AI Article Synopsis

  • In complex biological systems, simple behaviors at the individual level can lead to complex group behaviors, but the mesoscopic scale is not well understood.
  • This study focuses on collective feeding in roundworms, utilizing quantitative phenotyping and agent-based modeling to uncover the behavioral rules that promote aggregation and swarming behaviors.
  • The research identifies three key rules for aggregation: changes in movement direction at cluster edges, a switch in crawling speed based on population density, and attraction to nearby worms, suggesting swarming evolves from local food shortages while using similar mechanisms as aggregation.

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 . Here, we investigate collective feeding in the roundworm 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522220PMC
http://dx.doi.org/10.7554/eLife.43318DOI Listing

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