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  Brain structural networks associated with intelligence and visuomotor ability

Yoon, Y. B., Shin, W.-G., Lee, T. Y., Hur, J.-W., Cho, K. I. K., Sohn, W. S., et al. (2017). Brain structural networks associated with intelligence and visuomotor ability. Scientific Reports, 7: 2177. doi:10.1038/s41598-017-02304-z.

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 Creators:
Yoon, Youngwoo Bryan 1, Author
Shin, Won-Gyo 1, Author
Lee, Tae Young 2, Author
Hur, Ji-Won 3, Author
Cho, Kang Ik K. 2, Author
Sohn, William Seunghyun2, Author
Kim, Seung-Goo4, Author              
Lee, Kwang-Hyuk1, 2, Author
Kwon, Jun Soo 1, 2, 5, Author
Affiliations:
1Department of Brain and Cognitive Sciences, Korea University, Seoul, Republic of Korea, ou_persistent22              
2Seoul National University Hospital, Republic of Korea, ou_persistent22              
3Department of Psychology, Chung-Ang University, Seoul, Republic of Korea, ou_persistent22              
4Methods and Development Group MEG and EEG - Cortical Networks and Cognitive Functions, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_persistent22              
5Department of Psychiatry, Seoul National University Hospital, Republic of Korea, ou_persistent22              

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Free keywords: Intelligence; Magnetic resonance imaging
 Abstract: Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions.

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Language(s): eng - English
 Dates: 2016-12-302017-04-072017-05-19
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41598-017-02304-z
PMC: PMC5438383
PMID: 28526888
 Degree: -

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Project name : -
Grant ID : 2016R1E1A1A02921618
Funding program : Basic Science Research Program
Funding organization : National Research Foundation of Korea (NRF)

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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 7 Sequence Number: 2177 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322