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

PLoS Comput Biol. 2018 Jun 13;14(6):e1006221. doi: 10.1371/journal.pcbi.1006221. eCollection 2018 Jun.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cerebral Cortex / cytology
  • Cluster Analysis
  • Computer Simulation
  • Dendrites / physiology
  • Dendritic Spines / physiology*
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Pyramidal Cells / physiology*
  • Synapses / physiology

Grant support

This work has been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness through the Cajal Blue Brain (C080020-09; the Spanish partner of the Blue Brain initiative from EPFL) and TIN2016-79684-P projects, and by the Regional Government of Madrid through the S2013/ICE-2845-CASI-CAM-CM project. This project has received funding from the European Union`s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 720270 (HBP SGA1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.