ArticleNeuroinformatics2018
A Topological Representation of Branching Neuronal Morphologies.
Article in Neuroinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.
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Who cites it
74 citing papers in PubMed.
- Corticosterone-linked microglial activity underpins sexually dimorphic neuroplasticity after ketamine anesthesia.Science advances · 2026Article
- Temporal Topology Provides an Interpretable Framework for Neuronal Morphogenesis.Neuroinformatics · 2026Article
- Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Topo-CNN: Retinal Image Analysis with Topological Deep Learning.Journal of imaging informatics in medicine · 2026Article
- HOG-CNN: Integrating Histogram of Oriented Gradients with Convolutional Neural Networks for Retinal Image Classification.Journal of imaging informatics in medicine · 2026Article
- A multimodal spatial atlas of transcriptomic, morphological, and electrophysiological cell type densities in the mouse brain.PLoS computational biology · 2026Article
- Ultrastructure of astrocytes using volume electron microscopy: A scoping review.The Journal of physiology · 2026Article
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- Decoding gray matter, large-scale analysis of brain cell morphometry to inform microstructural modeling of diffusion MR signals.Communications biology · 2026Article
- MesoSCOUT: A novel tool for revealing mesoscale organization in the white-matter connectome.bioRxiv : the preprint server for biology · 2025Article
- Topology across scales on heterogeneous cell data.PLoS computational biology · 2025Article
- Article
- Topological classification of tumour-immune interactions and dynamics.Journal of mathematical biology · 2025Article
- Generating brain-wide connectome using synthetic axonal morphologies.Nature communications · 2025Article
- Of mice and men: Dendritic architecture differentiates human from mouse neuronal networks.iScience · 2025Article
- Topological Neuroscience: Linking Circuits to Function.Annual review of neuroscience · 2025Review
- Skeletonization of neuronal processes using Discrete Morse techniques from computational topology.Research square · 2025Article
- Predicting Affinity Through Homology (PATH): Interpretable binding affinity prediction with persistent homology.PLoS computational biology · 2025Article
- Skeletonization of neuronal processes using Discrete Morse techniques from computational topology.bioRxiv : the preprint server for biology · 2025Article
- Skeletonization of neuronal processes using Discrete Morse techniques from computational topology.ArXiv · 2025Article
14 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many biological systems consist of branching structures that exhibit a wide variety of shapes. Our understanding of their systematic roles is hampered from the start by the lack of a fundamental means of standardizing the description of complex branching patterns, such as those of neuronal trees. To solve this problem, we have invented the Topological Morphology Descriptor (TMD), a method for encoding the spatial structure of any tree as a "barcode", a unique topological signature. As opposed to traditional morphometrics, the TMD couples the topology of the branches with their spatial extents by tracking their topological evolution in 3-dimensional space. We prove that neuronal trees, as well as stochastically generated trees, can be accurately categorized based on their TMD profiles. The TMD retains sufficient global and local information to create an unbiased benchmark test for their categorization and is able to quantify and characterize the structural differences between distinct morphological groups. The use of this mathematically rigorous method will advance our understanding of the anatomy and diversity of branching morphologies.
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