Evidence map›Paper›PMID 37524935›Full record

ReviewNature reviews. Neuroscience2023

Network models to enhance the translational impact of cross-species studies.

Julia K Brynildsen, Kanaka Rajan, Michael X Henderson, Dani S Bassett

Open access · greenAbstract readReview
In one paragraph

Review in Nature reviews. Neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
8.9field-weighted citation impact, top 2% 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

19 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. The Cerebellar Connectome.Cerebellum (London, England) · 2026
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  6. Review
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  15. Uncovering multiscale structure in the variability of larval zebrafish navigation.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  16. Review
  17. Article
  18. Review
  19. Factors influencing JUUL e-cigarette nicotine vapour-induced reward, withdrawal, pharmacokinetics and brain connectivity in rats: sex matters.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    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

4 authors at 4 institutions in 1 country.

Julia K BrynildsenDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-1627-6576
Kanaka RajanDepartment of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0003-2749-2917
Michael X HendersonParkinson's Disease Center, Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA.
Dani S BassettDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA. dsb@seas.upenn.edu.ORCID 0000-0002-6183-4493
Allen Institute for Brain Science · USSanta Fe Institute · USUniversity of Pennsylvania · USVan Andel Institute · US

Funding

Neural Network Models Constrained by Multiscale Data to Infer Minimal Functional Motifs in the BrainRF1DA056403 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI RAJAN, KANAKA · 2022 to 2022
$1.2M
Metabolic control of cue reactivity during alcohol withdrawalF32AA030475 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI BRYNILDSEN, JULIA KATHERINE · 2022 to 2025
$188k
NIAAA NIH HHS F32 AA030475NIDA NIH HHS RF1 DA056403
6 · The paper itself

Abstract

Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.

Indexed as

BrainNeurosciencesAnimalsHumansNeurobiologyNeuroimagingTranslational Research, Biomedical

Identifiers

PMID37524935
PMCPMC10634203
OpenAlexW4385409987

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.