ArticleFrontiers in neuroanatomy2014
Automated computation of arbor densities: a step toward identifying neuronal cell types.
Article in Frontiers in neuroanatomy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
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.
Who cites it
14 citing papers in PubMed.
- High-throughput analysis of dendrite and axonal arbors reveals transcriptomic correlates of neuroanatomy.Nature communications · 2024Article
- A community-based transcriptomics classification and nomenclature of neocortical cell types.Nature neuroscience · 2020Review
- Transgenic models for investigating the nervous system: Currently available neurofluorescent reporters and potential neuronal markers.Biochimica et biophysica acta. General subjects · 2020Review
- Inducible rodent models of glaucoma.Progress in retinal and eye research · 2020Review
- Density Visualization Pipeline: A Tool for Cellular and Network Density Visualization and Analysis.Frontiers in computational neuroscience · 2020Article
- Article
- The diversity of GABAergic neurons and neural communication elements.Nature reviews. Neuroscience · 2019Review
- Cellular properties of intrinsically photosensitive retinal ganglion cells during postnatal development.Neural development · 2019Article
- Generative models and abstractions for large-scale neuroanatomy datasets.Current opinion in neurobiology · 2019Review
- Morphological Neuron Classification Based on Dendritic Tree Hierarchy.Neuroinformatics · 2019Article
- The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas.Neuron · 2017Review
- Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping.Nature protocols · 2015Article
- Function and Circuitry of VIP+ Interneurons in the Mouse Retina.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015Article
- Editorial: Quantitative Analysis of Neuroanatomy.Frontiers in neuroanatomy · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The shape and position of a neuron convey information regarding its molecular and functional identity. The identification of cell types from structure, a classic method, relies on the time-consuming step of arbor tracing. However, as genetic tools and imaging methods make data-driven approaches to neuronal circuit analysis feasible, the need for automated processing increases. Here, we first establish that mouse retinal ganglion cell types can be as precise about distributing their arbor volumes across the inner plexiform layer as they are about distributing the skeletons of the arbors. Then, we describe an automated approach to computing the spatial distribution of the dendritic arbors, or arbor density, with respect to a global depth coordinate based on this observation. Our method involves three-dimensional reconstruction of neuronal arbors by a supervised machine learning algorithm, post-processing of the enhanced stacks to remove somata and isolate the neuron of interest, and registration of neurons to each other using automatically detected arbors of the starburst amacrine interneurons as fiducial markers. In principle, this method could be generalizable to other structures of the CNS, provided that they allow sparse labeling of the cells and contain a reliable axis of spatial reference.
Indexed as
Identifiers
What OpenQuestion holds
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.