A computational model of associative learning and chemotaxis in the nematode worm C. elegans

A computational model of associative learning and chemotaxis in the nematode worm C. elegans
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  ORAL PRESENTATION Open Access A computational model of associative learningand chemotaxis in the nematode worm C. elegans Peter A Appleby, Netta Cohen * From  Nineteenth Annual Computational Neuroscience Meeting: CNS*2010San Antonio, TX, USA. 24-30 July 2010 The nematode worm  C. elegans  is an exciting modelsystem for experimentalists and modelers alike. It has arelatively small nervous system, made up of just 302neurons in the adult hermaphrodite, that has beenmapped in detail using serial section electron micro-scopy. Despite the simplicity of its nervous system  C.elegans  displays a range of interesting behaviors. Thisincludes thermo- and chemotaxis and the modulation of locomotion strategies in response to the presence of food. In chemotaxis  C. elegans  will move up or down achemical gradient dependent on whether the chemicalacts as an attractant or repellent. It does this in two dis-tinct ways, first by gradually steering left or right untilthe worm points up or down the gradient and secondby modulating the probability of initiating a sharp seriesof turns (known as a piroeutte) along with the finalorientation of the worm after the pirouette has finished.Experimental work has shown that the chemotaxisresponse is dynamic and that the degree of influence aparticular chemical has on navigation can be changed,or even reversed depending on experience. Changes arereversible, specific to the chemical in question, and canbe generated by classical conditioning experiments. Allof these are hallmarks of associative learning, a sophisti-cated process that requires integration of multiple sig-nals to produce a coordinated change in a behavioralresponse.Despite the wealth of experimental data on learningin chemotaxis in  C. elegans , comparatively little isknown about how the known circuitry of   C. elegans carries out the computations that underlie it. Even lessis known about how that circuitry changes duringassociative learning. Here, we focus on the worm ’ schemotaxis and the ability of   C. elegans  to learn asso-ciations between salt (NaCl) concentrations and food.We draw upon existing experimental data from a vari-ety of sources including electrophysiological and anato-mical data to construct a simplified NaCl chemotaxiscircuit in  C. elegans . This circuit consists of the leftand right ASE amphid sensory neurons, whichcomprise the dominant NaCl sensation pathway in C. elegans , eight pairs of interneurons, and ten headmotor neurons. Where possible the properties of indi- vidual neurons are constrained by electrophysiologicaland calcium imaging data.We next define a set of experimentally observed beha- viors we wish to reproduce, including gentle turning,modulation of pirouette frequency, control of finalorientation following a pirouette, and associative learn-ing. In particular, we are interested in the alteration inbehavioral response to NaCl that arises due to the pair-ing of high concentrations of NaCl with food or starva-tion. We use this to derive a family of model networkswith specific synaptic polarities, time scales of neuronalresponses, and intrinsic neuronal properties that havethe capacity to generate the specified set of behaviors.We implement one of these models and record thebehaviour of model worms that are placed in a variety of simulated environments. We observe qualitatively realistic chemotaxis behavior and adaptation anddemonstrate that our model is robust and tolerant tonoise.Our proposed chemotaxis circuit leads to a number of distinct predictions that could be used to test the modelexperimentally. This includes postulating the computa-tional role of each neuron in the network and the locusand nature of the plasticity underpinning the * Correspondence: School of Computing, University of Leeds, Leeds LS2 9JT, UK  Appleby and Cohen  BMC Neuroscience  2010,  11 (Suppl 1):O8 © 2010 Cohen and Appleby; licensee BioMed Central Ltd.  experimentally observed associative learning. Our modelalso suggests that this plasticity be expressed not by changes in synaptic strength but by changes in the sen-sory neurons themselves. Thus, contrary to the prevail-ing view in the  C. elegans  community, plasticity in ourmodel of chemotaxis is expressed at a neuronal ratherthan synaptic level. C. elegans  offers a unique opportunity to push theboundaries of systems neuroscience. The ability tomodel a neuronal circuit in such detail is a remarkableopportunity to study associative learning in an animaldisplaying a sophisticated set of behaviors and nontriviallearning. A biologically grounded model of behavior andlearning in  C. elegans  has great potential to offerdetailed and integrated understanding of sensory proces-sing, synaptic plasticity and associative learning. Lessonslearned from such models can be applied to other sen-sory and sensorimotor modalities in the worm with theeventual goal of producing an integrated model of theworm ’ s sensorimotor system. We believe that theoreticalinsights gained from this endeavour will be invaluable inour study of larger, more complex nervous systems. Published: 20 July 2010 doi:10.1186/1471-2202-11-S1-O8 Cite this article as:  Appleby and Cohen:  A computational model of associative learning and chemotaxis in the nematode worm  C. elegans . BMC Neuroscience  2010  11 (Suppl 1):O8. Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistribution Submit your manuscript at Appleby and Cohen  BMC Neuroscience  2010,  11 (Suppl 1):O8 2 of 2
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