ReviewNeuroinformatics2007
Successes and rewards in sharing digital reconstructions of neuronal morphology.
Review in Neuroinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Bridging the Brain and Data Sciences.Big data · 2021Article
- Highlights from the Era of Open Source Web-Based Tools.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Review
- Turning the Tide of Data Sharing.Neuroinformatics · 2019Article
- An open repository for single-cell reconstructions of the brain forest.Scientific data · 2018Article
- Sharing Neuron Data: Carrots, Sticks, and Digital Records.PLoS biology · 2015Article
- Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2015Review
- The 40-year history of modeling active dendrites in cerebellar Purkinje cells: emergence of the first single cell "community model".Frontiers in computational neuroscience · 2015Review
- Article
- Statistical analysis and data mining of digital reconstructions of dendritic morphologies.Frontiers in neuroanatomy · 2014Article
- Review
- Communication and wiring in the cortical connectome.Frontiers in neuroanatomy · 2012Article
- Models and simulation of 3D neuronal dendritic trees using Bayesian networks.Neuroinformatics · 2011Article
- The tree-edit-distance, a measure for quantifying neuronal morphology.Neuroinformatics · 2009Article
- Detection of the optimal neuron traces in confocal microscopy images.Journal of neuroscience methods · 2009Article
- NeuroMorpho.Org implementation of digital neuroscience: dense coverage and integration with the NIF.Neuroinformatics · 2008Article
- Non-parametric algorithmic generation of neuronal morphologies.Neuroinformatics · 2008Article
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Authors and funding
1 author.
Funding
Abstract
The computer-assisted three-dimensional reconstruction of neuronal morphology is becoming an increasingly popular technique to quantify the arborization patterns of dendrites and axons. The resulting digital files are suitable for comprehensive morphometric analyses as well as for building anatomically realistic compartmental models of membrane biophysics and neuronal electrophysiology. The digital tracings acquired in a lab for a specific purpose can be often re-used by a different research group to address a completely unrelated scientific question, if the original investigators are willing to share the data. Since reconstructing neuronal morphology is a labor-intensive process, data sharing and re-analysis is particularly advantageous for the neuroscience and biomedical communities. Here we present numerous cases of "success stories" in which digital reconstructions of neuronal morphology were shared and re-used, leading to additional, independent discoveries and publications, and thus amplifying the impact of the "source" study for which the data set was first collected. In particular, we overview four main applications of this kind of data: comparative morphometric analyses, statistical estimation of potential synaptic connectivity, morphologically accurate electrophysiological simulations, and computational models of neuronal shape and development.
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Registered trials
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.