ArticleFrontiers in neuroinformatics2012
An ontological approach to describing neurons and their relationships.
Article in Frontiers in neuroinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Modeling sources of interlaboratory variability in electrophysiological properties of mammalian neurons.Journal of neurophysiology · 2018Pooled it
- Automatic identification of scientific publications describing digital reconstructions of neural morphology.Brain informatics · 2023Article
- Cell morphologies in the nervous system: Glia steal the limelight.The Journal of comparative neurology · 2023Article
- The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.Frontiers in neuroinformatics · 2023Review
- Assisted neuroscience knowledge extraction via machine learning applied to neural reconstruction metadata on NeuroMorpho.Org.Brain informatics · 2022Article
- Molecular ontology of the parabrachial nucleus.The Journal of comparative neurology · 2022Article
- Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project.Frontiers in neuroinformatics · 2022Article
- Neuronal classification from network connectivity via adjacency spectral embedding.Network neuroscience (Cambridge, Mass.) · 2021Article
- Operations Research Methods for Estimating the Population Size of Neuron Types.Annals of operations research · 2020Article
- An open-source framework for neuroscience metadata management applied to digital reconstructions of neuronal morphology.Brain informatics · 2020Article
- Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons.Frontiers in neuroanatomy · 2019Article
- Origin of heterogeneous spiking patterns from continuously distributed ion channel densities: a computational study in spinal dorsal horn neurons.The Journal of physiology · 2018Article
- An ontology-based search engine for digital reconstructions of neuronal morphology.Brain informatics · 2017Article
- Name-calling in the hippocampus (and beyond): coming to terms with neuron types and properties.Brain informatics · 2017Article
- Twenty years of ModelDB and beyond: building essential modeling tools for the future of neuroscience.Journal of computational neuroscience · 2017Review
- A Quantitative Golgi Study of Dendritic Morphology in the Mice Striatal Medium Spiny Neurons.Frontiers in neuroanatomy · 2017Article
- Reproducibility in Computational Neuroscience Models and Simulations.IEEE transactions on bio-medical engineering · 2016Article
- In search of a periodic table of the neurons: Axonal-dendritic circuitry as the organizing principle: Patterns of axons and dendrites within distinct anatomical parcels provide the blueprint for circuit-based neuronal classification.BioEssays : news and reviews in molecular, cellular and developmental biology · 2016Review
- Article
- Brain-wide analysis of electrophysiological diversity yields novel categorization of mammalian neuron types.Journal of neurophysiology · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The advancement of neuroscience, perhaps one of the most information rich disciplines of all the life sciences, requires basic frameworks for organizing the vast amounts of data generated by the research community to promote novel insights and integrated understanding. Since Cajal, the neuron remains a fundamental unit of the nervous system, yet even with the explosion of information technology, we still have few comprehensive or systematic strategies for aggregating cell-level knowledge. Progress toward this goal is hampered by the multiplicity of names for cells and by lack of a consensus on the criteria for defining neuron types. However, through umbrella projects like the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF), we have the opportunity to propose and implement an informatics infrastructure for establishing common tools and approaches to describe neurons through a standard terminology for nerve cells and a database (a Neuron Registry) where these descriptions can be deposited and compared. This article provides an overview of the problem and outlines a solution approach utilizing ontological characterizations. Based on illustrative implementation examples, we also discuss the need for consensus criteria to be adopted by the research community, and considerations on future developments. A scalable repository of neuron types will provide researchers with a resource that materially contributes to the advancement of neuroscience.
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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.