title: Information Flow through a Model of the C. elegans Klinotaxis Circuit.
abstract: Understanding how information about external stimuli is transformed into behavior is one of the central goals of neuroscience. Here we characterize the information flow through a complete sensorimotor circuit: from stimulus, to sensory neurons, to interneurons, to motor neurons, to muscles, to motion. Specifically, we apply a recently developed framework for quantifying information flow to a previously published ensemble of models of salt klinotaxis in the nematode worm Caenorhabditis elegans. Despite large variations in the neural parameters of individual circuits, we found that the overall information flow architecture circuit is remarkably consistent across the ensemble. This suggests structural connectivity is not necessarily predictive of effective connectivity. It also suggests information flow analysis captures general principles of operation for the klinotaxis circuit. In addition, information flow analysis reveals several key principles underlying how the models operate: (1) Interneuron class AIY is responsible for integrating information about positive and negative changes in concentration, and exhibits a strong left/right information asymmetry. (2) Gap junctions play a crucial role in the transfer of information responsible for the information symmetry observed in interneuron class AIZ. (3) Neck motor neuron class SMB implements an information gating mechanism that underlies the circuit's state-dependent response. (4) The neck carries more information about small changes in concentration than about large ones, and more information about positive changes in concentration than about negative ones. Thus, not all directions of movement are equally informative for the worm. Each of these findings corresponds to hypotheses that could potentially be tested in the worm. Knowing the results of these experiments would greatly refine our understanding of the neural circuit underlying klinotaxis.
authors.affiliation: Cognitive Science Program, Indiana University, Bloomington, Indiana, United States of America; School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America.
authors.forename: Eduardo J
authors.initials: EJ
authors.lastname: Izquierdo
authors.affiliation: Cognitive Science Program, Indiana University, Bloomington, Indiana, United States of America.
authors.forename: Paul L
authors.initials: PL
authors.lastname: Williams
authors.affiliation: Cognitive Science Program, Indiana University, Bloomington, Indiana, United States of America; School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America.
authors.forename: Randall D
authors.initials: RD
authors.lastname: Beer
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000502:physiology*; D002633:Chemotaxis; D017629:Gap Junctions / Q000502:physiology; D007395:Interneurons / Q000502:physiology; D008959:Models, Neurological; D009046:Motor Neurons / Q000502:physiology; D009415:Nerve Net / Q000502:physiology*; D009435:Synaptic Transmission