Evidence map›Paper›PMID 32511750›Full record

ArticleThe Journal of comparative neurology2021

An open access mouse brain flatmap and upgraded rat and human brain flatmaps based on current reference atlases.

Joel D Hahn, Larry W Swanson, Ian Bowman, Nicholas N Foster, Brian Zingg, Michael S Bienkowski, Houri Hintiryan, Hong-Wei Dong

Open access · greenAbstract read
In one paragraph

Article in The Journal of comparative neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.3field-weighted citation impact, top 6% 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

28 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Intrinsic neuronal network organization of a mammalian peripheral nervous system.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Article
  7. The intrinsic neuronal network of the central nervous system and its modular (subsystem) architecture in a mammal.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Neural network architecture of a mammalian brain.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  12. Interactive data exploration websites for large-scale electrophysiology.bioRxiv : the preprint server for biology · 2024
    Article
  13. Review
  14. Network architecture of intrinsic connectivity in a mammalian spinal cord (the central nervous system's caudal sector).Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  15. Article
  16. Intrinsic circuitry of the rhombicbrain (central nervous system's intermediate sector) in a mammal.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  17. Article
  18. Activation of the nociceptin/orphanin-FQ receptor promotes NREM sleep and EEG slow wave activity.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  19. Article
  20. 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.

Joel D HahnDepartment of Biological Sciences, University of Southern California, California, Los Angeles, USA.ORCID 0000-0003-4024-0247
Larry W SwansonDepartment of Biological Sciences, University of Southern California, California, Los Angeles, USA.ORCID 0000-0002-4260-3892
Ian BowmanCenter for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Nicholas N FosterCenter for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Brian ZinggCenter for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Michael S BienkowskiCenter for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Houri HintiryanCenter for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
Hong-Wei DongCenter for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.
University of Southern California · US

Funding

Anatomical characterization of neuronal cell types of the mouse brainU01MH114829 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ASCOLI, GIORGIO A, DONG, HONG-WEI · 2017 to 2021
$13.9M
The Mouse Connectome Project Phase III: Assembling the global neural networks of the mouse brainR01MH094360 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI DONG, HONG-WEI · 2012 to 2021
$7.4M
Integrative approach to classifying neuronal cell types of the mouse hippocampusRF1MH114112 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI DONG, HONG-WEI, ZHANG, LI I · 2017 to 2017
$4.2M
NIMH NIH HHS R01 MH094360NIMH NIH HHS RF1 MH114112NIMH NIH HHS U01 MH114829
6 · The paper itself

Abstract

Here we present a flatmap of the mouse central nervous system (CNS) (brain) and substantially enhanced flatmaps of the rat and human brain. Also included are enhanced representations of nervous system white matter tracts, ganglia, and nerves, and an enhanced series of 10 flatmaps showing different stages of rat brain development. The adult mouse and rat brain flatmaps provide layered diagrammatic representation of CNS divisions, according to their arrangement in corresponding reference atlases: Brain Maps 4.0 (BM4, rat) (Swanson, The Journal of Comparative Neurology, 2018, 526, 935-943), and the first version of the Allen Reference Atlas (mouse) (Dong, The Allen reference atlas, (book + CD-ROM): A digital color brain atlas of the C57BL/6J male mouse, 2007). To facilitate comparative analysis, both flatmaps are scaled equally, and the divisional hierarchy of gray matter follows a topographic arrangement used in BM4. Also included with the mouse and rat brain flatmaps are cerebral cortex atlas level contours based on the reference atlases, and direct graphical and tabular comparison of regional parcellation. To encourage use of the brain flatmaps, they were designed and organized, with supporting reference tables, for ease-of-use and to be amenable to computational applications. We demonstrate how they can be adapted to represent novel parcellations resulting from experimental data, and we provide a proof-of-concept for how they could form the basis of a web-based graphical data viewer and analysis platform. The mouse, rat, and human brain flatmap vector graphics files (Adobe Reader/Acrobat viewable and Adobe Illustrator editable) and supporting tables are provided open access; they constitute a broadly applicable neuroscience toolbox resource for researchers seeking to map and perform comparative analysis of brain data.

Indexed as

Atlases as TopicMedical IllustrationOpen Access PublishingAnimalsBrainBrain MappingHumansMiceRatsSpecies Specificitybrain atlasesbrain flatmapbrain mappingcomputer graphicshumanmouserat

Identifiers

PMID32511750
PMCPMC7721992
OpenAlexW3033275359

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.