Automated algorithms for multiscale morphometry of neuronal dendrites

Christina M. Weaver, Patrick R. Hof, Susan L. Wearne, W. Brent Lindquist

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

We describe the synthesis of automated neuron branching morphology and spine detection algorithms to provide multiscale three-dimensional morphological analysis of neurons. The resulting software is applied to the analysis of a high-resolution (0.098 μm × 0.098 μm × 0.081 μm) image of an entire pyramidal neuron from layer III of the superior temporal cortex in rhesus macaque monkey. The approach provides a highly automated, complete morphological analysis of the entire neuron; each dendritic branch segment is characterized by several parameters, including branch order, length, and radius as a function of distance along the branch, as well as by the locations, lengths, shape classification (e.g., mushroom, stubby, thin), and density distribution of spines on the branch. Results for this automated analysis are compared to published results obtained by other computer-assisted manual means.

Original languageEnglish
Pages (from-to)1353-1383
Number of pages31
JournalNeural Computation
Volume16
Issue number7
DOIs
StatePublished - Jul 2004

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