Evidence map›Paper›PMID 23268782›Full record

ArticleNeuroImage2013

The structural connectome of the human brain in agenesis of the corpus callosum.

Julia P Owen, Yi-Ou Li, Etay Ziv, Zoe Strominger, Jacquelyn Gold, Polina Bukhpun, Mari Wakahiro, Eric J Friedman, Elliott H Sherr, Pratik Mukherjee

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in NeuroImage, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00305305 (Disorders of Cerebral Development), which is not on this map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
5.2field-weighted citation impact, top 4% 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.

NCT00305305 recruitingnot on this map

Disorders of Cerebral Development: A Phenotypic and Genetic Analysis

TypeobservationalSponsorUniversity of California, San FranciscoRan2003 to 2027Enrolled2,000ConditionsBrain Disorders, Aicardi Syndrome
3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 84 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. mTOR-Dependent Spine Dynamics in Autism.Frontiers in molecular neuroscience · 2022
    Review
  19. Article
  20. Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
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

10 authors at 2 institutions in 1 country.

Julia P OwenDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, CA 94107, USA.
Yi-Ou Li
Etay Ziv
Zoe Strominger
Jacquelyn Gold
Polina Bukhpun
Mari Wakahiro
Eric J Friedman
Elliott H Sherr
Pratik Mukherjee
University of California, San Francisco · USInternational Computer Science Institute · US

Funding

Neural mechanisms of auditory feedback during speechR01DC006435 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NAGARAJAN, SRIKANTAN S. · 2004 to 2008
$2.3M
Macrostructural and Microstructural Imaging Biomarkers of Traumatic Brain InjuryR01NS060776 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MUKHERJEE, PRATIK · 2009 to 2012
$1.8M
Robust Localized Measures for Brain NetworksK25NS073689 · NINDS · INTERNATIONAL COMPUTER SCIENCE INSTITUTE · PI FRIEDMAN, ERIC J. · 2011 to 2015
$876k
Fusion of Electromagnetic Brain Imaging and fMRIR21NS076171 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NAGARAJAN, SRIKANTAN S. · 2011 to 2012
$425k
NIDCD NIH HHS R01 DC006435NINDS NIH HHS K25 NS073689NINDS NIH HHS R01 NS060776NINDS NIH HHS R21 NS076171
6 · The paper itself

Abstract

Adopting a network perspective, the structural connectome reveals the large-scale white matter connectivity of the human brain, yielding insights into cerebral organization otherwise inaccessible to researchers and clinicians. Connectomics has great potential for elucidating abnormal connectivity in congenital brain malformations, especially axonal pathfinding disorders. Agenesis of the corpus callosum (AgCC) is one of the most common brain malformations and can also be considered a prototypical genetic disorder of axonal guidance in humans. In this exploratory study, the structural connectome of AgCC is mapped and compared to that of the normal human brain. Multiple levels of granularity of the AgCC connectome are investigated, including summary network metrics, modularity analysis, and network consistency measures, with comparison to the normal structural connectome after simulated removal of all callosal connections ("virtual callostomy"). These investigations reveal four major findings. First, global connectivity is abnormally reduced in AgCC, but local connectivity is increased. Second, the network topology of AgCC is more variable than that of the normal human connectome, contradicting the predictions of the virtual callostomy model. Third, modularity analysis reveals that many of the tracts that comprise the structural core of the cerebral cortex have relatively weak connectivity in AgCC, especially the cingulate bundles bilaterally. Finally, virtual lesions of the Probst bundles in the AgCC connectome demonstrate that there is consistency across subjects in many of the connections generated by these ectopic white matter tracts, and that they are a mixture of cortical and subcortical fibers. These results go beyond prior diffusion tractography studies to provide a systems-level perspective on anomalous connectivity in AgCC. Furthermore, this work offers a proof of principle for the utility of the connectome framework in neurodevelopmental disorders.

Indexed as

ConnectomeAgenesis of Corpus CallosumBrainFemaleHumansMaleYoung Adult

Identifiers

PMID23268782
PMCPMC4127170
OpenAlexW2085438263

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

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.