Machine vision analysis of nematode behavioral patterns.

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DESCRIPTION (provided by applicant): The nematode C. elegans has powerful genetics, a well-described nervous system, and a near complete genome sequence; thus, it is well suited to analysis of behavior at the molecular and cellular levels. The ability to functionally map the influence of particular genes to specific behavioral consequences makes it possible to use genetic analysis to functionally dissect the molecular mechanisms underlying poorly understood aspects of nervous system function such as addiction. However, many genes with critical roles in neuronal function have effects on behavior that to a casual observer appear very subtle or difficult to describe precisely. Therefore, to fully realize the potential of C. elegans for the genetic analysis of nervous system functions, it is necessary to develop sophisticated methods for the rapid and consistent quantitation of behavioral phenotypes. The goal of this proposed work is to develop computer vision tools for quantitatively characterizing the behavioral patterns caused by mutations or pharmacological treatment in C. elegans. By making it possible to precisely characterize the behavioral phenotypes of uncoordinated, locomotion-abnormal mutants, these tools will be particularly useful for correlation specific neurotransmission defects with characteristic behavioral patterns. These analytical tools will also be used to precisely define the long-term effects of neuroactive drugs on behavioral, opening the possibility of genetic screening for mutants with defects in tolerance and dependence.