Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Youngwoo Bryan Yoon,William Seunghyun Sohn,Ji-Won Hur,Kwang-Hyuk Lee,Won-Gyo Shin,Seung-Goo Kim,Jun Soo Kwon,Tae Young Lee,Kang Ik K Cho

doi:10.1038/s41598-017-02304-z

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.

Highlights

There is firm evidence that grey matter (GM) is associated with intelligence[6, 16, 17]
Our study examined GM structural networks by applying a multivariate morphometric procedure and further revealed the networks’ relationships with intelligence and visuomotor ability (TMT-A)
Our results showed that the cerebello-parietal component and the frontal component were associated with intelligence

Summary

Introduction

There is firm evidence that grey matter (GM) is associated with intelligence[6, 16, 17]. We expect that SBM will enable us to uncover submerged regional networks within the brain and further provide us with a more comprehensive picture of GM structural networks. Verbal fluency, processing speed, and executive functioning have been reported to be relevant to brain structural networks[25,26,27,28,29,30] This relevance has not been shown at GM structural network level. We hypothesized that intelligence is associated with parietal and frontal GM structural network and that different structural networks interact with different domains of cognitive functions. To test this hypothesis, we first acquired GM structural networks using SBM. We explored how cognitive functions, assessed with the TMT and COWAT, are associated with the GM structural network

Methods

Results

Conclusion