title: Keeping track of worm trackers.
abstract: C. elegans is used extensively as a model system in the neurosciences due to its well defined nervous system. However, the seeming simplicity of this nervous system in anatomical structure and neuronal connectivity, at least compared to higher animals, underlies a rich diversity of behaviors. The usefulness of the worm in genome-wide mutagenesis or RNAi screens, where thousands of strains are assessed for phenotype, emphasizes the need for computational methods for automated parameterization of generated behaviors. In addition, behaviors can be modulated upon external cues like temperature, O(subscript)2(/subscript) and CO(subscript)2(/subscript) concentrations, mechanosensory and chemosensory inputs. Different machine vision tools have been developed to aid researchers in their efforts to inventory and characterize defined behavioral "outputs". Here we aim at providing an overview of different worm-tracking packages or video analysis tools designed to quantify different aspects of locomotion such as the occurrence of directional changes (turns, omega bends), curvature of the sinusoidal shape (amplitude, body bend angles) and velocity (speed, backward or forward movement).
authors: Katholieke Universiteit Leuven, Research group of Functional Genomics and Proteomics, Naamsestraat 59, B-3000 Leuven, Belgium.
authors: Steven J
authors: SJ
authors: Husson
authors: Wagner Steuer
authors: WS
authors: Costa
authors: Cornelia
authors: C
authors: Schmitt
authors: Alexander
authors: A
authors: Gottschalk
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000502:physiology*; D007091:Image Processing, Computer-Assisted; D008124:Locomotion / Q000502:physiology; D008853:Microscopy / Q000379:methods; D009040:Motion Pictures; D012984:Software