Evidence map›Paper›PMID 38168226›Full record

ArticlebioRxiv : the preprint server for biology2023

A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients.

William E Snyder, Petra E Vértes, Vanessa Kyriakopoulou, Konrad Wagstyl, Logan Z J Williams, Dustin Moraczewski, Adam G Thomas, Vyacheslav R Karolis, Jakob Seidlitz, Denis Rivière and 4 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 6 institutions in 3 countries.

William E SnyderDepartment of Psychiatry, University of Cambridge, Cambridge, UK.ORCID 0000-0001-8629-4633
Petra E VértesDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
Vanessa KyriakopoulouCentre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Konrad WagstylWellcome Centre for Human Neuroimaging, University College London, London, UK.
Logan Z J WilliamsCentre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Dustin MoraczewskiData Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA.
Adam G ThomasData Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA.
Vyacheslav R KarolisCentre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Jakob SeidlitzLifespan Brain Institute, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.
Denis RivièreUniversité Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, 91191, France.
Emma C RobinsonCentre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Jean-Francois ManginUniversité Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, 91191, France.
Armin RaznahanSection on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA.
Edward T BullmoreDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
King's College London · GBNational Institute of Mental Health · USUniversity of Cambridge · GBCentre National de la Recherche Scientifique · FRChildren's Hospital of Philadelphia · USWellcome Centre for Human Neuroimaging · GB

Funding

Section on Developmental NeurogenomicsZIAMH002949 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI RAZNAHAN, ARMIN · 2016 to 2025
$30.0M
Data Science and Sharing TeamZICMH002960 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI THOMAS, ADAM G · 2017 to 2025
$10.3M
Intramural NIH HHS ZIA MH002949Intramural NIH HHS ZIC MH002960Medical Research Council MR/V03832X/1
6 · The paper itself

Abstract

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

Identifiers

PMID38168226
PMCPMC10760196
OpenAlexW4389992972

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.