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

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 pap...

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Bibliographic Details
Published in:PLoS computational biology 2018-06, Vol.14 (6), p.e1006221-e1006221
Main Authors: Luengo-Sanchez, Sergio, Fernaud-Espinosa, Isabel, Bielza, Concha, Benavides-Piccione, Ruth, Larrañaga, Pedro, DeFelipe, Javier
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Biology and Life Sciences
CAD
Cerebral cortex
Cerebral Cortex - cytology
Cluster Analysis
Clustering
Computer aided design
Computer graphics
Computer Simulation
Cytology
Dendrites - physiology
Dendritic cells
Dendritic spines
Dendritic Spines - physiology
Dendritic structure
Discriminant analysis
Geometry
Humans
Imaging, Three-Dimensional - methods
International conferences
Mathematical morphology
Mathematics
Microscopy
Morphology
Neurons
Physical Sciences
Physiological aspects
Pyramidal cells
Pyramidal Cells - physiology
Research and Analysis Methods
Software
Spine
Studies
Supervision
Synapses
Synapses - physiology
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Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1006221