Evidence map›Paper›PMID 29947164›Full record

ArticleHuman brain mapping2018

Exploring 3-hinge gyral folding patterns among HCP Q3 868 human subjects.

Tuo Zhang, Hanbo Chen, Mir Jalil Razavi, Yujie Li, Fangfei Ge, Lei Guo, Xianqiao Wang, Tianming Liu

Open access · greenAbstract read
In one paragraph

Article in Human brain mapping, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

16 citing papers in PubMed, 29 citations in OpenAlex.

  1. DEEP-GYRALNET: ENABLING MACHINE LEARNING IN GYRAL FOLDING PATTERN EXTRACTION ON CORTICAL SURFACE.Proceedings. IEEE International Symposium on Biomedical Imaging · 2026
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  4. UNSUPERVISED CORTICAL SURFACE REGISTRATION NETWORK FOR ALIGNING GYRALNET.Proceedings. IEEE International Symposium on Biomedical Imaging · 2025
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  6. MILD COGNITIVE IMPAIRMENT CLASSIFICATION USING A NOVEL FINER-SCALE BRAIN CONNECTOME.Proceedings. IEEE International Symposium on Biomedical Imaging · 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

8 authors at 2 institutions in 2 countries.

Tuo ZhangBrain Decoding Research Center and School of Automation, Northwestern Polytechnical University Xi'an, Shaanxi, China.
Hanbo ChenCortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, Georgia.
Mir Jalil RazaviCollege of Engineering, The University of Georgia, Athens, Georgia.
Yujie LiCortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, Georgia.
Fangfei GeCortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, Georgia.
Lei GuoBrain Decoding Research Center and School of Automation, Northwestern Polytechnical University Xi'an, Shaanxi, China.
Xianqiao WangCollege of Engineering, The University of Georgia, Athens, Georgia.
Tianming LiuCortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, Georgia.
University of Georgia · USNorthwestern Polytechnical University · CN

Funding

Assessing Large-scale Connectivities in Prenatal Cocaine Exposure Affected BrainsR01DA033393 · NIDA · UNIVERSITY OF GEORGIA · PI HU, XIAOPING P, LIU, TIANMING · 2012 to 2016
$1.6M
Assessing Large-scale Brain Connectivities in Mild Cognitive ImpairmentR01AG042599 · NIA · UNIVERSITY OF GEORGIA · PI LIU, TIANMING · 2013 to 2017
$1.4M
NIA NIH HHS R01 AG042599NIDA NIH HHS R01 DA033393
6 · The paper itself

Abstract

Comparison and integration of neuroimaging data from different brains and populations are fundamental in neuroscience. Over the past decades, the neuroimaging field has largely depended on image registration to compare and integrate neuroimaging data from individuals in a common reference space, with a basic assumption that the brains are similar. However, the intrinsic neuroanatomical complexity and huge interindividual cortical folding variation remain underexplored. Here we focus on a specific cortical convolution pattern, termed 3-hinge gyral folding, which is the conjunction of gyri from multiple orientations and has unique and consistent anatomically, structurally, and functionally connective patterns across subjects. By developing a novel shape descriptor and a two-stage clustering pipeline, we devise an automatic method to identify 3-hinges in the Human Connectome Project Q3 868 human brains, and further parameterize the complexity of such a pattern and quantify its regularity and variation in terms of 3-hinge number, position, and morphology. Our results not only exhibit the huge interindividual variations, but also reveal regular relationship between gyral hinges and other factors, such as their locations and cortical morphologies. It is found that "line-shape" cortices have relatively more consistent 3-hinge shape pattern distributions, and certain types of 3-hinge patterns favor particular cortical morphologies. In addition, more 3-hinges are found on "line-shape" cortices while their numbers vary more across subjects than those on "non-line-shape" cortices. This study adds new insights into a better understanding of the regularity and variability of human brain anatomy, and their functional aspects.

Indexed as

ConnectomeData Interpretation, StatisticalAdultCerebral CortexHumansImage Processing, Computer-AssistedMagnetic Resonance Imaging3-hinge gyrusanatomical morphologycortical architecturecortical folding

Identifiers

PMID29947164
PMCPMC6160316
OpenAlexW2810912854

What OpenQuestion holds

Textmetadata
LicenceTDM
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.