575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-26835752009-06-02 Brain Anatomical Network and Intelligence Li, Yonghui Liu, Yong Li, Jun Qin, Wen Li, Kuncheng Yu, Chunshui Jiang, Tianzi PLoS Comput Biol Research Article Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. Public Library of Science 2009-05-29 /pmc/articles/PMC2683575/ /pubmed/19492086 http://dx.doi.org/10.1371/journal.pcbi.1000395 Text en Li 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 Li, Yonghui Liu, Yong Li, Jun Qin, Wen Li, Kuncheng Yu, Chunshui Jiang, Tianzi Brain Anatomical Network and Intelligence |
title | Brain Anatomical Network and Intelligence |
title_full | Brain Anatomical Network and Intelligence |
title_fullStr | Brain Anatomical Network and Intelligence |
title_full_unstemmed | Brain Anatomical Network and Intelligence |
title_short | Brain Anatomical Network and Intelligence |
title_sort | brain anatomical network and intelligence |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2683575/ https://www.ncbi.nlm.nih.gov/pubmed/19492086 http://dx.doi.org/10.1371/journal.pcbi.1000395 |
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