title: Computational Approach to Dendritic Spine Taxonomy and Shape Transition Analysis.
abstract: The common approach in morphological analysis of dendritic spines of mammalian neuronal cells is to categorize spines into subpopulations based on whether they are stubby, mushroom, thin, or filopodia shaped. The corresponding cellular models of synaptic plasticity, long-term potentiation, and long-term depression associate the synaptic strength with either spine enlargement or spine shrinkage. Although a variety of automatic spine segmentation and feature extraction methods were developed recently, no approaches allowing for an automatic and unbiased distinction between dendritic spine subpopulations and detailed computational models of spine behavior exist. We propose an automatic and statistically based method for the unsupervised construction of spine shape taxonomy based on arbitrary features. The taxonomy is then utilized in the newly introduced computational model of behavior, which relies on transitions between shapes. Models of different populations are compared using supplied bootstrap-based statistical tests. We compared two populations of spines at two time points. The first population was stimulated with long-term potentiation, and the other in the resting state was used as a control. The comparison of shape transition characteristics allowed us to identify the differences between population behaviors. Although some extreme changes were observed in the stimulated population, statistically significant differences were found only when whole models were compared. The source code of our software is freely available for non-commercial use.
  
  
  BACKGROUND
  d.plewczynski@cent.uw.edu.pl.
authors.affiliation: Centre of New Technologies, University of Warsaw Warsaw, Poland.
authors.forename: Grzegorz
authors.initials: G
authors.lastname: Bokota
authors.affiliation: Nencki Institute of Experimental Biology, Polish Academy of Sciences Warsaw, Poland.
authors.forename: Marta
authors.initials: M
authors.lastname: Magnowska
authors.affiliation: Department of Computer and Information Science, Norwegian University of Science and Technology Trondheim, Norway.
authors.forename: Tomasz
authors.initials: T
authors.lastname: Kuśmierczyk
authors.affiliation: Department of Computer Science, University of Sheffield Sheffield, UK.
authors.forename: Michał
authors.initials: M
authors.lastname: Łukasik
authors.affiliation: Nencki Institute of Experimental Biology, Polish Academy of Sciences Warsaw, Poland.
authors.forename: Matylda
authors.initials: M
authors.lastname: Roszkowska
authors.affiliation: Centre of New Technologies, University of WarsawWarsaw, Poland; Faculty of Pharmacy, Medical University of WarsawWarsaw, Poland.
authors.forename: Dariusz
authors.initials: D
authors.lastname: Plewczynski
keywords: dendritic spines; image processing; shape transitions; synaptic plasticity