title: A percolation approach to neural morphometry and connectivity.
abstract: This article addresses the issues of neural shape characterization and analysis from the perspective of one of the main roles played by neural shapes, namely, connectivity. This study is oriented toward the geometry at the individual cell level and involves the use of the percolation concept from statistical mechanics, which is reviewed in an accessible fashion. The characterization of the neural cell geometry with respect to connectivity is performed in terms of critical percolation probability obtained experimentally while considering several types of geometrical interactions between cells, therefore directly expressing the potential for connections defined by each situation. Two basic situations are considered: dendrite-dendrite and dendrite-axon interactions. The obtained results corroborate the potential of the critical percolation probability as a valuable resource for characterizing, classifying, and analyzing the morphology of neural cells.
authors.affiliation: Cybernetic Vision Research Group, IFSC-USP, Caixa Postal 369, 13560-970, São Carlos, SP, Brazil. luciano@if.sc.usp.br
authors.forename: Luciano da Fontoura
authors.initials: Lda F
authors.lastname: Costa
authors.forename: Edson Tadeu Monteiro
authors.initials: ET
authors.lastname: Manoel
mesh_terms: D000465:Algorithms; D001369:Axons / Q000502:physiology / Q000648:ultrastructure; D008959:Models, Neurological; D016501:Neurites / Q000502:physiology / Q000648:ultrastructure; D009474:Neurons / Q000502:physiology* / Q000648:ultrastructure*; D013569:Synapses / Q000502:physiology