Evidence map›Paper›PMID 35499628›Full record

ArticleBrain topography2022

A More Female-Characterized Resting-State Brain: Graph Similarity Analyses of Sex Influence on the Human Brain Intrinsic Functional Network.

Leinian Li, Zhijun Cui, Li Wang

Abstract read
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In one paragraph

Article in Brain topography, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 46% 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

3 citing papers in PubMed, 3 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

3 authors at 3 institutions in 1 country.

Leinian Li *School of Psychology, Shandong Normal University, 250013, Jinan, People's Republic of China.
Zhijun Cui *State Key Lab of Cognitive Neuroscience and Learning, Beijing Normal University, 100088, Beijing, People's Republic of China.
Li WangCurriculum and Teaching Materials Research Institution, People's Education Press, 100081, Beijing, People's Republic of China. Wli@pep.com.cn.ORCID 0000-0002-9437-8199
Beijing Normal University · CNPeking University · CNShandong Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It remains unclear whether human species exhibits sexual dimorphism in brain activities, and how the dimorphisms associated with sex-characterized behaviors. Here, in a large dataset from Human Connectome Project, we investigated sex differences of resting-state network structure by using local and global network graph similarity analysis. The "typical male" and "typical female" resting-state networks were highly similar. However, we found significant inter-sex difference in all local brain networks compared with sex-label permutations. The global and many local network topologies showed significant higher intra-female similarity, while males' network topologies were more dissimilar to each other. Additionally, by using global graph similarity analysis, we found that female individuals whose brain network were more similar to the average pattern present lower social-related anger, lower social distress and better companionships, while similar effects were not detected for males. Our study confirms the existence of sex-related resting-state network topology. Female's intrinsic brain is closer to a typical pattern than male's, and they may more fulfill the "similarity breeds connection" principle in building social ties.

Indexed as

ConnectomeMagnetic Resonance ImagingBrainFemaleHumansMaleNerve NetBrain networkGraph similarity analysisHuman Connectome ProjectSex influenceThe resting-state network

Identifiers

PMID35499628
OpenAlexW4225264696

What OpenQuestion holds

Textmetadata
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.