Literature DB >> 24028946

Visual sensory networks and effective information transfer in animal groups.

Ariana Strandburg-Peshkin1, Colin R Twomey, Nikolai W F Bode, Albert B Kao, Yael Katz, Christos C Ioannou, Sara B Rosenthal, Colin J Torney, Hai Shan Wu, Simon A Levin, Iain D Couzin.   

Abstract

Social transmission of information is vital for many group-living animals, allowing coordination of motion and effective response to complex environments. Revealing the interaction networks underlying information flow within these groups is a central challenge. Previous work has modeled interactions between individuals based directly on their relative spatial positions: each individual is considered to interact with all neighbors within a fixed distance (metric range), a fixed number of nearest neighbors (topological range), a 'shell' of near neighbors (Voronoi range), or some combination (Figure 1A). However, conclusive evidence to support these assumptions is lacking. Here, we employ a novel approach that considers individual movement decisions to be based explicitly on the sensory information available to the organism. In other words, we consider that while spatial relations do inform interactions between individuals, they do so indirectly, through individuals' detection of sensory cues. We reconstruct computationally the visual field of each individual throughout experiments designed to investigate information propagation within fish schools (golden shiners, Notemigonus crysoleucas). Explicitly considering visual sensing allows us to more accurately predict the propagation of behavioral change in these groups during leadership events. Furthermore, we find that structural properties of visual interaction networks differ markedly from those of metric and topological counterparts, suggesting that previous assumptions may not appropriately reflect information flow in animal groups.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 24028946      PMCID: PMC4780851          DOI: 10.1016/j.cub.2013.07.059

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  7 in total

1.  Effective leadership and decision-making in animal groups on the move.

Authors:  Iain D Couzin; Jens Krause; Nigel R Franks; Simon A Levin
Journal:  Nature       Date:  2005-02-03       Impact factor: 49.962

2.  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

Review 3.  Information transfer in moving animal groups.

Authors:  David Sumpter; Jerome Buhl; Dora Biro; Iain Couzin
Journal:  Theory Biosci       Date:  2008-05-06       Impact factor: 1.919

4.  Relevance of metric-free interactions in flocking phenomena.

Authors:  Francesco Ginelli; Hugues Chaté
Journal:  Phys Rev Lett       Date:  2010-10-13       Impact factor: 9.161

5.  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

6.  Can a minority of informed leaders determine the foraging movements of a fish shoal?

Authors: 
Journal:  Anim Behav       Date:  2000-02       Impact factor: 2.844

7.  Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Authors:  Richard P Mann; Andrea Perna; Daniel Strömbom; Roman Garnett; James E Herbert-Read; David J T Sumpter; Ashley J W Ward
Journal:  PLoS Comput Biol       Date:  2013-03-21       Impact factor: 4.475

  7 in total
  81 in total

1.  Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion.

Authors:  Sara Brin Rosenthal; Colin R Twomey; Andrew T Hartnett; Hai Shan Wu; Iain D Couzin
Journal:  Proc Natl Acad Sci U S A       Date:  2015-03-30       Impact factor: 11.205

2.  Weber's Law-based perception and the stability of animal groups.

Authors:  Andrea Perna; Giulio Facchini; Jean-Louis Deneubourg
Journal:  J R Soc Interface       Date:  2019-05-31       Impact factor: 4.118

3.  The socially mediated recovery of a fearful fish paired with periodically replaced calm models.

Authors:  Adam L Crane; Kevin R Bairos-Novak; Laurel H Sacco; Maud C O Ferrari
Journal:  Proc Biol Sci       Date:  2018-10-03       Impact factor: 5.349

4.  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

5.  Nonreciprocity as a generic route to traveling states.

Authors:  Zhihong You; Aparna Baskaran; M Cristina Marchetti
Journal:  Proc Natl Acad Sci U S A       Date:  2020-08-04       Impact factor: 11.205

Review 6.  Challenges and solutions for studying collective animal behaviour in the wild.

Authors:  Lacey F Hughey; Andrew M Hein; Ariana Strandburg-Peshkin; Frants H Jensen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-05-19       Impact factor: 6.237

Review 7.  Inferring influence and leadership in moving animal groups.

Authors:  Ariana Strandburg-Peshkin; Danai Papageorgiou; Margaret C Crofoot; Damien R Farine
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-05-19       Impact factor: 6.237

8.  Synchronization and collective swimming patterns in fish (Hemigrammus bleheri).

Authors:  I Ashraf; R Godoy-Diana; J Halloy; B Collignon; B Thiria
Journal:  J R Soc Interface       Date:  2016-10       Impact factor: 4.118

9.  The effects of flow on schooling Devario aequipinnatus: school structure, startle response and information transmission.

Authors:  A Chicoli; S Butail; Y Lun; J Bak-Coleman; S Coombs; D A Paley
Journal:  J Fish Biol       Date:  2014-05       Impact factor: 2.051

10.  idTracker: tracking individuals in a group by automatic identification of unmarked animals.

Authors:  Alfonso Pérez-Escudero; Julián Vicente-Page; Robert C Hinz; Sara Arganda; Gonzalo G de Polavieja
Journal:  Nat Methods       Date:  2014-06-01       Impact factor: 28.547

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