Evidence map›Paper›PMID 38974113›Full record

ArticleFASEB bioAdvances2024

Accelerating the continuous community sharing of digital neuromorphology data.

Carolina Tecuatl, Bengt Ljungquist, Giorgio A Ascoli

Abstract read
In one paragraph

Article in FASEB bioAdvances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Computational modelling of the suppression of optic nerve fibre.Medical & biological engineering & computing · 2026
    Article
  6. Article
  7. Article
  8. Hippocampome.org, a resource for subicular neuron types and beyond.bioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Article
  11. Spatiotemporal Dynamics of Lateral NaThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  12. Review
  13. Spatio-temporal dynamics of lateral NabioRxiv : the preprint server for biology · 2025
    Article
  14. Wrap it up: myelination of transplanted neurons for repair.Frontiers in cellular neuroscience · 2025
    Review
  15. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Carolina TecuatlBioengineering Department and Center for Neural Informatics, Structures and Plasticity, College of Engineering and Computing George Mason University Fairfax Virginia USA.ORCID https://orcid.org/0000-0001-6398-3444
Bengt LjungquistBioengineering Department and Center for Neural Informatics, Structures and Plasticity, College of Engineering and Computing George Mason University Fairfax Virginia USA.ORCID https://orcid.org/0000-0002-3934-5853
Giorgio A AscoliBioengineering Department and Center for Neural Informatics, Structures and Plasticity, College of Engineering and Computing George Mason University Fairfax Virginia USA.ORCID https://orcid.org/0000-0002-0964-676X

Funding

Generation and Description of Neuronal Morphology and ConnectivityR01NS039600 · NINDS · GEORGE MASON UNIVERSITY · PI ASCOLI, GIORGIO A · 1999 to 2024
$6.9M
Cytoskeletal mechanisms of dendrite arbor shape developmentR01NS086082 · NINDS · GEORGIA STATE UNIVERSITY · PI ASCOLI, GIORGIO A, COX, DANIEL N · 2013 to 2023
$3.1M
Long-range neuronal projections: circuit blueprint or stochastic targeting? Rigorous classification of brain-wide axonal reconstructionsRF1MH128693 · NIMH · GEORGE MASON UNIVERSITY · PI ASCOLI, GIORGIO A · 2021 to 2021
$1.3M
NIMH NIH HHS RF1 MH128693NINDS NIH HHS R01 NS039600NINDS NIH HHS R01 NS086082
6 · The paper itself

Abstract

The tree-like morphology of neurons and glia is a key cellular determinant of circuit connectivity and metabolic function in the nervous system of essentially all animals. To elucidate the contribution of specific cell types to both physiological and pathological brain states, it is important to access detailed neuroanatomy data for quantitative analysis and computational modeling. NeuroMorpho.Org is the largest online collection of freely available digital neural reconstructions and related metadata and is continuously updated with new uploads. Earlier in the project, we released multiple datasets together yearly, but this process caused an average delay of several months in making the data public. Moreover, in the past 5 years, >80% of invited authors agreed to share their data with the community via NeuroMorpho.Org, up from <20% in the first 5 years of the project. In the same period, the average number of reconstructions per publication increased 600%, creating the need for automatic processing to release more reconstructions in less time. The progressive automation of our pipeline enabled the transition to agile releases of individual datasets as soon as they are ready. The overall time from data identification to public sharing decreased by 63.7%; 78% of the datasets are now released in less than 3 months with an average workflow duration below 40 days. Furthermore, the mean processing time per reconstruction dropped from 3 h to 2 min. With these continuous improvements, NeuroMorpho.Org strives to forge a positive culture of open data. Most importantly, the new, original research enabled through reuse of datasets across the world has a multiplicative effect on science discovery, benefiting both authors and users.

Indexed as

data sharingdigital reconstructionsmetadataneuron morphologyopen source

Identifiers

PMID38974113
PMCPMC11226999

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.