Evidence map›Paper›PMID 32792927›Full record

ArticleFrontiers in human neuroscience2020

Gender Differences Are Encoded Differently in the Structure and Function of the Human Brain Revealed by Multimodal MRI.

Xi Zhang, Meng Liang, Wen Qin, Baikun Wan, Chunshui Yu, Dong Ming

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Article in Frontiers in human neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

33 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Sex-specific brain reserve and progression from mild cognitive impairment to Alzheimer's disease dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  13. Sex Differences in Human Brain Structure at Birth.Biology of sex differences · 2024
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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

6 authors.

Xi ZhangDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Meng LiangSchool of Medical Imaging, Tianjin Medical University, Tianjin, China.
Wen QinTianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.
Baikun WanDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
Chunshui YuSchool of Medical Imaging, Tianjin Medical University, Tianjin, China.
Dong MingDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite widely reported gender differences in both brain structure and brain function, very few studies have examined the relationship between the structural differences and the functional differences between genders. Here, different imaging measures including both structural [i.e., gray matter volume (GMV)] and functional [i.e., regional homogeneity (ReHo) and functional connectivity (FC)] measures were employed to detect the gender differences in the human brain based on univariate and multivariate approaches with a sample of 290 healthy adults (155 females). The univariate analyses revealed that gender differences were detected in both structural (i.e., GMV) and functional (ReHo or FC) imaging measures, mainly manifested as greater values in females than in males in regions of the frontal, parietal, occipital lobes and cerebellum. Importantly, there was little overlap between the differences detected in GMV and those detected in ReHo and FC, and their differences between genders were not correlated with each other. The multivariate pattern analyses revealed that each of these measures had discriminative power to successfully distinguish between genders (classification accuracy: 94.3%, 90.73%, and 83.89% for GMV, ReHo, and FC, respectively) and their combination further improved the classification performance (96.6%). Our results suggest that gender differences are encoded in both brain structure and brain function, but in different manners. The finding of different and complementary information contained in structural and functional differences between genders highlights the complex relationship between brain structure and function, which may underlie the complex nature of gender differences in behavior.

Indexed as

functional connectivitygender differencegray matter volumemultivariate pattern analysisregional homogeneitysupport vector machine

Identifiers

PMID32792927
PMCPMC7385398

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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.