ArticleScientific reports2018
Modelling brain-wide neuronal morphology via rooted Cayley trees.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Neuronal diversity and stereotypy at multiple scales through whole brain morphometry.Nature communications · 2024Article
- Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry.Research square · 2023Article
- Brain-wide dendrites in a near-optimal performance of dynamic range and information transmission.Scientific reports · 2023Article
- Cellular Localization of Orexin 1 Receptor in Human Hypothalamus and Morphological Analysis of Neurons Expressing the Receptor.Biomolecules · 2023Article
- CACTUS: a computational framework for generating realistic white matter microstructure substrates.Frontiers in neuroinformatics · 2023Article
- Neuron matters: neuromodulation with electromagnetic stimulation must consider neurons as dynamic identities.Journal of neuroengineering and rehabilitation · 2022Review
- Integrin β3 organizes dendritic complexity of cerebral cortical pyramidal neurons along a tangential gradient.Molecular brain · 2020Article
- Extrinsic Factors Regulating Dendritic Patterning.Frontiers in cellular neuroscience · 2020Review
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4 authors.
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Abstract
Neuronal morphology is an essential element for brain activity and function. We take advantage of current availability of brain-wide neuron digital reconstructions of the Pyramidal cells from a mouse brain, and analyze several emergent features of brain-wide neuronal morphology. We observe that axonal trees are self-affine while dendritic trees are self-similar. We also show that tree size appear to be random, independent of the number of dendrites within single neurons. Moreover, we consider inhomogeneous branching model which stochastically generates rooted 3-Cayley trees for the brain-wide neuron topology. Based on estimated order-dependent branching probability from actual axonal and dendritic trees, our inhomogeneous model quantitatively captures a number of topological features including size and shape of both axons and dendrites. This sheds lights on a universal mechanism behind the topological formation of brain-wide axonal and dendritic trees.
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