Universal features of dendrites through centripetal branch ordering

Dendrites form predominantly binary trees that are exquisitely embedded in the networks of the brain. While neuronal computation is known to depend on the morphology of dendrites, their underlying topological blueprint remains unknown. Here, we used a centripetal branch ordering scheme originally de...

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Bibliographic Details
Published in:PLoS computational biology 2017-07, Vol.13 (7), p.e1005615-e1005615
Main Authors: Vormberg, Alexandra, Effenberger, Felix, Muellerleile, Julia, Cuntz, Hermann
Format: Article
Language:English
Subjects:
Animals
Biology and Life Sciences
Brain
Computer Simulation
Cooperation
Dendrites
Dendrites - ultrastructure
Dendritic branching
Dendritic structure
Humans
Insects
Mathematical morphology
Models, Anatomic
Models, Neurological
Models, Statistical
Morphogenesis
Morphology
Neuronal Plasticity
Neurons
Neurosciences
Physiological aspects
River networks
Rivers
Society
Software
Studies
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Summary:Dendrites form predominantly binary trees that are exquisitely embedded in the networks of the brain. While neuronal computation is known to depend on the morphology of dendrites, their underlying topological blueprint remains unknown. Here, we used a centripetal branch ordering scheme originally developed to describe river networks-the Horton-Strahler order (SO)-to examine hierarchical relationships of branching statistics in reconstructed and model dendritic trees. We report on a number of universal topological relationships with SO that are true for all binary trees and distinguish those from SO-sorted metric measures that appear to be cell type-specific. The latter are therefore potential new candidates for categorising dendritic tree structures. Interestingly, we find a faithful correlation of branch diameters with centripetal branch orders, indicating a possible functional importance of SO for dendritic morphology and growth. Also, simulated local voltage responses to synaptic inputs are strongly correlated with SO. In summary, our study identifies important SO-dependent measures in dendritic morphology that are relevant for neural function while at the same time it describes other relationships that are universal for all dendrites.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1005615