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Updated: Sep 26, 2026

Automatic Identification of Dendritic Branches and their Orientation
Published on: September 17, 2021
Deriving physical connectivity from neuronal morphology
Nir Kalisman1, Gilad Silberberg, Henry Markram
1Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel.
Abstract:
A model is presented that allows prediction of the probability for the formation of appositions between the axons and dendrites of any two neurons based only on their morphological statistics and relative separation. Statistics of axonal and dendritic morphologies of single neurons are obtained from 3D reconstructions of biocytin-filled cells, and a statistical representation of the same cell type is obtained by averaging across neurons according to the model. A simple mathematical formulation is applied to the axonal and dendritic statistical representations to yield the probability for close appositions. The model is validated by a mathematical proof and by comparison of predicted appositions made by layer 5 pyramidal neurons in the rat somatosensory cortex with real anatomical data. The model could be useful for studying microcircuit connectivity and for designing artificial neural networks.
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