Evidence map›Paper›PMID 37105968›Full record

ArticleScientific data2023

Multi-modal brain magnetic resonance imaging database covering marmosets with a wide age range.

Junichi Hata, Ken Nakae, Hiromichi Tsukada, Alexander Woodward, Yawara Haga, Mayu Iida, Akiko Uematsu, Fumiko Seki, Noritaka Ichinohe, Rui Gong and 19 more

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
6.9field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 30 citations in OpenAlex.

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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

29 authors at 9 institutions in 1 country.

Junichi Hata *Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan. j-hata@tmu.ac.jp.ORCID http://orcid.org/0000-0001-5833-444X
Ken Nakae *Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Aichi, Japan.
Hiromichi TsukadaCenter for Mathematical Science and Artificial Intelligence, Chubu University, Aichi, Japan.
Alexander WoodwardConnectome Analysis Unit, RIKEN Center for Brain Science, Saitama, Japan.ORCID http://orcid.org/0000-0003-3068-1401
Yawara HagaLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.
Mayu IidaGraduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan.
Akiko UematsuLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.
Fumiko SekiLive Animal Imaging Center, Central Institute for Experimental Animals, Kanagawa, Japan.
Noritaka IchinoheDepartment of Ultrastructural Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan.
Rui GongConnectome Analysis Unit, RIKEN Center for Brain Science, Saitama, Japan.
Takaaki KanekoCenter for the Evolutionary Origins of Human Behavior, Kyoto University, Aichi, Japan.
Daisuke YoshimaruLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.
Akiya WatakabeLaboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Saitama, Japan.ORCID http://orcid.org/0000-0002-8382-3840
Hiroshi AbeLaboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Saitama, Japan.ORCID http://orcid.org/0000-0002-9711-9715
Toshiki TaniLaboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Saitama, Japan.
Hiro Taiyo HamdaNeural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan.
Carlos Enrique GutierrezNeural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan.
Henrik SkibbeBrain Image Analysis Unit, RIKEN Center for Brain Science, Saitama, Japan.
Masahide MaedaConnectome Analysis Unit, RIKEN Center for Brain Science, Saitama, Japan.
Frederic PapazianConnectome Analysis Unit, RIKEN Center for Brain Science, Saitama, Japan.
Kei HagiyaLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.
Noriyuki KishiLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.
Shin IshiiGraduate School of Informatics, Kyoto University, Kyoto, Japan.
Kenji DoyaNeural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan.ORCID http://orcid.org/0000-0002-2446-6820
Tomomi ShimogoriLaboratory for Molecular Mechanisms of Brain Development, RIKEN Center for Brain Science, Saitama, Japan.
Tetsuo YamamoriLaboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Saitama, Japan.
Keiji TanakaConnectome Analysis Unit, RIKEN Center for Brain Science, Saitama, Japan.
Hirotaka James OkanoLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.ORCID http://orcid.org/0000-0003-4611-7098
Hideyuki OkanoLaboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan. hidokano@keio.jp.
RIKEN Center for Brain Science · JPJikei University School of Medicine · JPOkinawa Institute of Science and Technology Graduate University · JPCentral Institute for Experimental Animals · JPKyoto University · JPKeio University · JPNational Center of Neurology and Psychiatry · JPNational Institutes of Natural Sciences · JPTokyo Metropolitan University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) is a non-invasive neuroimaging technique that is useful for identifying normal developmental and aging processes and for data sharing. Marmosets have a relatively shorter life expectancy than other primates, including humans, because they grow and age faster. Therefore, the common marmoset model is effective in aging research. The current study investigated the aging process of the marmoset brain and provided an open MRI database of marmosets across a wide age range. The Brain/MINDS Marmoset Brain MRI Dataset contains brain MRI information from 216 marmosets ranging in age from 1 and 10 years. At the time of its release, it is the largest public dataset in the world. It also includes multi-contrast MRI images. In addition, 91 of 216 animals have corresponding high-resolution ex vivo MRI datasets. Our MRI database, available at the Brain/MINDS Data Portal, might help to understand the effects of various factors, such as age, sex, body size, and fixation, on the brain. It can also contribute to and accelerate brain science studies worldwide.

Indexed as

BrainCallithrixMagnetic Resonance ImagingAge FactorsAnimalsDatabases, FactualNeuroimaging

Identifiers

PMID37105968
PMCPMC10250358
OpenAlexW4367181422

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.