Literature DB >> 22169536

A general principle of neural arbor branch density.

Corinne M Teeter1, Charles F Stevens.   

Abstract

The tree-like structures of a neuron that are responsible for distributing (axons) or collecting (dendrites) information over a region of the brain are called arbors. The size of the territory occupied by an arbor and the density of the arbor branches within that territory are important for computation because these factors determine what fraction of a neural map is sampled by a single cell and at what resolution [1]. Arbor territory size and branch density can vary by many orders of magnitude; however, we have identified a universal relationship between these two physical properties revealing a general neural architectural design principle. All of the arbors (axons and dendrites) we have studied (including fish retinal ganglion cells, rodent Purkinje cells, and the cortical arbors of various neural classes from rat, cat, monkey, and human) are found to be systematically less dense when they cover larger territories. This relationship can be described as a power law. Of several simple biological explanations explored, we find that this relationship is most consistent with a design principle that conserves the average number of connections between pairs of arbors of different sizes.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 22169536     DOI: 10.1016/j.cub.2011.11.013

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  22 in total

1.  A scaling law derived from optimal dendritic wiring.

Authors:  Hermann Cuntz; Alexandre Mathy; Michael Häusser
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-19       Impact factor: 11.205

2.  The effects of neuron morphology on graph theoretic measures of network connectivity: the analysis of a two-level statistical model.

Authors:  Jugoslava Aćimović; Tuomo Mäki-Marttunen; Marja-Leena Linne
Journal:  Front Neuroanat       Date:  2015-06-10       Impact factor: 3.856

3.  Neural arbors are Pareto optimal.

Authors:  Arjun Chandrasekhar; Saket Navlakha
Journal:  Proc Biol Sci       Date:  2019-05-15       Impact factor: 5.349

4.  Morphological Neuron Classification Based on Dendritic Tree Hierarchy.

Authors:  Evelyn Perez Cervantes; Cesar Henrique Comin; Roberto Marcondes Cesar Junior; Luciano da Fontoura Costa
Journal:  Neuroinformatics       Date:  2019-01

5.  A general principle governs vision-dependent dendritic patterning of retinal ganglion cells.

Authors:  Hong-Ping Xu; Jin Hao Sun; Ning Tian
Journal:  J Comp Neurol       Date:  2014-04-29       Impact factor: 3.215

6.  Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices.

Authors:  Joseph M Amatrudo; Christina M Weaver; Johanna L Crimins; Patrick R Hof; Douglas L Rosene; Jennifer I Luebke
Journal:  J Neurosci       Date:  2012-10-03       Impact factor: 6.167

7.  Nerve growth factor-induced formation of axonal filopodia and collateral branches involves the intra-axonal synthesis of regulators of the actin-nucleating Arp2/3 complex.

Authors:  Mirela Spillane; Andrea Ketschek; Chris J Donnelly; Almudena Pacheco; Jeffrey L Twiss; Gianluca Gallo
Journal:  J Neurosci       Date:  2012-12-05       Impact factor: 6.167

Review 8.  Neuronal morphology goes digital: a research hub for cellular and system neuroscience.

Authors:  Ruchi Parekh; Giorgio A Ascoli
Journal:  Neuron       Date:  2013-03-20       Impact factor: 17.173

Review 9.  Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology.

Authors:  Ruchi Parekh; Giorgio A Ascoli
Journal:  Neuroscientist       Date:  2014-06-27       Impact factor: 7.519

10.  A quantitative analysis of cerebellar anatomy in birds.

Authors:  Felipe Cunha; Cristian Gutiérrez-Ibáñez; Kelsey Racicot; Douglas R Wylie; Andrew N Iwaniuk
Journal:  Brain Struct Funct       Date:  2021-08-06       Impact factor: 3.270

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