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

The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic ar...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2009-07, Vol.106 (30), p.12536-12541
Main Authors: Wen, Quan, Stepanyants, Armen, Elston, Guy N, Grosberg, Alexander Y, Chklovskii, Dmitri B
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Algorithms
Animals
Axons
Axons - physiology
Biological Sciences
Brain
Branches
Cells
Connectivity
Datasets
Dendrites
Dendrites - physiology
Entropy
Haplorhini
Mammals
Models, Neurological
Neural Pathways - physiology
Neurons
Neuroscience
Purkinje cells
Purkinje Cells - cytology
Purkinje Cells - physiology
Pyramidal cells
Pyramidal Cells - cytology
Pyramidal Cells - physiology
Rats
Synapses
Synapses - physiology
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Summary:The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.0901530106