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Shared behavioral mechanisms underlie C. elegans aggregation and swarming

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Title: Shared behavioral mechanisms underlie C. elegans aggregation and swarming
Authors: Ding, SS
Schumacher, L
Javer, A
Endres, R
Brown, A
Item Type: Journal Article
Abstract: In complex biological systems, simple individual-level behavioral rules can give rise to emergent group-level behavior. While collective behavior has been well studied in cells and larger organisms, the mesoscopic scale is less understood, as it is unclear which sensory inputs and physical processes matter a priori. Here, we investigate collective feeding in the roundworm C. elegans at this intermediate scale, using quantitative phenotyping and agent-based modeling to identify behavioral rules underlying both aggregation and swarming—a dynamic phenotype only observed at longer timescales. Using fluorescence multi-worm tracking, we quantify aggregation in terms of individual dynamics and population-level statistics. Then we use agent-based simulations and approximate Bayesian inference to identify three key behavioral rules for aggregation: cluster-edge reversals, a density-dependent switch between crawling speeds, and taxis towards neighboring worms. Our simulations suggest that swarming is simply driven by local food depletion but otherwise employs the same behavioral mechanisms as the initial aggregation.
Issue Date: 25-Apr-2019
Date of Acceptance: 19-Apr-2019
URI: http://hdl.handle.net/10044/1/70267
DOI: https://dx.doi.org/10.7554/eLife.43318
ISSN: 2050-084X
Publisher: eLife Sciences Publications Ltd
Journal / Book Title: eLife
Volume: 8
Copyright Statement: © 2019, Ding et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited (https://creativecommons.org/licenses/by/4.0/)
Sponsor/Funder: Biotechnology and Biological Sciences Research Council (BBSRC)
Funder's Grant Number: BB/N00065X/1
Keywords: C. elegans
agent-based modeling
aggregation
animal tracking
collective behavior
physics of living systems
quantitative behavior
swarming
Publication Status: Published
Article Number: e43318
Appears in Collections:Clinical Sciences
Molecular Sciences
Faculty of Natural Sciences



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