Evidence map›Paper›PMID 30405187›Full record

ArticleScientific reports2018

Brain structural connectivity and neuroticism in healthy adults.

Issei Ueda, Shingo Kakeda, Keita Watanabe, Koichiro Sugimoto, Natsuki Igata, Junji Moriya, Kazuhiro Takemoto, Asuka Katsuki, Reiji Yoshimura, Osamu Abe and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

13 citing papers in PubMed, 30 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

11 authors at 3 institutions in 1 country.

Issei UedaDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan.
Shingo KakedaDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan. kakeda@med.uoeh-u.ac.jp.ORCID http://orcid.org/0000-0002-0521-9728
Keita WatanabeDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan.
Koichiro SugimotoDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan.
Natsuki IgataDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan.
Junji MoriyaDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan.
Kazuhiro TakemotoDepartment of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka, Japan.ORCID http://orcid.org/0000-0002-6355-1366
Asuka KatsukiDepartment of Psychiatry, University of Occupational and Environmental Health, Fukuoka, Japan.
Reiji YoshimuraDepartment of Psychiatry, University of Occupational and Environmental Health, Fukuoka, Japan.
Osamu AbeDepartment of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
Yukunori KorogiDepartment of Radiology, University of Occupational and Environmental Health, Fukuoka, Japan.
University of Occupational and Environmental Health Japan · JPKyushu Institute of Technology · JPThe University of Tokyo · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the neural correlates of the neurotic brain is important because neuroticism is a risk factor for the development of psychopathology. We examined the correlation between brain structural networks and neuroticism based on NEO Five-Factor Inventory (NEO-FFI) scores. Fifty-one healthy participants (female, n = 18; male, n = 33; mean age, 38.5 ± 11.7 years) underwent the NEO-FFI test and magnetic resonance imaging (MRI), including diffusion tensor imaging and 3D T1WI. Using MRI data, for each participant, we constructed whole-brain interregional connectivity matrices by deterministic tractography and calculated the graph theoretical network measures, including the characteristic path length, global clustering coefficient, small-worldness, and betweenness centrality (BET) in 83 brain regions from the Desikan-Killiany atlas with subcortical segmentation using FreeSurfer. In relation to the BET, neuroticism score had a negative correlation in the left isthmus cingulate cortex, left superior parietal, left superior temporal, right caudal middle frontal, and right entorhinal cortices, and a positive correlation in the bilateral frontal pole, left caudal anterior cingulate cortex, and left fusiform gyrus. No other measurements showed significant correlations. Our results imply that the brain regions related to neuroticism exist in various regions, and that the neuroticism trait is likely formed as a result of interactions among these regions. This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (Comprehensive Brain Science Network) from the Ministry of Education, Science, Sports and Culture of Japan.

Indexed as

ConnectomeNeuroticismAdultAgedAlgorithmsBrainBrain MappingData Interpretation, StatisticalDiffusion Tensor ImagingFemaleHealthy VolunteersHumansImage Processing, Computer-AssistedMaleMiddle AgedYoung Adult

Identifiers

PMID30405187
PMCPMC6220248
OpenAlexW2898699296

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.