Shared behavioral mechanisms underlie C. elegans aggregation and swarming

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...
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Autor*in:	Siyu Serena Ding [verfasserIn] Linus J Schumacher [verfasserIn] Avelino E Javer [verfasserIn] Robert G Endres [verfasserIn] André EX Brown [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	quantitative behavior collective behavior animal tracking agent-based modeling aggregation swarming

Übergeordnetes Werk:	In: eLife - eLife Sciences Publications Ltd, 2013, 8(2019)
Übergeordnetes Werk:	volume:8 ; year:2019

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.7554/eLife.43318

Katalog-ID:	DOAJ084209763

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allfields	10.7554/eLife.43318 doi (DE-627)DOAJ084209763 (DE-599)DOAJ09565fa0cb5a4d108a896d266fbaf27a DE-627 ger DE-627 rakwb eng QH301-705.5 Siyu Serena Ding verfasserin aut Shared behavioral mechanisms underlie C. elegans aggregation and swarming 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. quantitative behavior collective behavior animal tracking agent-based modeling aggregation swarming Medicine R Science Q Biology (General) Linus J Schumacher verfasserin aut Avelino E Javer verfasserin aut Robert G Endres verfasserin aut André EX Brown verfasserin aut In eLife eLife Sciences Publications Ltd, 2013 8(2019) (DE-627)728518384 (DE-600)2687154-3 2050084X nnns volume:8 year:2019 https://doi.org/10.7554/eLife.43318 kostenfrei https://doaj.org/article/09565fa0cb5a4d108a896d266fbaf27a kostenfrei https://elifesciences.org/articles/43318 kostenfrei https://doaj.org/toc/2050-084X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2019
spelling	10.7554/eLife.43318 doi (DE-627)DOAJ084209763 (DE-599)DOAJ09565fa0cb5a4d108a896d266fbaf27a DE-627 ger DE-627 rakwb eng QH301-705.5 Siyu Serena Ding verfasserin aut Shared behavioral mechanisms underlie C. elegans aggregation and swarming 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. quantitative behavior collective behavior animal tracking agent-based modeling aggregation swarming Medicine R Science Q Biology (General) Linus J Schumacher verfasserin aut Avelino E Javer verfasserin aut Robert G Endres verfasserin aut André EX Brown verfasserin aut In eLife eLife Sciences Publications Ltd, 2013 8(2019) (DE-627)728518384 (DE-600)2687154-3 2050084X nnns volume:8 year:2019 https://doi.org/10.7554/eLife.43318 kostenfrei https://doaj.org/article/09565fa0cb5a4d108a896d266fbaf27a kostenfrei https://elifesciences.org/articles/43318 kostenfrei https://doaj.org/toc/2050-084X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2019
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allfieldsGer	10.7554/eLife.43318 doi (DE-627)DOAJ084209763 (DE-599)DOAJ09565fa0cb5a4d108a896d266fbaf27a DE-627 ger DE-627 rakwb eng QH301-705.5 Siyu Serena Ding verfasserin aut Shared behavioral mechanisms underlie C. elegans aggregation and swarming 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. quantitative behavior collective behavior animal tracking agent-based modeling aggregation swarming Medicine R Science Q Biology (General) Linus J Schumacher verfasserin aut Avelino E Javer verfasserin aut Robert G Endres verfasserin aut André EX Brown verfasserin aut In eLife eLife Sciences Publications Ltd, 2013 8(2019) (DE-627)728518384 (DE-600)2687154-3 2050084X nnns volume:8 year:2019 https://doi.org/10.7554/eLife.43318 kostenfrei https://doaj.org/article/09565fa0cb5a4d108a896d266fbaf27a kostenfrei https://elifesciences.org/articles/43318 kostenfrei https://doaj.org/toc/2050-084X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2019
allfieldsSound	10.7554/eLife.43318 doi (DE-627)DOAJ084209763 (DE-599)DOAJ09565fa0cb5a4d108a896d266fbaf27a DE-627 ger DE-627 rakwb eng QH301-705.5 Siyu Serena Ding verfasserin aut Shared behavioral mechanisms underlie C. elegans aggregation and swarming 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. quantitative behavior collective behavior animal tracking agent-based modeling aggregation swarming Medicine R Science Q Biology (General) Linus J Schumacher verfasserin aut Avelino E Javer verfasserin aut Robert G Endres verfasserin aut André EX Brown verfasserin aut In eLife eLife Sciences Publications Ltd, 2013 8(2019) (DE-627)728518384 (DE-600)2687154-3 2050084X nnns volume:8 year:2019 https://doi.org/10.7554/eLife.43318 kostenfrei https://doaj.org/article/09565fa0cb5a4d108a896d266fbaf27a kostenfrei https://elifesciences.org/articles/43318 kostenfrei https://doaj.org/toc/2050-084X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2019
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author	Siyu Serena Ding
spellingShingle	Siyu Serena Ding misc QH301-705.5 misc quantitative behavior misc collective behavior misc animal tracking misc agent-based modeling misc aggregation misc swarming misc Medicine misc R misc Science misc Q misc Biology (General) Shared behavioral mechanisms underlie C. elegans aggregation and swarming
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topic_title	QH301-705.5 Shared behavioral mechanisms underlie C. elegans aggregation and swarming quantitative behavior collective behavior animal tracking agent-based modeling aggregation swarming
topic	misc QH301-705.5 misc quantitative behavior misc collective behavior misc animal tracking misc agent-based modeling misc aggregation misc swarming misc Medicine misc R misc Science misc Q misc Biology (General)
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title	Shared behavioral mechanisms underlie C. elegans aggregation and swarming
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title_full	Shared behavioral mechanisms underlie C. elegans aggregation and swarming
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title_sort	shared behavioral mechanisms underlie c. elegans aggregation and swarming
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title_auth	Shared behavioral mechanisms underlie C. elegans aggregation and swarming
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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Shared behavioral mechanisms underlie C. elegans aggregation and swarming
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Shared behavioral mechanisms underlie C. elegans aggregation and swarming

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