Data from: Maximally informative foraging by Caenorhabditis elegans
Data files
Nov 28, 2015 version files 5.74 MB
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infotaxis.m
9.06 KB
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trajectory_individual.m
3.16 KB
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Wormdata.xlsx
5.73 MB
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.