Evidence map›Paper›PMID 28235566›Full record

ArticleNeuroImage2018

Tests of cortical parcellation based on white matter connectivity using diffusion tensor imaging.

Yurui Gao, Kurt G Schilling, Iwona Stepniewska, Andrew J Plassard, Ann S Choe, Xia Li, Bennett A Landman, Adam W Anderson

Abstract read
In one paragraph

Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Imaging-based parcellations of the human brain.Nature reviews. Neuroscience · 2018
    Review
  10. Tests of clustering thalamic nuclei based on various dMRI models in the squirrel monkey brain.Proceedings of SPIE--the International Society for Optical Engineering · 2018
    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

8 authors at 1 institution in 1 country.

Yurui GaoInstitute of Imaging Science, Vanderbilt University, United States; Department of Biomedical Engineering, Vanderbilt University, United States.
Kurt G SchillingInstitute of Imaging Science, Vanderbilt University, United States; Department of Biomedical Engineering, Vanderbilt University, United States.
Iwona StepniewskaDepartment of Psychology, Vanderbilt University, United States.
Andrew J PlassardDepartment of Computer Science, Vanderbilt University, United States.
Ann S ChoeInstitute of Imaging Science, Vanderbilt University, United States; Department of Biomedical Engineering, Vanderbilt University, United States.
Xia LiInstitute of Imaging Science, Vanderbilt University, United States; Department of Radiology and Radiological Science, Vanderbilt University, United States.
Bennett A LandmanInstitute of Imaging Science, Vanderbilt University, United States; Department of Biomedical Engineering, Vanderbilt University, United States; Department of Computer Science, Vanderbilt University, United States; Department of Electrical Engineering, Vanderbilt University, United States.
Adam W AndersonInstitute of Imaging Science, Vanderbilt University, United States; Department of Biomedical Engineering, Vanderbilt University, United States; Department of Radiology and Radiological Science, Vanderbilt University, United States.
Vanderbilt University · US

Funding

Research Project: Sensory and Multisensory Contributions to AutismU54HD083211 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI DYKENS, ELISABETH MAY · 2015 to 2019
$7.1M
The Biological Basis of Diffusion MRI of the BrainR01NS058639 · NINDS · VANDERBILT UNIVERSITY · PI ANDERSON, ADAM W · 2008 to 2016
$3.7M
BIDS: Vanderbilt Training Program in BIg Biomedical Data ScienceT32LM012412 · NLM · VANDERBILT UNIVERSITY · PI BLUME, JEFFREY D., GADD, CYNTHIA S · 2016 to 2020
$1.5M
NICHD NIH HHS U54 HD083211NINDS NIH HHS R01 NS058639NLM NIH HHS T32 LM012412
6 · The paper itself

Abstract

The cerebral cortex is conventionally divided into a number of domains based on cytoarchitectural features. Diffusion tensor imaging (DTI) enables noninvasive parcellation of the cortex based on white matter connectivity patterns. However, the correspondence between DTI-connectivity-based and cytoarchitectural parcellation has not been systematically established. In this study, we compared histological parcellation of New World monkey neocortex to DTI- connectivity-based classification and clustering in the same brains. First, we used supervised classification to parcellate parieto-frontal cortex based on DTI tractograms and the cytoarchitectural prior (obtained using Nissl staining). We performed both within and across sample classification, showing reasonable classification performance in both conditions. Second, we used unsupervised clustering to parcellate the cortex and compared the clusters to the cytoarchitectonic standard. We then explored the similarities and differences with several post-hoc analyses, highlighting underlying principles that drive the DTI-connectivity-based parcellation. The differences in parcellation between DTI-connectivity and Nissl histology probably represent both DTI's bias toward easily-tracked bundles and true differences between cytoarchitectural and connectivity defined domains. DTI tractograms appear to cluster more according to functional networks, rather than mapping directly onto cytoarchitectonic domains. Our results show that caution should be used when DTI-tractography classification, based on data from another brain, is used as a surrogate for cytoarchitectural parcellation.

Indexed as

AnimalsCerebral CortexDiffusion Tensor ImagingNeuroimagingSaimiriWhite MatterClassificationCortical parcellationCross-validationDTI tractographyWhite matter connectivity

Identifiers

PMID28235566
PMCPMC5568504
OpenAlexW2590688054

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.