Evidence map›Paper›PMID 36523439›Full record

ArticleFrontiers in neuroscience2022

Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders.

Lei Wei, Yao Zhang, Wensheng Zhai, Huaning Wang, Junchao Zhang, Haojie Jin, Jianfei Feng, Qin Qin, Hao Xu, Baojuan Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 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
2.5field-weighted citation impact, top 10% 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, 22 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 2 institutions in 1 country.

Lei WeiNetwork Center, Air Force Medical University, Xi'an, China.
Yao ZhangMilitary Medical Center, Xijing Hospital, Air Force Medical University, Xi'an, China.
Wensheng ZhaiSchool of Biomedical Engineering, Air Force Medical University, Xi'an, China.
Huaning WangDepartment of Psychiatry, Xijing Hospital, Air Force Medical University, Xi'an, China.
Junchao ZhangNetwork Center, Air Force Medical University, Xi'an, China.
Haojie JinNetwork Center, Air Force Medical University, Xi'an, China.
Jianfei FengNetwork Center, Air Force Medical University, Xi'an, China.
Qin QinNetwork Center, Air Force Medical University, Xi'an, China.
Hao XuNetwork Center, Air Force Medical University, Xi'an, China.
Baojuan LiSchool of Biomedical Engineering, Air Force Medical University, Xi'an, China.
Jian LiuNetwork Center, Air Force Medical University, Xi'an, China.
Air Force Medical University · CNAir Force Engineering University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Understanding the neurological basis of autism spectrum disorder (ASD) is important for the diagnosis and treatment of this mental disorder. Emerging evidence has suggested aberrant functional connectivity of large-scale brain networks in individuals with ASD. However, whether the effective connectivity which measures the causal interactions of these networks is also impaired in these patients remains unclear. Objects: The main purpose of this study was to investigate the effective connectivity of large-scale brain networks in patients with ASD during resting state. Materials and methods: The subjects were 42 autistic children and 127 age-matched normal children from the ABIDE II dataset. We investigated effective connectivity of 7 large-scale brain networks including visual network (VN), default mode network (DMN), cerebellum, sensorimotor network (SMN), auditory network (AN), salience network (SN), frontoparietal network (FPN), with spectral dynamic causality model (spDCM). Parametric empirical Bayesian (PEB) was used to perform second-level group analysis and furnished group commonalities and differences in effective connectivity. Furthermore, we analyzed the correlation between the strength of effective connectivity and patients' clinical characteristics. Results: For both groups, SMN acted like a hub network which demonstrated dense effective connectivity with other large-scale brain network. We also observed significant causal interactions within the "triple networks" system, including DMN, SN and FPN. Compared with healthy controls, children with ASD showed decreased effective connectivity among some large-scale brain networks. These brain networks included VN, DMN, cerebellum, SMN, and FPN. In addition, we also found significant negative correlation between the strength of the effective connectivity from right angular gyrus (ANG_R) of DMN to left precentral gyrus (PreCG_L) of SMN and ADOS-G or ADOS-2 module 4 stereotyped behaviors and restricted interest total (ADOS_G_STEREO_BEHAV) scores. Conclusion: Our research provides new evidence for the pathogenesis of children with ASD from the perspective of effective connections within and between large-scale brain networks. The attenuated effective connectivity of brain networks may be a clinical neurobiological feature of ASD. Changes in effective connectivity of brain network in children with ASD may provide useful information for the diagnosis and treatment of the disease.

Indexed as

autism spectrum disorderbrain networkdynamic causal modellingeffective connectivityparametric empirical bayesian

Identifiers

PMID36523439
PMCPMC9745118
OpenAlexW4310988455

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.