Effect of pruning on dendritic tree topology
- PMID: 9176635
- DOI: 10.1006/jtbi.1996.0341
Effect of pruning on dendritic tree topology
Abstract
The variability in topological shapes of observed neuronal branching patterns can accurately be described by a simple model for random sequential growth. This finding is remarkable in view of the fact that the actual neuritic growth process can vary, and includes phases of regression and removal of branches which were not considered in the model. The aim of the present study is to investigate the influence of removal of branches on the topological structure of branching patterns as well as the effect of variable growth rules. A tree asymmetry index is used for the characterization of the topological structure of a tree. The mean value of the asymmetry index for a set of dendritic trees is sensitive to the mode of growth. The effect of removal of branches ("pruning") on the topological structure of dendritic trees has been studied for several random pruning schemes, namely (i) removal of uniform randomly chosen subtrees, (ii) removal of uniform randomly chosen terminal segments, (iii) uniform random pruning during the growth process itself, and (iv) non-uniform random pruning schemes. It was found that the effect of pruning depends on both the mode of pruning and the mode of growth. Uniform random (terminal) pruning had no effect on the mean and standard deviation of the asymmetry index of trees grown with an order-independent mode of branching. Changes in the mean of the asymmetry index could occur either with non-uniform random pruning or when trees are grown according to an order-dependent mode of branching. The effect of variable growth rules was studied for several specific schemes, and it could be shown that they all result in a substantial increase in the variation in the asymmetry index of the trees.
Similar articles
-
Comparison of the topology and growth rules of motoneuronal dendrites.J Comp Neurol. 1995 Dec 18;363(3):505-16. doi: 10.1002/cne.903630312. J Comp Neurol. 1995. PMID: 8847414
-
Spatial embedding of neuronal trees modeled by diffusive growth.J Neurosci Methods. 2006 Oct 15;157(1):132-41. doi: 10.1016/j.jneumeth.2006.03.024. Epub 2006 May 11. J Neurosci Methods. 2006. PMID: 16690135
-
Morphological analysis and modeling of neuronal dendrites.Math Biosci. 2004 Mar-Apr;188:147-55. doi: 10.1016/j.mbs.2003.08.006. Math Biosci. 2004. PMID: 14766099
-
Maturation of dendritic architecture: lessons from insect identified neurons.J Neurobiol. 2005 Jul;64(1):11-23. doi: 10.1002/neu.20142. J Neurobiol. 2005. PMID: 15884008 Review.
-
How voltage-gated ion channels alter the functional properties of ganglion and amacrine cell dendrites.Arch Ital Biol. 2002 Oct;140(4):347-59. Arch Ital Biol. 2002. PMID: 12228988 Review.
Cited by
-
Principles of branch dynamics governing shape characteristics of cerebellar Purkinje cell dendrites.Development. 2012 Sep;139(18):3442-55. doi: 10.1242/dev.081315. Development. 2012. PMID: 22912417 Free PMC article.
-
Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction.Elife. 2020 Nov 26;9:e60920. doi: 10.7554/eLife.60920. Elife. 2020. PMID: 33241995 Free PMC article.
-
Topological characterization of neuronal arbor morphology via sequence representation: I--motif analysis.BMC Bioinformatics. 2015 Jul 10;16:216. doi: 10.1186/s12859-015-0604-2. BMC Bioinformatics. 2015. PMID: 26156313 Free PMC article.
-
Convergence among non-sister dendritic branches: an activity-controlled mean to strengthen network connectivity.PLoS One. 2008;3(11):e3782. doi: 10.1371/journal.pone.0003782. Epub 2008 Nov 21. PLoS One. 2008. PMID: 19023423 Free PMC article.
-
Topology recapitulates morphogenesis of neuronal dendrites.Cell Rep. 2023 Nov 28;42(11):113268. doi: 10.1016/j.celrep.2023.113268. Epub 2023 Oct 28. Cell Rep. 2023. PMID: 38007691 Free PMC article.
MeSH terms
LinkOut - more resources
Full Text Sources
