Literature DB >> 16083911

Functionally relevant measures of spatial complexity in neuronal dendritic arbors.

P Rothnie1, D Kabaso, P R Hof, B I Henry, S L Wearne.   

Abstract

We introduce a set of scaling exponents for characterizing global 3D morphologic properties of mass distribution, branching and taper in neuronal dendritic arbors, capable of distinguishing functionally relevant changes in dendritic complexity that standard Sholl analysis and fractal analysis cannot. We demonstrate that the scaling exponent for mass distribution, d(M), comprises a sum of independent scaling exponents for branching, d(N), and taper, d(T). The accuracy of experimental measurements of the scaling exponents was verified using computer generated self-similar binary trees of known fractal dimension, and with prescribed amounts of branching and taper. The theory was applied to measuring 3D spatial complexity in the apical and basal dendritic trees of two functionally distinct types of macaque monkey neocortical pyramidal neurons: long corticocortical projection neurons from superior temporal cortex to area 46 of the prefrontal cortex (PFC), and local projection neurons within area 46 of the PFC. Two distinct scaling subregions (proximal and medial) were identified in both apical and basal trees of the two neuron types, and scaling exponents were fitted. A small but significant difference in mass scaling in the proximal region distinguished long from local projection neurons. Interestingly, both classes of neuron exhibited a homeostatic pattern of mass distribution across the two regions: despite large differences between proximal and medial regions in branching and tapering exponents, these effects were compensatory, resulting in a uniform, slow reduction of mass with distance from the soma, over both scaling regions of the apical and basal trees. Given a uniformly excitable membrane, the electrotonic properties of dendritic arbors depend entirely upon mass distribution, and its relative contributions from dendritic branching and taper. By capturing each of these complex morphologic properties in a single, globally descriptive parameter, the new 3D scaling exponents introduced in this study permit efficient morphometric characterization of complex dendritic arbors in the fewest possible parameters, that can be directly related to their electrotonic properties, and hence to neuronal function.

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Year:  2005        PMID: 16083911     DOI: 10.1016/j.jtbi.2005.06.001

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  10 in total

Review 1.  Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse models.

Authors:  Jennifer I Luebke; Christina M Weaver; Anne B Rocher; Alfredo Rodriguez; Johanna L Crimins; Dara L Dickstein; Susan L Wearne; Patrick R Hof
Journal:  Brain Struct Funct       Date:  2010-02-24       Impact factor: 3.270

2.  The electrotonic structure of pyramidal neurons contributing to prefrontal cortical circuits in macaque monkeys is significantly altered in aging.

Authors:  Doron Kabaso; Patrick J Coskren; Bruce I Henry; Patrick R Hof; Susan L Wearne
Journal:  Cereb Cortex       Date:  2009-01-15       Impact factor: 5.357

3.  Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors.

Authors:  Quan Wen; Armen Stepanyants; Guy N Elston; Alexander Y Grosberg; Dmitri B Chklovskii
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-21       Impact factor: 11.205

Review 4.  Changes in the structural complexity of the aged brain.

Authors:  Dara L Dickstein; Doron Kabaso; Anne B Rocher; Jennifer I Luebke; Susan L Wearne; Patrick R Hof
Journal:  Aging Cell       Date:  2007-04-26       Impact factor: 9.304

5.  Trapping in and Escape from Branched Structures of Neuronal Dendrites.

Authors:  Robin Jose; Ludger Santen; M Reza Shaebani
Journal:  Biophys J       Date:  2018-10-04       Impact factor: 4.033

6.  Pyramidal cells in prefrontal cortex of primates: marked differences in neuronal structure among species.

Authors:  Guy N Elston; Ruth Benavides-Piccione; Alejandra Elston; Paul R Manger; Javier Defelipe
Journal:  Front Neuroanat       Date:  2011-02-10       Impact factor: 3.856

7.  Using Strahler's analysis to reduce up to 200-fold the run time of realistic neuron models.

Authors:  Addolorata Marasco; Alessandro Limongiello; Michele Migliore
Journal:  Sci Rep       Date:  2013-10-14       Impact factor: 4.379

8.  Brain-specific lipoprotein receptors interact with astrocyte derived apolipoprotein and mediate neuron-glia lipid shuttling.

Authors:  Jun Yin; Emma Spillman; Ethan S Cheng; Jacob Short; Yang Chen; Jingce Lei; Mary Gibbs; Justin S Rosenthal; Chengyu Sheng; Yuki X Chen; Kelly Veerasammy; Tenzin Choetso; Rinat Abzalimov; Bei Wang; Chun Han; Ye He; Quan Yuan
Journal:  Nat Commun       Date:  2021-04-23       Impact factor: 14.919

9.  Communication and wiring in the cortical connectome.

Authors:  Julian M L Budd; Zoltán F Kisvárday
Journal:  Front Neuroanat       Date:  2012-10-16       Impact factor: 3.856

10.  Neuronal firing sensitivity to morphologic and active membrane parameters.

Authors:  Christina M Weaver; Susan L Wearne
Journal:  PLoS Comput Biol       Date:  2007-12-13       Impact factor: 4.475

  10 in total

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