Evidence map›Paper›PMID 30858600›Full record

ArticleNature methods2019

An active texture-based digital atlas enables automated mapping of structures and markers across brains.

Yuncong Chen, Lauren E McElvain, Alexander S Tolpygo, Daniel Ferrante, Beth Friedman, Partha P Mitra, Harvey J Karten, Yoav Freund, David Kleinfeld

Abstract read
In one paragraph

Article in Nature methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
5.0field-weighted citation impact, top 5% 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

24 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Review
  3. Chemoarchitectural studies of the rat hypothalamus and zona incerta.bioRxiv : the preprint server for biology · 2025
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  10. Developmental Mouse Brain Common Coordinate Framework.bioRxiv : the preprint server for biology · 2023
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  15. Review
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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

9 authors at 2 institutions in 1 country.

Yuncong ChenDepartment of Computer Science and Engineering, University of California, San Diego, CA, USA.
Lauren E McElvainDepartment of Physics, University of California, San Diego, CA, USA.
Alexander S TolpygoCold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Daniel FerranteCold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Beth FriedmanDepartment of Computer Science and Engineering, University of California, San Diego, CA, USA.
Partha P MitraCold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Harvey J KartenDepartment of Neurosciences, University of California School of Medicine, San Diego, CA, USA.
Yoav FreundDepartment of Computer Science and Engineering, University of California, San Diego, CA, USA. yfreund@eng.ucsd.edu.ORCID http://orcid.org/0000-0002-3850-6184
David KleinfeldDepartment of Physics, University of California, San Diego, CA, USA. dk@physics.ucsd.edu.ORCID http://orcid.org/0000-0001-9797-4722
University of California San Diego · USCold Spring Harbor Laboratory · US

Funding

Tool and Technology Development CoreU19MH114821 · NIMH · COLD SPRING HARBOR LABORATORY · PI HUANG, Z JOSH · 2017 to 2021
$64.5M
Theory and Modeling of the Orofacial Active SensationU19NS107466 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MITRA, PARTHA PRATIM · 2018 to 2022
$14.9M
ResourceP40OD010996 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI STRICK, PETER · 2012 to 2024
$11.0M
Towards quantitative cell type-based mapping of the whole mouse brainU01MH105971 · NIMH · COLD SPRING HARBOR LABORATORY · PI OSTEN, PAVEL · 2014 to 2016
$3.9M
Supplement request to: Revealing the connectivity and functionality of brain stem circuitsU01NS090595 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DESCHENES, MARTIN, FREUND, YOAV SHAI · 2014 to 2016
$2.6M
NIH HHS MH105971NIH HHS MH114821NIH HHS NS0905905NIH HHS NS107466NIH HHS P40 OD010996NIMH NIH HHS U01 MH105971NIMH NIH HHS U19 MH114821NINDS NIH HHS U01 NS090595NINDS NIH HHS U19 NS107466
6 · The paper itself

Abstract

Brain atlases enable the mapping of labeled cells and projections from different brains onto a standard coordinate system. We address two issues in the construction and use of atlases. First, expert neuroanatomists ascertain the fine-scale pattern of brain tissue, the 'texture' formed by cellular organization, to define cytoarchitectural borders. We automate the processes of localizing landmark structures and alignment of brains to a reference atlas using machine learning and training data derived from expert annotations. Second, we construct an atlas that is active; that is, augmented with each use. We show that the alignment of new brains to a reference atlas can continuously refine the coordinate system and associated variance. We apply this approach to the adult murine brainstem and achieve a precise alignment of projections in cytoarchitecturally ill-defined regions across brains from different animals.

Indexed as

AlgorithmsAnimalsBrainBrain MappingBrain StemComputational BiologyImage Processing, Computer-AssistedMachine LearningMagnetic Resonance ImagingMaleMiceMice, Inbred C57BLMotor NeuronsNeuroanatomyNeuronsProbability

Identifiers

PMID30858600
PMCPMC6736610
OpenAlexW2921596675

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.