Evidence map›Paper›PMID 28526888›Full record

ArticleScientific reports2017

Brain Structural Networks Associated with Intelligence and Visuomotor Ability.

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

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
2.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 57 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 3 countries.

Youngwoo Bryan YoonDepartment of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
Won-Gyo ShinDepartment of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
Tae Young LeeMedical Research Center, Seoul National University Hospital, Seoul, 03080, Republic of Korea.ORCID 0000-0002-0238-8147
Ji-Won HurDepartment of Psychology, Chung-Ang University, Seoul, 06974, Republic of Korea.
Kang Ik K ChoDepartment of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
William Seunghyun SohnMedical Research Center, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
Seung-Goo KimMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany.
Kwang-Hyuk LeeDepartment of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea.
Jun Soo KwonDepartment of Brain and Cognitive Sciences, Seoul National University, Seoul, 08826, Republic of Korea. kwonjs@snu.ac.kr.
Seoul National University · KRSeoul National University Hospital · KRChung-Ang University · KRMax Planck Institute for Human Cognitive and Brain Sciences · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

IntelligenceNeural PathwaysPsychomotor PerformanceAdolescentAdultBrainCerebellumFemaleGray MatterHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological TestsYoung Adult

Identifiers

PMID28526888
PMCPMC5438383
OpenAlexW2614954696

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.