title: Maximally informative foraging by Caenorhabditis elegans.
abstract: Animals have evolved intricate search strategies to find new sources of food. Here, we analyze a complex food seeking behavior in the nematode Caenorhabditis elegans (C. elegans) to derive a general theory describing different searches. We show that C. elegans, like many other animals, uses a multi-stage search for food, where they initially explore a small area intensively ('local search') before switching to explore a much larger area ('global search'). We demonstrate that these search strategies as well as the transition between them can be quantitatively explained by a maximally informative search strategy, where the searcher seeks to continuously maximize information about the target. Although performing maximally informative search is computationally demanding, we show that a drift-diffusion model can approximate it successfully with just three neurons. Our study reveals how the maximally informative search strategy can be implemented and adopted to different search conditions.
authors.affiliation: Neurosciences Graduate Program, University of California, San Diego, La Jolla, United States.
authors.forename: Adam J
authors.initials: AJ
authors.lastname: Calhoun
authors.affiliation: Neurosciences Graduate Program, University of California, San Diego, La Jolla, United States.
authors.forename: Sreekanth H
authors.initials: SH
authors.lastname: Chalasani
authors.affiliation: Neurosciences Graduate Program, University of California, San Diego, La Jolla, United States.
authors.forename: Tatyana O
authors.initials: TO
authors.lastname: Sharpee
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000502:physiology*; D002633:Chemotaxis; D005247:Feeding Behavior; D008954:Models, Biological
keywords: C. elegans; decision making; drift-diffusion model; information theory; neuroscience