Digital Reconstructions of Neuronal Morphology: Three Decades of Research Trends

Overview

Journal Front Neurosci

Date 2012 Apr 27

PMID 22536169

Citations 72

Authors

Maryam Halavi

Kelly A Hamilton

Ruchi Parekh

Giorgio A Ascoli

Affiliations

Soon will be listed here.

Abstract

The importance of neuronal morphology has been recognized from the early days of neuroscience. Elucidating the functional roles of axonal and dendritic arbors in synaptic integration, signal transmission, network connectivity, and circuit dynamics requires quantitative analyses of digital three-dimensional reconstructions. We extensively searched the scientific literature for all original reports describing reconstructions of neuronal morphology since the advent of this technique three decades ago. From almost 50,000 titles, 30,000 abstracts, and more than 10,000 full-text articles, we identified 902 publications describing ∼44,000 digital reconstructions. Reviewing the growth of this field exposed general research trends on specific animal species, brain regions, neuron types, and experimental approaches. The entire bibliography, annotated with relevant metadata and (wherever available) direct links to the underlying digital data, is accessible at NeuroMorpho.Org.

Citing Articles

Accelerating the continuous community sharing of digital neuromorphology data.

Tecuatl C, Ljungquist B, Ascoli G FASEB Bioadv. 2024; 6(7):207-221.

PMID: 38974113 PMC: 11226999. DOI: 10.1096/fba.2024-00048.

From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation.

Hoffmann C, Cho E, Zalesky A, Di Biase M Commun Biol. 2024; 7(1):571.

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NeuroEditor: a tool to edit and visualize neuronal morphologies.

Velasco I, Garcia-Cantero J, Brito J, Bayona S, Pastor L, Mata S Front Neuroanat. 2024; 18:1342762.

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Bibliometric analysis of neuroscience publications quantifies the impact of data sharing.

Emissah H, Ljungquist B, Ascoli G Bioinformatics. 2023; 39(12).

PMID: 38070153 PMC: 10733721. DOI: 10.1093/bioinformatics/btad746.

Online conversion of reconstructed neural morphologies into standardized SWC format.

Mehta K, Ljungquist B, Ogden J, Nanda S, Ascoli R, Ng L Nat Commun. 2023; 14(1):7429.

PMID: 37973857 PMC: 10654402. DOI: 10.1038/s41467-023-42931-x.

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