NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases
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Abstract
Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. VIDEO ABSTRACT.
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Using morphology (NBLAST) and connectivity, the large majority of neurons were assigned to specific HATs that matched in all three hemispheres (FlyWire left, right, hemibrain).
“by comparison of morphology (NBLAST38), as well as connectivity (assuming that homologous neurons share synaptic partners), we were able to assign the large majority of neurons to specific HATs that matched in all three hemispheres.”
From Whole-brain annotation and multi-connectome cell typing of Drosophila (2024) · cites this paper as [38]
NBLAST compares two morphologies by examining the distance and local direction of nearby points between them.
“This method compares a pair of morphologies by analyzing the distance and local direction of nearby points between the two structures.”
From Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells (2020) · cites this paper as Costa et al., 2016
The analysis based on soma side or neck plane side and NBLAST clustering allowed for an initial grouping of left-right homologous sets and enabled the identification of neurons with different morphologies on each side of the nervous system, triggering further proofreading.
“This analysis allowed for an initial grouping of left–right homologous sets and enabled the identification of neurons with different morphologies on each side of the nervous system, triggering further proofreading”
From Comparative connectomics of Drosophila descending and ascending neurons (2025) · cites this paper as [74]
Phelps et al.'s computational analysis, based on NBLAST, identified bundles of neurons with primary neurites running together from soma to axon, but was limited to primary neurites of manually traced motor neurons.
“Then, we used a computational analysis from Phelps et al.1, which relied on the NBLAST algorithm72 to identify bundles, or groups of neurons with primary neurites that run together from the soma to the axon. Phelps et al. limited this analysis to the primary neurites of the manually traced MNs.”
From Connectomic reconstruction of a female Drosophila ventral nerve cord (2024) · cites this paper as [72]
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- Authors
- Costa, M., Manton, J. D., Ostrovsky, A. D., Prohaska, S., & Jefferis, G. S. X. E.
- Affiliations
- MRC Laboratory of Molecular Biology (GB)
- Corresponding author
- Jefferis, Gregory S.X.E.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 91
- Issue
- 2
- Pages
- 293-311
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC4961245
- OpenAlex
- W2951976236
- Cited by
- 294
- References
- 77
- Citations by year
- 2026: 20 · 2025: 35 · 2024: 42 · 2023: 39 · 2022: 24 · 2021: 17 · 2020: 35 · 2019: 18 · 2018: 24 · 2017: 19 · 2016: 13 · 2015: 7 · 2014: 1
- FWCI
- 15.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Neuron (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- National Tsing Hua University
- Medical Research Council (U105188491)
- National Institute of Biomedical Imaging and Bioengineering
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- neural circuit mapping, Drosophila neurons, neuronal morphology, automatic clustering, invertebrate neurons
- MeSH terms
- Algorithms, Animals, Brain, Nerve Net, Neurons, Statistics as Topic, Time Factors, Cluster Analysis, Databases, Factual, Computational Biology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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