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

by Sergio Luengo-Sanchez, Isabel Fernaud-Espinosa, Concha Bielza, Ruth Benavides-Piccione, Pedro Larra ñaga, Javier DeFelipe

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 p aper 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 discrimin ative 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 theoretica l predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines.

Source: PLoS Computational Biology - June 13, 2018 Category: Biology Authors: Sergio Luengo-Sanchez Source Type: research