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3D morphology-based clustering and simulation of human pyramidal cell dendritic spines.

Authors :
Luengo-Sanchez, Sergio
Fernaud-Espinosa, Isabel
Bielza, Concha
Benavides-Piccione, Ruth
LarraƱaga, Pedro
DeFelipe, Javier
Source :
PLoS Computational Biology; 6/13/2018, Vol. 14 Issue 6, p1-22, 22p, 2 Color Photographs, 2 Diagrams, 2 Charts, 3 Graphs
Publication Year :
2018

Abstract

The dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex. They have a wide variety of morphologies, and their morphology appears to be critical from the functional point of view. To further characterize dendritic spine geometry, we used in this paper over 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons to group dendritic spines using model-based clustering. This approach uncovered six separate groups of human dendritic spines. To better understand the differences between these groups, the discriminative characteristics of each group were identified as a set of rules. Model-based clustering was also useful for simulating accurate 3D virtual representations of spines that matched the morphological definitions of each cluster. This mathematical approach could provide a useful tool for theoretical predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1553734X
Volume :
14
Issue :
6
Database :
Complementary Index
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
130135085
Full Text :
https://doi.org/10.1371/journal.pcbi.1006221