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Inferring the structure and dynamics of interactions in schooling fish
Open accessAbstract
Determining individual-level interactions that govern highly coordinated motion in animal groups or cellular aggregates has been a long-standing challenge, central to understanding the mechanisms and evolution of collective behavior. Numerous models have been proposed, many of which display realistic-looking dynamics, but nonetheless rely on untested assumptions about how individuals integrate information to guide movement. Here we infer behavioral rules directly from experimental data. We begin by analyzing trajectories of golden shiners (Notemigonus crysoleucas) swimming in two-fish and three-fish shoals to map the mean effective forces as a function of fish positions and velocities. Speeding and turning responses are dynamically modulated and clearly delineated. Speed regulation is a dominant component of how fish interact, and changes in speed are transmitted to those both behind and ahead. Alignment emerges from attraction and repulsion, and fish tend to copy directional changes made by those ahead. We find no evidence for explicit matching of body orientation. By comparing data from two-fish and three-fish shoals, we challenge the standard assumption, ubiquitous in physics-inspired models of collective behavior, that individual motion results from averaging responses to each neighbor considered separately; three-body interactions make a substantial contribution to fish dynamics. However, pairwise interactions qualitatively capture the correct spatial interaction structure in small groups, and this structure persists in larger groups of 10 and 30 fish. The interactions revealed here may help account for the rapid changes in speed and direction that enable real animal groups to stay cohesive and amplify important social information.
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“This knowledge can then be used to infer individual decision rules in collective motion (Katz, Tunstrom, Ioannou, Huepe, & Couzin, 2011;Nagy, Kos, Biro, & Vicsek, 2010) and to compute activity budgets for individuals without the need for continuous human observation or time-consuming video analysis.”
From Applications of machine learning in animal behaviour studies (2017) · cites this paper as Katz et al., 2011
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Cites
Flocks, herds and schools: A distributed behavioral model
Reynolds, C. W. (1987) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/37401.37406 · Cited by 7,954
Novel Type of Phase Transition in a System of Self-Driven Particles
Vicsek, T., Czirók, A., Ben‐Jacob, E., Cohen, I., & Shochet, O. (1995) · Physical Review Letters · doi:10.1103/physrevlett.75.1226 · Cited by 7,395
Social force model for pedestrian dynamics.
Helbing, D., & Molnár, P. (1995) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.51.4282 · Cited by 7,299
Flocks, herds and schools: A distributed behavioral model
Reynolds, C. W. (1987) · ACM SIGGRAPH Computer Graphics · doi:10.1145/37402.37406 · Cited by 5,148
Collective Memory and Spatial Sorting in Animal Groups
Couzin, I. D., Krause, J., JAMES, R., Ruxton, G. D., & Franks, N. R. (2002) · Journal of Theoretical Biology · doi:10.1006/jtbi.2002.3065 · Cited by 2,141
Ballerini, M., Cabibbo, N., Candelier, R., Cavagna, A., Cisbani, E., Giardina, I., Lecomte, V., Orlandi, A., Giorgio Parisi, A., Procaccini, A., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0711437105 · Cited by 1,978
Lecture notes in control and information sciences
Aplevich, J. D. (1991) · Springer eBooks · Cited by 1,832
Felipe Cucker, B., & Smale, S. (2007) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2007.895842 · Cited by 1,786
Weak pairwise correlations imply strongly correlated network states in a neural population
Schneidman, E., Berry, M. J., Segev, R., & Bialek, W. (2006) · Nature · doi:10.1038/nature04701 · Cited by 1,745
Feature point tracking and trajectory analysis for video imaging in cell biology
Sbalzarini, I. F., & Koumoutsakos, P. (2005) · Journal of Structural Biology · doi:10.1016/j.jsb.2005.06.002 · Cited by 1,403
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Ling, H., McIvor, G. E., Westley, J., van der Vaart, K., Vaughan, R., Thornton, A., & Ouellette, N. T. (2019) · Nature Communications · doi:10.1038/s41467-019-13281-4 · Cited by 77
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“Rotational or vortex motion is exceptionally widespread in nature, ranging from quantum Abrikosov vortices in type II superconductors (19, 20) over animal flocks (21, 22) and atmospheric cyclones (23) to galactic-scale astrophysical flows (24).”
BackgroundContrarians Synchronize beyond the Limit of Pairwise Interactions
Kovalenko, K., Dai, X., Alfaro-Bittner, K., Raigorodskii, A. M., Perc, M., & Boccaletti, S. (2021) · Physical Review Letters · doi:10.1103/physrevlett.127.258301 · Cited by 77
“Swarming in three dimensions [45], in particular where making swift decisions plays a key role even if not involving humans, such as in fish schools or murmurations under predation [46, 47], might also benefit from the insights reported in our research.”
ResultLong-range acoustic interactions in insect swarms: an adaptive gravity model
Gorbonos, D., Ianconescu, R., Puckett, J. G., Ni, R., Ouellette, N. T., & Gov, N. S. (2016) · New Journal of Physics · doi:10.1088/1367-2630/18/7/073042 · Cited by 76
The dynamics of audience applause
Mann, R. P., Faria, J. J., Sumpter, D. J. T., & Krause, J. (2013) · Journal of The Royal Society Interface · doi:10.1098/rsif.2013.0466 · Cited by 78
“Unlike studies focused on visual information, where local transmission of information is between local neighbours [18–20], we find in our experiments that spatial proximity is not important.”
BackgroundChemically Controlled Spatiotemporal Oscillations of Colloidal Assemblies
Altemose, A., Sánchez‐Farrán, M. A., Duan, W., Schulz, S., Borhan, A., Crespi, V. H., & Sen, A. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201703239 · Cited by 76
Lei, L., Escobedo, R., Sire, C., & Theraulaz, G. (2020) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1007194 · Cited by 75
“[29] have shown that the combined effect of two neighbors on a fish response 88 is close to averaging for turning, but somewhere between averaging and adding for speed 89 adjustments.”
BackgroundTracking and Following a Tagged Leopard Shark with an Autonomous Underwater Vehicle
Clark, C., Forney, C., Manii, E., Shinzaki, D., Gage, C., Farris, M., Lowe, C. G., & Moline, M. A. (2013) · Journal of Field Robotics · doi:10.1002/rob.21450 · Cited by 75
“Other particle models assume an individual follows simple kinematic equations that are affected by the state of its local neighbors (Hensor et al., 2005; Huse et al., 2002; Katz et al., 2011).”
BackgroundActive Brownian particles with velocity-alignment and active fluctuations
Großmann, R., Schimansky-Geier, L., & Romańczuk, P. (2012) · New Journal of Physics · doi:10.1088/1367-2630/14/7/073033 · Cited by 74
“The functional form of Fi and ηi can be set using reasonable modelling assumptions based on qualitative empirical observations [1, 10] or, if available, directly on experimental measurements of interactions between individuals [20–22].”
Jolles, J. W., Laskowski, K. L., Boogert, N. J., & Manica, A. (2018) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2017.2629 · Cited by 71
“Considerable computational [1–3] and experimental work [4–6] has shown that the seemingly complex collective behaviour of animal groups can often be explained by relatively simple interaction rules [3,5,6].”
BackgroundDynamical maximum entropy approach to flocking
Cavagna, A., Giardina, I., Ginelli, F., Mora, T., Piovani, D., Tavarone, R., & Walczak, A. M. (2014) · Physical Review E · doi:10.1103/physreve.89.042707 · Cited by 73
From the origin of life to pandemics: emergent phenomena in complex systems
Artime, O., & Domenico, M. D. (2022) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0410 · Cited by 80
The emergence and development of behavioral individuality in clonal fish
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Collective motion in biological systems
Deutsch, A., Guy Theraulaz, A., & Vicsek, T. (2012) · Interface Focus · doi:10.1098/rsfs.2012.0048 · Cited by 71
Rieucau, G., Kiszka, J. J., Castillo, J. C., Mourier, J., Boswell, K. M., & Heithaus, M. R. (2018) · Journal of Fish Biology · doi:10.1111/jfb.13645 · Cited by 71
“There is a growing body of evidence supporting the idea that collective responses yield a significant adaptive advantage, for instance, as they facilitate information transfer through the group (Handegard et al., 2012; Katz et al., 2011; Marras et al., 2012; Rieucau et al., 2014, 2016bb; Rosenthal et al., 2015; Treher…”
BackgroundVision in two cyprinid fish: implications for collective behavior
Pita, D., Moore, B. A., Tyrrell, L. P., & Fernández‐Juricic, E. (2015) · PeerJ · doi:10.7717/peerj.1113 · Cited by 71
Torney, C. J., Hopcraft, J. G. C., Morrison, T. A., Couzin, I. D., & Levin, S. A. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0012 · Cited by 70
Farine, D. R., Strandburg‐Peshkin, A., Berger-Wolf, T. Y., Ziebart, B. D., Brugere, I., Li, J., & Crofoot, M. C. (2016) · Scientific Reports · doi:10.1038/srep27704 · Cited by 65
Precise visuomotor transformations underlying collective behavior in larval zebrafish
Harpaz, R., Nguyen, M. N., Bahl, A., & Engert, F. (2021) · Nature Communications · doi:10.1038/s41467-021-26748-0 · Cited by 63
“Future experiments using VR assays as we used here, can specifically test if older larvae or juvenile fish are capable of detecting and responding to neighbors’ body orientation and motion or if they are largely agnostic to it (22, 23, 25, 26, 68).”
MethodInitiative, Personality and Leadership in Pairs of Foraging Fish
Nakayama, S., Harcourt, J. L., Johnstone, R. A., & Manica, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036606 · Cited by 69
“Recent work on collective movement in larger groups has shown that interactions between nearest neighbours are sufficient to explain synchronisation of direction and speed [32,33]; it will be interesting to see whether the lasting effects of initiation described in this paper scale up to larger groups when multiple tr…”
BackgroundInformative and misinformative interactions in a school of fish
Crosato, E., Jiāng, L., Lecheval, V., Lizier, J. T., Wang, X. R., Tichit, P., Théraulaz, G., & Prokopenko, M. (2018) · Swarm Intelligence · doi:10.1007/s11721-018-0157-x · Cited by 71
“This phenomenon is related to underlying causal interactions, and a common goal is to infer physical interaction rules directly from experimental data (Katz et al. 2011; Gautrais et al. 2012; Herbert-Read et al. 2011) and measure correlations within a collective.”
InfluentialStramaglia, S., Scagliarini, T., Daniels, B. C., & Marinazzo, D. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2020.595736 · Cited by 68
“In many biological systems, pairwise interactions have been found to be insufficient for explaining the orchestrated activity of multiple components (Crutchfield, 1994; Ohiorhenuan et al., 2010; Katz et al., 2011; Yu et al., 2011; Daniels et al., 2016).”
BackgroundAbsence of “selfish herd” dynamics in bird flocks under threat
Sankey, D. W. E., Storms, R. F., Musters, R., Russell, T., Hemelrijk, C. K., & Portugal, S. J. (2021) · Current Biology · doi:10.1016/j.cub.2021.05.009 · Cited by 68
Collective detection based on visual information in animal groups
Davidson, J. D., Sosna, M. M. G., Twomey, C. R., Sridhar, V. H., Leblanc, S. P., & Couzin, I. D. (2021) · Journal of The Royal Society Interface · doi:10.1098/rsif.2021.0142 · Cited by 68
“These methodologies are identical to those used in [53].”
MethodPredators attacking virtual prey reveal the costs and benefits of leadership
Ioannou, C. C., Rocque, F., Herbert‐Read, J. E., Duffield, C., & Firth, J. A. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1816323116 · Cited by 68
Genetic Control of Collective Behavior in Zebrafish
Tang, W., Davidson, J. D., Zhang, G., Conen, K. E., Fang, J., Serluca, F. C., Li, J., Xiong, X., Coble, M., Tsai, T., et al. (2020) · iScience · doi:10.1016/j.isci.2020.100942 · Cited by 62
Sync and Swarm: Solvable Model of Nonidentical Swarmalators
Yoon, S. Y., O’Keeffe, K. P., Mendes, J. F. F., & Goltsev, A. V. (2022) · Physical Review Letters · doi:10.1103/physrevlett.129.208002 · Cited by 65
“[7] Yael Katz, Kolbjørn Tunstrøm, Christos C Ioannou, Cristián Huepe, and Iain D Couzin, “Inferring the structure and dynamics of interactions in schooling fish,” Proceedings of the National Academy of Sciences 108, 18720–18725 (2011).”
BackgroundA unifying framework for quantifying the nature of animal interactions
Potts, J. R., Mokross, K. S., & Lewis, M. A. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0333 · Cited by 65
“For example, fish repulsion-alignment-attraction mechanisms have been measured using several different techniques [16, 17, 18], as have the geometric nature of their interactions [19] and their decision processes [20, 21].”
BackgroundMethodRing states in swarmalator systems
O’Keeffe, K. P., Evers, J. H. M., & Kolokolnikov, T. (2018) · Physical review. E · doi:10.1103/physreve.98.022203 · Cited by 65
Washburne, A. D., Silverman, J. D., Morton, J. T., Becker, D. J., Crowley, D. E., Mukherjee, S., David, L. A., & Plowright, R. K. (2019) · Ecological Monographs · doi:10.1002/ecm.1353 · Cited by 60
Data-driven modelling of social forces and collective behaviour in zebrafish
Zienkiewicz, A. K., Ladu, F., Barton, D. A. W., Porfiri, M., & di Bernardo, M. (2018) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2018.01.011 · Cited by 63
Ioannou, C. C., & Laskowski, K. L. (2023) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2022.0059 · Cited by 63
“[30,31]) or the macroscale group-level behaviour and outcomes of these interactions [32,33].”
BackgroundDelayed Response and Biosonar Perception Explain Movement Coordination in Trawling Bats
Giuggioli, L., McKetterick, T. J., & Holderied, M. W. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004089 · Cited by 63
“Recent experimental studies on golden shiners (Notemigonus crysoleucas) [16] have indicated that speed regulation along the direction of travel appears a more dominant component of the interaction compared to alignment, whereas studies in mosquitofish reported the lack of any justifiable alignment rule [17].”
BackgroundA self-adaptive communication strategy for flocking in stationary and non-stationary environments
Ferrante, E., Turgut, A. E., Stranieri, A., Pinciroli, C., Birattari, M., & Dorigo, M. (2013) · Natural Computing · doi:10.1007/s11047-013-9390-9 · Cited by 63
“These include the zone model by Couzin et al. (2002), the already mentioned study of implicit leadership (Couzin et al. 2005) and more recent works that mapped real data obtained from tracking to individual-based models (Katz et al. 2011; Gautrais et al. 2012).”
BackgroundBurns, A., Herbert‐Read, J. E., Morrell, L. J., & Ward, A. J. W. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036567 · Cited by 62
“An individual’s spatial positioning in a travelling group and the order in which it ultimately made its decision were highly correlated, lending support to the idea that in fish shoals, those individuals in front positions have a strong influence on group travel direction; a finding consistent with a number of other s…”
ResultPhase Transitions in a Kinetic Flocking Model of Cucker--Smale Type
Barbaro, A., Cañizo, J. A., Carrillo, J. A., & Degond, P. (2016) · Multiscale Modeling and Simulation · doi:10.1137/15m1043637 · Cited by 62
“In many biological systems made of a large number of individuals such as cell populations [38], insect colonies [10], or vertebrate groups [28], agents are known to strongly interact with each other.”
BackgroundSpatial positioning of individuals in a group of feral horses: a case study using drone technology
Inoue, S., Yamamoto, S., Ringhofer, M., Mendonça, R. S., Pereira, C., & Hirata, S. (2018) · Mammal Research · doi:10.1007/s13364-018-0400-2 · Cited by 60
“These studies have shown rules with respect to the distance and angle between individuals within a group, suggesting strong preference and anisotropy of the direction for neighboring individuals (Ballerini et al. 2008a; Lukeman et al. 2010; Katz et al. 2011; Pettit et al. 2013; Rosenthal et al. 2015).”
BackgroundA data-driven method for reconstructing and modelling social interactions in moving animal groups
Escobedo, R., Lecheval, V., Papaspyros, V., Bonnet, F., Francesco Mondada, C., Sire, C., & Théraulaz, G. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0380 · Cited by 59
Activity waves and freestanding vortices in populations of subcritical Quincke rollers
Liu, Z. T., Shi, Y., Zhao, Y., Chaté, H., Shi, X.-Q., & Zhang, T. H. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2104724118 · Cited by 60
The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots
Ko, H., LAUDER, G. V., & Nagpal, R. (2023) · Journal of The Royal Society Interface · doi:10.1098/rsif.2023.0357 · Cited by 58
“Recordings that are around an hour long allowed researchers to apply statistical methods and analyse the state of the school [150,168].”
MethodKelley, J. L., Phillips, B., Cummins, G. H., & Shand, J. (2012) · Animal Behaviour · doi:10.1016/j.anbehav.2011.12.028 · Cited by 60
Multi-scale Inference of Interaction Rules in Animal Groups Using Bayesian Model Selection
Mann, R. P., Perna, A., Strömbom, D., Garnett, R., Herbert‐Read, J. E., Sumpter, D. J. T., & Ward, A. J. W. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002961 · Cited by 60
“Either fine scale individual-level behaviour is observed without explicit fitting of a model [18,19] or global properties, such as direction switches [11,20], speed distributions [21,22] or group decision outcome [23] have been compared between model and data.”
BackgroundThe neurogenetics of group behavior inDrosophila melanogaster
Ramdya, P. P., Schneider, J., & Levine, J. D. (2017) · Journal of Experimental Biology · doi:10.1242/jeb.141457 · Cited by 63
“Then, to infer interaction rules giving rise to the grouplevel phenomenon, individuals, pairs and even triads (Katz et al., 2011) of animals are closely studied in highly controlled conditions.”
BackgroundSwarming and pattern formation due to selective attraction and repulsion
Romańczuk, P., & Schimansky-Geier, L. (2012) · Interface Focus · doi:10.1098/rsfs.2012.0030 · Cited by 60
Learning to flock through reinforcement
Durve, M., Peruani, F., & Celani, A. (2020) · Physical Review E · doi:10.1103/physreve.102.012601 · Cited by 58
The Emerging Science of Interacting Minds
Wheatley, T. P., Thornton, M. A., Stolk, A., & Chang, L. J. (2023) · Perspectives on Psychological Science · doi:10.1177/17456916231200177 · Cited by 68
“And schools of fish and flocks of birds can create intricate patterns of collective behavior that increase protection from predators because each individual organism follows simple rules (Couzin, 2009; Katz et al., 2011).”
BackgroundBEEINFO: Interest-Based Forwarding Using Artificial Bee Colony for Socially Aware Networking
Xia, F., Liu, L., Li, J., Ahmed, A. M., Yang, L. T., & Ma, J. (2014) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2014.2305192 · Cited by 59
Motion-guided attention promotes adaptive communications during social navigation
Lemasson, B. H., Anderson, J. J., & Goodwin, R. A. (2013) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2012.2003 · Cited by 59
Hagstrom, G. I., & Levin, S. A. (2017) · Ecosystems · doi:10.1007/s10021-017-0114-3 · Cited by 60
“…and field measurements of different species of schooling fish identified various distinct behavioral states such as swarming, milling, and polarized swimming (Katz et al., 2011), and theoretical methods were used to explain the states in terms of individual-level behaviors (Tunstrøm et al., 2013).”
MethodUsing a robotic fish to investigate individual differences in social responsiveness in the guppy
Bierbach, D., Landgraf, T., Romańczuk, P., Lukas, J., Nguyen, H., Wolf, M., & Krause, J. (2018) · Royal Society Open Science · doi:10.1098/rsos.181026 · Cited by 58
C. elegans collectively forms dynamical networks
Sugi, T., Ito, H., Nishimura, M., & Nagai, K. H. (2019) · Nature Communications · doi:10.1038/s41467-019-08537-y · Cited by 62
KINETIC LIMITS FOR PAIR-INTERACTION DRIVEN MASTER EQUATIONS AND BIOLOGICAL SWARM MODELS
Carlen, E. A., Degond, P., & Wennberg, B. (2012) · Mathematical Models and Methods in Applied Sciences · doi:10.1142/s0218202513500115 · Cited by 56
Data-driven stochastic modelling of zebrafish locomotion
Zienkiewicz, A. K., Barton, D. A. W., Porfiri, M., & di Bernardo, M. (2014) · Journal of Mathematical Biology · doi:10.1007/s00285-014-0843-2 · Cited by 56
“We refer specifically to the findings of Katz et al. (2011) and Herbert-Read and Perna (2011), which report that speed regulation is the primary response governing the interaction between conspecifics and their environment.”
Lattice-Boltzmann hydrodynamics of anisotropic active matter
de Graaf, J., Menke, H., Mathijssen, A. J. T. M., Fabritius, M., Holm, C., & Shendruk, T. N. (2016) · The Journal of Chemical Physics · doi:10.1063/1.4944962 · Cited by 54
Phase Coexistence in Insect Swarms
Sinhuber, M., & Ouellette, N. T. (2017) · Physical Review Letters · doi:10.1103/physrevlett.119.178003 · Cited by 56
Local interactions and their group-level consequences in flocking jackdaws
Ling, H., McIvor, G. E., van der Vaart, K., Vaughan, R., Thornton, A., & Ouellette, N. T. (2019) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2019.0865 · Cited by 56
Learning dynamical models of single and collective cell migration: a review
Brückner, D. B., & Broedersz, C. P. (2024) · Reports on Progress in Physics · doi:10.1088/1361-6633/ad36d2 · Cited by 60
A jump persistent turning walker to model zebrafish locomotion
Mwaffo, V., Anderson, R. P., Butail, S., & Porfiri, M. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0884 · Cited by 54
Cohesion, order and information flow in the collective motion of mixed-species shoals
Ward, A. J. W., Schaerf, T. M., Burns, A., Lizier, J. T., Crosato, E., Prokopenko, M., & Webster, M. (2018) · Royal Society Open Science · doi:10.1098/rsos.181132 · Cited by 54
Active Matter under Control: Insights from Response Theory
Davis, L. K., Proesmans, K., & Fodor, É. (2024) · Physical Review X · doi:10.1103/physrevx.14.011012 · Cited by 53
“Such emergent –collective– properties are plentiful, ranging from the flocking of animals [12–14], active turbulence [15], swarming bacteria [16, 17], to motility-induced phase separation (MIPS) that occurs in the absence of attractive particle interactions [18].”
BackgroundCollective behavior from surprise minimization
Heins, C., Millidge, B., Da Costa, L., Mann, R. P., Friston, K. J., & Couzin, I. D. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2320239121 · Cited by 55
Particle Based gPC Methods for Mean-Field Models of Swarming with Uncertainty
Carrillo, J. A., Pareschi, L., & Zanella, M. (2018) · Communications in Computational Physics · doi:10.4208/cicp.oa-2017-0244 · Cited by 53
The emergence of collective knowledge and cumulative culture in animals, humans and machines
Whiten, A., Biro, D., Bredèche, N., Garland, E. C., & Kirby, S. (2021) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2020.0306 · Cited by 56
“Contexts studied include the collective movements of large aggregates (bird flocks, fish schools, insect swarms and ungulate herds [35 – 37]), collective construction (foraging trail networks, social insect nests and even structures composed of the bodies of the animals themselves, such as…”
Body synchrony in triadic interaction
Dale, R. A. C., Bryant, G. A., Manson, J. H., & Gervais, M. M. (2020) · Royal Society Open Science · doi:10.1098/rsos.200095 · Cited by 58
“Mosquitoes may synchronize their wing flaps during mating [2], fish schools emerge from local interactive dynamics [3], and common chimpanzees appear to coordinate hunting in groups [4].”
BackgroundA physics perspective on collective animal behavior
Ouellette, N. T. (2022) · Physical Biology · doi:10.1088/1478-3975/ac4bef · Cited by 51
“Similar social forces were found to work well to characterize the local behavior of several species of schooling fish [74, 75, 124].”
Swarm intelligence: A survey of model classification and applications
Wang, C., Zhang, S., Tianhang, M. A., Yuetong, X. I. A. O., Chen, M. Z. Q., & Wang, L. (2024) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2024.03.019 · Cited by 62
Inference of Causal Information Flow in Collective Animal Behavior
Lord, W. M., Sun, J., Ouellette, N. T., & Bollt, E. M. (2016) · IEEE Transactions on Molecular Biological and Multi-Scale Communications · doi:10.1109/tmbmc.2016.2632099 · Cited by 51
“perform a macroscopic analysis, focusing on the observed group-level behavior such as the group morphology [20] or the material-like properties [18], [21], [22]; we can perform a microscopic analysis, determining the nature of the interactions between individuals [10], [19], [23], [24]; and we can study how the micros…”
MethodTime-Frequency Analysis Reveals Pairwise Interactions in Insect Swarms
Puckett, J. G., Ni, R., & Ouellette, N. T. (2015) · Physical Review Letters · doi:10.1103/physrevlett.114.258103 · Cited by 50
Rieucau, G., Holmin, A. J., Castillo, J. C., Couzin, I. D., & Handegard, N. O. (2016) · Animal Behaviour · doi:10.1016/j.anbehav.2016.05.002 · Cited by 50
Li, L., Ravi, S., Xie, G., & Couzin, I. D. (2021) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.2020.0810 · Cited by 50
“Individuals of numerous fish species have been observed swimming closely together in schools [1,2].”
BackgroundUsing activity and sociability to characterize collective motion
Sumpter, D. J. T., Szorkovszky, A., Kotrschal, A., Kolm, N., & Herbert‐Read, J. E. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0015 · Cited by 48
Self-organized hydrodynamics with congestion and path formation in crowds
Degond, P., & Hua, J. (2012) · Journal of Computational Physics · doi:10.1016/j.jcp.2012.11.033 · Cited by 48
“Comparisons have been made between the three-zone model and experimental data collected from the observation of groups of locusts [34], surf scooters (a gregarious species of see-duck) [43] and golden shiners (fish) [37].”
BackgroundA new interaction potential for swarming models
Carrillo, J. A., Martin, S., & Panferov, V. A. (2013) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2013.02.004 · Cited by 45
Loza, A. J., Koride, S., Schimizzi, G. V., Li, B., Sun, S. X., & Longmore, G. D. (2016) · Molecular Biology of the Cell · doi:10.1091/mbc.e16-05-0329 · Cited by 47
“This peak represents the response time of the system (Katz et al., 2011), and a shift of the peak to increasing distances at longer delay times provides the rate at which this response propagates.”
BackgroundDiscrete modes of social information processing predict individual behavior of fish in a group
Harpaz, R., Tkačik, G., & Schneidman, E. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1703817114 · Cited by 45
“metric relations between conspecifics (14), effective social “forces” depending on the distance between individuals (5, 6), inference of functional interactions based on maximum entropy models of observed directional correlations (13), hierarchical spatial ordering (12, 31, 32), and active signaling (33, 34).”
BackgroundFishing out collective memory of migratory schools
Luca, G. D., Mariani, P., MacKenzie, B. R., & Matteo Marsili, A. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2014.0043 · Cited by 47
“In fact previous approaches mainly fall in a class of agent based models with spatial interaction [18, 19, 1, 20, 16] where “social” individuals tend to align and to follow the individuals that are nearby, in a finite spatial range.”
BackgroundInherent noise appears as a Lévy walk in fish schools
Murakami, H., Niizato, T., Tomaru, T., Nishiyama, Y., & Gunji, Y. (2015) · Scientific Reports · doi:10.1038/srep10605 · Cited by 47
Adaptive leadership overcomes persistence–responsivity trade-off in flocking
Balázs, B., Vásárhelyi, G., & Vicsek, T. (2020) · Journal of The Royal Society Interface · doi:10.1098/rsif.2019.0853 · Cited by 50
Learning to swim in potential flow
Jiao, Y., Ling, F., Heydari, S., Heess, N., Merel, J., & Kanso, E. A. (2021) · Physical Review Fluids · doi:10.1103/physrevfluids.6.050505 · Cited by 49
“[35] Katz Y, Tunstrøm K, Ioannou CC, Huepe C, Couzin ID.”
BackgroundMcKee, A., Soto, A. P., Chen, P., & McHenry, M. J. (2020) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2020.0568 · Cited by 42
“These persistent changes in relative position contrast the kinematics of some steady-swimming species that maintain their station in a school [4] and probably presents a fish with highly dynamic stimuli.”
BackgroundResultThe origin of traveling waves in an emperor penguin huddle
Gerum, R. C., Fabry, B., Metzner, C., Beaulieu, M., Ancel, A., & Zitterbart, D. P. (2013) · New Journal of Physics · doi:10.1088/1367-2630/15/12/125022 · Cited by 46
“Our approach therefore resembles other many-particle models used to describe collective behavior [10–12] in flocks of birds [13–15], schools of fish [16, 17] or traffic jams [18, 19].”
ResultShared behavioral mechanisms underlie C. elegans aggregation and swarming
Ding, S. S., Schumacher, L. J., Javer, A., Endres, R. G., & Brown, A. E. (2019) · eLife · doi:10.7554/elife.43318 · Cited by 46
Emergence of social cluster by collective pairwise encounters in Drosophila
Jiang, L., Cheng, Y., Gao, S., Zhong, Y., Ma, C., Wang, T., & Zhu, Y. (2020) · eLife · doi:10.7554/elife.51921 · Cited by 45
Fractional calculus ties the microscopic and macroscopic scales of complex network dynamics
West, B. J., Turalska, M., & Paolo Grigolini, A. (2014) · University of North Texas Digital Library (University of North Texas) · Cited by 46
Trail formation based on directed pheromone deposition
Boissard, E., Degond, P., & Motsch, S. (2012) · Journal of Mathematical Biology · doi:10.1007/s00285-012-0529-6 · Cited by 45
Leadership in Moving Human Groups
Boos, M., Pritz, J., Lange, S., & Belz, M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003541 · Cited by 42
“Behavioural modelling [5–7] and empirical research [8–10] have shown that in diverse species, including humans [11,12], local individual rules are adequate to generate complex collective behaviour at the group level [13–15].”
BackgroundUsing field data to test locust migratory band collective movement models
Buhl, C., Sword, G. A., & Simpson, S. J. (2012) · Interface Focus · doi:10.1098/rsfs.2012.0024 · Cited by 45
Székely, M., & Michael, J. (2018) · Cognition · doi:10.1016/j.cognition.2018.01.012 · Cited by 51
Calabrese, J. M., Fleming, C. H., Fagan, W. F., Rimmler, M., Kaczensky, P., Bewick, S. A., Leimgruber, P., & Mueller, T. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0007 · Cited by 45
Collective predator evasion: Putting the criticality hypothesis to the test
Klamser, P., & Romańczuk, P. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008832 · Cited by 49
“The general structure of the assumed social interactions (short ranged repulsion, alignment and long range attraction) is supported by experiments [49, 50].”
ResultCollective behavior emerges from genetically controlled simple behavioral motifs in zebrafish
Harpaz, R., Aspiras, A., Chambule, S., Tseng, S., Bind, M.-A. C., Engert, F., Fishman, M., & Bahl, A. (2021) · bioRxiv · doi:10.1126/sciadv.abi7460 · Cited by 48
“Clutches were raised in small groups 356 (20-30) in 15 cm petri dishes with fish facility water in 14h light, 10 hr dark cycle at constant 28 °C.”
Wang, W., Escobedo, R., Sanchez, S., Sire, C., Han, Z., & Théraulaz, G. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009437 · Cited by 43
Xiao, J. Q., Yuan, G., He, J., Fang, K., & Wang, Z. (2022) · Information Sciences · doi:10.1016/j.ins.2022.11.059 · Cited by 44
Development of neural circuits for social motion perception in schooling fish
Zada, D., Schulze, L., Yu, J., Tarabishi, P., Napoli, J. L., Milan, J., & Lovett-Barron, M. (2024) · Current Biology · doi:10.1016/j.cub.2024.06.049 · Cited by 41
Distinguishing Social from Nonsocial Navigation in Moving Animal Groups
Bode, N. W. F., Franks, D. W., Wood, A. J., Piercy, J. J. B., Croft, D. P., & Codling, E. A. (2012) · The American Naturalist · doi:10.1086/665005 · Cited by 44
“Our case study suggests that our assumptions are adequate, despite the fact that they may not capture the actual mechanisms of animal group movement as suggested by Ballerini et al. (2008) or Katz et al. (2011), for example.”
BackgroundRobustness of flight leadership relations in pigeons
Flack, A., Ákos, Z., Nagy, M., Vicsek, T., & Biro, D. (2013) · Animal Behaviour · doi:10.1016/j.anbehav.2013.07.005 · Cited by 44
“Progress in digital image processing and high temporal resolution tracking has allowed the inference of interaction rules in bird and fish species (e.g., Ballerini et al. 2008; Lukeman et al. 2010; Herbert-Read et al. 2011; Katz et al. 2011).”
BackgroundSpeed-mediated properties of schooling
Kent, M. I. A., Lukeman, R., Lizier, J. T., & Ward, A. J. W. (2019) · Royal Society Open Science · doi:10.1098/rsos.181482 · Cited by 44
“At intermediate distances, these repulsion and attraction forces interact to promote orientation and alignment with neighbours [2,3].”
BackgroundJolles, J. W., Mazué, G. P. F., Davidson, J. D., Behrmann‐Godel, J., & Couzin, I. D. (2020) · Scientific Reports · doi:10.1038/s41598-020-69057-0 · Cited by 43
Agrawal, D., Budak, C., Abbadi, A. E., Georgiou, T., & Yan, X. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-05693-7_1 · Cited by 43
“This type of model, which has its roots in social network theory, was developed to explain small group dynamics [15], and has also been used to simulate dynamics of fish schools [25].”
Method
Metadata
- Authors
- Katz, Y., Tunstrøm, K., Ioannou, C. C., Huepe, C., & Couzin, I. D.
- Affiliations
- Princeton University (US)
- 614 North Paulina Street, Chicago, IL 60622
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-07-27
- Volume
- 108
- Issue
- 46
- Pages
- 18720-18725
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3219116
- OpenAlex
- W2002266200
- Cited by
- 927
- References
- 54
- Citations by year
- 2026: 50 · 2025: 69 · 2024: 76 · 2023: 80 · 2022: 72 · 2021: 73 · 2020: 76 · 2019: 58 · 2018: 69 · 2017: 57 · 2016: 53 · 2015: 54 · 2014: 46 · 2013: 46 · 2012: 40
- FWCI
- 58.66
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion)
- KOPS (University of Konstanz) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- National Science Foundation (0848755, 0905970, N00014-09-1-1074)
- Princeton University
- Norges Forskningsråd
- Advanced Research Projects Agency
- Office of Naval Research (N00014-09-1-1074, N00014)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
- Social Sciences › Safety Research › Evacuation and Crowd Dynamics
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Animal Behavior and Reproduction
- Keywords
- fish schooling, collective behavior, golden shiner, Notemigonus crysoleucas, fish shoals, effective force, speed regulation, alignment, attraction and repulsion, three-body interactions, pairwise interactions, trajectory analysis, social information, group cohesion
- MeSH terms
- Animals, Behavior, Animal, Cyprinidae, Fishes, Models, Biological, Movement, Social Behavior, Software, Swimming, Time Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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