Evidence map›Paper›PMID 36588440›Full record

ArticlePsychiatry investigation2022

Alterations in Social Brain Network Topology at Rest in Children With Autism Spectrum Disorder.

Narae Yoon, Youngmin Huh, Hyekyoung Lee, Johanna Inhyang Kim, Jung Lee, Chan-Mo Yang, Soomin Jang, Yebin D Ahn, Mee Rim Oh, Dong Soo Lee and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Psychiatry investigation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed, 15 citations in OpenAlex.

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  7. Unsupervised Dimensionality Reduction Techniques for the Assessment of ASD Biomarkers.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2025
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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

12 authors at 3 institutions in 1 country.

Narae YoonDivision of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Youngmin HuhMedical Research Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
Hyekyoung LeeDepartment of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Johanna Inhyang KimDepartment of Psychiatry, Hanyang University Medical Center, Seoul, Republic of Korea.
Jung LeeDivision of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Chan-Mo YangDivision of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Soomin JangDivision of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Yebin D AhnDivision of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Mee Rim OhBiomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.
Dong Soo LeeDepartment of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Hyejin KangDepartment of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Bung-Nyun KimDivision of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Seoul National University · KRHanyang University Medical Center · KRSeoul National University Hospital · KR

Funding

Bio & Medical Technology Development ProgramInstitute of Information & communications Technology Planning & Evaluation 2022-0-00375-001Ministry of Trade, Industry, and EnergyNational Research Foundation of Korea 2020M3E5D9080787 to B.-N.KNational Research Foundation of Korea 2020R1A2C2011532 to H.K.Technology Innovation Program 20002769
6 · The paper itself

Abstract

objectiveUnderconnectivity in the resting brain is not consistent in autism spectrum disorder (ASD). However, it is known that the functional connectivity of the default mode network is mainly decreased in childhood ASD. This study investigated the brain network topology as the changes in the connection strength and network efficiency in childhood ASD, including the early developmental stages.

methodsIn this study, 31 ASD children aged 2-11 years were compared with 31 age and sex-matched children showing typical development. We explored the functional connectivity based on graph filtration by assessing the single linkage distance and global and nodal efficiencies using resting-state functional magnetic resonance imaging. The relationship between functional connectivity and clinical scores was also analyzed.

resultsUnderconnectivities within the posterior default mode network subregions and between the inferior parietal lobule and inferior frontal/superior temporal regions were observed in the ASD group. These areas significantly correlated with the clinical phenotypes. The global, local, and nodal network efficiencies were lower in children with ASD than in those with typical development. In the preschool-age children (2-6 years) with ASD, the anterior-posterior connectivity of the default mode network and cerebellar connectivity were reduced.

conclusionThe observed topological reorganization, underconnectivity, and disrupted efficiency in the default mode network subregions and social function-related regions could be significant biomarkers of childhood ASD.

Indexed as

Autism spectrum disorderChildrenDefault mode networkFunctional MRIFunctional neuroimaging

Identifiers

PMID36588440
PMCPMC9806512
OpenAlexW4313262731

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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.