Literature DB >> 20826476

Limited interactions in flocks: relating model simulations to empirical data.

Nikolai W F Bode1, Daniel W Franks, A Jamie Wood.   

Abstract

The mechanism of self-organization resulting in coordinated collective motion has received wide attention from a range of scientists interested in both its technical and biological relevance. Models have been highly influential in highlighting how collective motion can be produced from purely local interactions between individuals. Typical models in this field are termed 'metric' because each individual only reacts to conspecifics within a fixed distance. A recent large-scale study has, however, provided evidence that interactions ruling collective behaviour occur between a fixed number of nearest neighbours ('topological' framework). Despite their importance in clarifying the nature of the mechanism underlying animal interactions, these findings have yet to be produced by either metric or topological models. Here, we present an original individual-based model of collective animal motion that reproduces the previous findings. Our approach bridges the current gap between previous model analysis and recent evidence, and presents a framework for further study.

Mesh:

Year:  2010        PMID: 20826476      PMCID: PMC3033030          DOI: 10.1098/rsif.2010.0397

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  12 in total

1.  Novel type of phase transition in a system of self-driven particles.

Authors: 
Journal:  Phys Rev Lett       Date:  1995-08-07       Impact factor: 9.161

2.  Simulating dynamical features of escape panic.

Authors:  D Helbing; I Farkas; T Vicsek
Journal:  Nature       Date:  2000-09-28       Impact factor: 49.962

3.  Onset of collective and cohesive motion.

Authors:  Guillaume Grégoire; Hugues Chaté
Journal:  Phys Rev Lett       Date:  2004-01-15       Impact factor: 9.161

4.  How perceived threat increases synchronization in collectively moving animal groups.

Authors:  Nikolai W F Bode; Jolyon J Faria; Daniel W Franks; Jens Krause; A Jamie Wood
Journal:  Proc Biol Sci       Date:  2010-05-26       Impact factor: 5.349

5.  Flocking regimes in a simple lattice model.

Authors:  J R Raymond; M R Evans
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2006-03-08

6.  Collective memory and spatial sorting in animal groups.

Authors:  Iain D Couzin; Jens Krause; Richard James; Graeme D Ruxton; Nigel R Franks
Journal:  J Theor Biol       Date:  2002-09-07       Impact factor: 2.691

7.  Interaction ruling animal collective behavior depends on topological rather than metric distance: evidence from a field study.

Authors:  M Ballerini; N Cabibbo; R Candelier; A Cavagna; E Cisbani; I Giardina; V Lecomte; A Orlandi; G Parisi; A Procaccini; M Viale; V Zdravkovic
Journal:  Proc Natl Acad Sci U S A       Date:  2008-01-28       Impact factor: 11.205

8.  Scale-free correlations in starling flocks.

Authors:  Andrea Cavagna; Alessio Cimarelli; Irene Giardina; Giorgio Parisi; Raffaele Santagati; Fabio Stefanini; Massimiliano Viale
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-14       Impact factor: 11.205

9.  From disorder to order in marching locusts.

Authors:  J Buhl; D J T Sumpter; I D Couzin; J J Hale; E Despland; E R Miller; S J Simpson
Journal:  Science       Date:  2006-06-02       Impact factor: 47.728

Review 10.  The principles of collective animal behaviour.

Authors:  D J T Sumpter
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-01-29       Impact factor: 6.237

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  34 in total

1.  Inferring the rules of interaction of shoaling fish.

Authors:  James E Herbert-Read; Andrea Perna; Richard P Mann; Timothy M Schaerf; David J T Sumpter; Ashley J W Ward
Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-07       Impact factor: 11.205

2.  Spatially balanced topological interaction grants optimal cohesion in flocking models.

Authors:  Marcelo Camperi; Andrea Cavagna; Irene Giardina; Giorgio Parisi; Edmondo Silvestri
Journal:  Interface Focus       Date:  2012-08-08       Impact factor: 3.906

Review 3.  From behavioural analyses to models of collective motion in fish schools.

Authors:  Ugo Lopez; Jacques Gautrais; Iain D Couzin; Guy Theraulaz
Journal:  Interface Focus       Date:  2012-10-03       Impact factor: 3.906

4.  Ontogeny of collective behavior reveals a simple attraction rule.

Authors:  Robert C Hinz; Gonzalo G de Polavieja
Journal:  Proc Natl Acad Sci U S A       Date:  2017-02-13       Impact factor: 11.205

5.  Obstacle avoidance in social groups: new insights from asynchronous models.

Authors:  Simon Croft; Richard Budgey; Jonathan W Pitchford; A Jamie Wood
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

6.  Motion-guided attention promotes adaptive communications during social navigation.

Authors:  B H Lemasson; J J Anderson; R A Goodwin
Journal:  Proc Biol Sci       Date:  2013-01-16       Impact factor: 5.349

7.  A unifying framework for quantifying the nature of animal interactions.

Authors:  Jonathan R Potts; Karl Mokross; Mark A Lewis
Journal:  J R Soc Interface       Date:  2014-07-06       Impact factor: 4.118

8.  Modeling active sensing reveals echo detection even in large groups of bats.

Authors:  Thejasvi Beleyur; Holger R Goerlitz
Journal:  Proc Natl Acad Sci U S A       Date:  2019-12-10       Impact factor: 11.205

9.  Local interactions and their group-level consequences in flocking jackdaws.

Authors:  Hangjian Ling; Guillam E Mclvor; Kasper van der Vaart; Richard T Vaughan; Alex Thornton; Nicholas T Ouellette
Journal:  Proc Biol Sci       Date:  2019-07-03       Impact factor: 5.349

10.  Computational and robotic modeling reveal parsimonious combinations of interactions between individuals in schooling fish.

Authors:  Liu Lei; Ramón Escobedo; Clément Sire; Guy Theraulaz
Journal:  PLoS Comput Biol       Date:  2020-03-16       Impact factor: 4.475

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