A stochastic neuronal model predicts random search behaviors at multiple spatial scales in C. elegans

William M Roberts,Steven B Augustine,Kristy J Lawton,Cornelia I Bargmann,Matthew Cale Britton,Serge Faumont,Shawn R Lockery,Eduardo J Izquierdo,Navin Pokala,Tod R Thiele,Rebecca A Lindsay,Theodore H Lindsay

doi:10.7554/elife.12572

Abstract

Random search is a behavioral strategy used by organisms from bacteria to humans to locate food that is randomly distributed and undetectable at a distance. We investigated this behavior in the nematode Caenorhabditis elegans, an organism with a small, well-described nervous system. Here we formulate a mathematical model of random search abstracted from the C. elegans connectome and fit to a large-scale kinematic analysis of C. elegans behavior at submicron resolution. The model predicts behavioral effects of neuronal ablations and genetic perturbations, as well as unexpected aspects of wild type behavior. The predictive success of the model indicates that random search in C. elegans can be understood in terms of a neuronal flip-flop circuit involving reciprocal inhibition between two populations of stochastic neurons. Our findings establish a unified theoretical framework for understanding C. elegans locomotion and a testable neuronal model of random search that can be applied to other organisms.

Highlights

Random search is an evolutionarily ancient set of foraging strategies that evolved as an adaptation to environments in which prey items are undetectable at a distance and occur at unpredictable locations
A neuronal model of random search in C. elegans is a theory of the relationship between activation states of the command neurons and foraging behavior
The Stochastic Switch Model is cast at a level of biological detail that is minimally sufficient to capture the stochastic dynamics of C. elegans locomotion in neuronal terms

Summary

Introduction

Random search is an evolutionarily ancient set of foraging strategies that evolved as an adaptation to environments in which prey items are undetectable at a distance and occur at unpredictable locations. Rather than attempting to exhaustively search a region of interest, the organism samples the environment at randomly selected points. This is achieved by executing a series of straight-line movements, called ’runs,’ terminated at random intervals by sampling episodes during which the organism may or may not find prey. In optimal random foraging strategies the probability distribution of run length is matched to the statistical distribution of isolated food patches or prey items (Viswanathan, 2011), with power law distributions predominating

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Conclusion