Temporal Processing by Caenorhabditis elegans Sensory Neurons

Abstract

Caenorhabditis elegans is a promising organism for trying to understand how nervous systems generate real-time behavior. Its low neuron count suggests that we may be able to observe all of the constituents of the computation of sophisticated sensorimotor behavior. However, its appropriateness as a system for quantitative dynamical study has yet to be established. We show that C. elegans chemosensory neurons can operate in a highly deterministic and low-noise mode, and they act as reliable linear filters of their input. We then use dynamical systems analysis in combination with classical genetic perturbation to uncover cellular and circuit mechanisms of temporal processing. This work should firmly establish C. elegans as a viable platform for applying quantitative dynamical systems methods to understanding how a nervous system processes sensory information, integrates it with an evolving internal state, and produces goal-directed, coordinated behavior

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