Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
134 tokens/sec
GPT-4o
9 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Selective social interactions and speed-induced leadership in schooling fish (2305.17108v2)

Published 26 May 2023 in physics.bio-ph

Abstract: Animals moving together in groups are believed to interact among each other with effective social forces, such as attraction, repulsion and alignment. Such forces can be inferred using 'force maps', i.e. by analysing the dependency of the acceleration of a focal individual on relevant variables. Here we introduce a force map technique suitable for the analysis of the alignment forces experienced by individuals. After validating it using an agent-based model, we apply the force map to experimental data of schooling fish. We observe signatures of an effective alignment force with faster neighbours, and an unexpected anti-alignment with slower neighbours. Instead of an explicit anti-alignment behaviour, we suggest that the observed pattern is the result of a selective attention mechanism, where fish pay less attention to slower neighbours. This mechanism implies the existence of temporal leadership interactions based on relative speeds between neighbours. We present support for this hypothesis both from agent-based modelling, as well as from exploring leader-follower relationships in the experimental data.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (26)
  1. D. J. T. Sumpter, Collective Animal Behavior (Princeton University Press, 2010).
  2. T. Vicsek and A. Zafeiris, Collective motion, Physics Reports 517, 71 (2012).
  3. P. Romanczuk, I. D. Couzin, and L. Schimansky-Geier, Collective Motion due to Individual Escape and Pursuit Response, Physical Review Letters 102, 010602 (2009).
  4. J. E. Herbert-Read, Understanding how animal groups achieve coordinated movement, Journal of Experimental Biology 219, 2971 (2016).
  5. D. Strömbom, Collective motion from local attraction, Journal of Theoretical Biology 283, 145 (2011).
  6. R. Bastien and P. Romanczuk, A model of collective behavior based purely on vision, Science Advances 6, eaay0792 (2020).
  7. D. Strömbom and G. Tulevech, Attraction vs. Alignment as Drivers of Collective Motion, Frontiers in Applied Mathematics and Statistics 7 (2022).
  8. R. Lukeman, Y.-X. Li, and L. Edelstein-Keshet, Inferring individual rules from collective behavior, Proceedings of the National Academy of Sciences 107, 12576 (2010).
  9. R. K. Mudaliar and T. M. Schaerf, Examination of an averaging method for estimating repulsion and attraction interactions in moving groups, PLOS ONE 15, e0243631 (2020).
  10. R. K. Mudaliar and T. M. Schaerf, An examination of force maps targeted at orientation interactions in moving groups, PLOS ONE 18, e0286810 (2023).
  11. A. Zafeiris and T. Vicsek, Why We Live in Hierarchies?: A Quantitative Treatise, SpringerBriefs in Complexity (Springer International Publishing, Cham, 2018).
  12. N. Orange and N. Abaid, A transfer entropy analysis of leader-follower interactions in flying bats, The European Physical Journal Special Topics 224, 3279 (2015).
  13. D. Bumann and J. Krause, Front Individuals Lead in Shoals of Three-Spined Sticklebacks (Gasterosteus Aculeatus) and Juvenile Roach (Rutilus Rutilus), Behaviour 125, 189 (1993).
  14. D. Weihs, Energetic advantages of burst swimming of fish, Journal of Theoretical Biology 48, 215 (1974).
  15. R. Harpaz, G. Tkačik, and E. Schneidman, Discrete modes of social information processing predict individual behavior of fish in a group, Proceedings of the National Academy of Sciences 114, 10149 (2017).
  16. B. Lemasson, J. Anderson, and R. Goodwin, Collective motion in animal groups from a neurobiological perspective: The adaptive benefits of dynamic sensory loads and selective attention, Journal of Theoretical Biology 261, 501 (2009).
  17. B. H. Lemasson, J. J. Anderson, and R. A. Goodwin, Motion-guided attention promotes adaptive communications during social navigation, Proceedings of the Royal Society B: Biological Sciences 280, 20122003 (2013).
  18. A. Haluts, A. Jordan, and N. S. Gov, Modelling animal contests based on spatio-temporal dynamics, Journal of The Royal Society Interface 20, 20220866 (2023).
  19. R. B. Ivry and A. Cohen, Asymmetry in visual search for targets defined by differences in movement speed, Journal of Experimental Psychology: Human Perception and Performance 18, 1045 (1992).
  20. J. M. Wolfe and T. S. Horowitz, What attributes guide the deployment of visual attention and how do they do it?, Nature Reviews Neuroscience 5, 495 (2004).
  21. B. L. Partridge and T. J. Pitcher, The sensory basis of fish schools: Relative roles of lateral line and vision, Journal of Comparative Physiology ? A 135, 315 (1980).
  22. J. W. Jolles, A. J. King, and S. S. Killen, The Role of Individual Heterogeneity in Collective Animal Behaviour, Trends in Ecology & Evolution 35, 278 (2020b).
  23. P. P. Klamser and P. Romanczuk, Collective predator evasion: Putting the criticality hypothesis to the test, PLOS Computational Biology 17, e1008832 (2021).
  24. P. Romanczuk and L. Schimansky-Geier, Brownian Motion with Active Fluctuations, Physical Review Letters 106, 230601 (2011).
  25. R. Toral and P. Colet, Stochastic Numerical Methods: An Introduction for Students and Scientists (John Wiley & Sons, 2014).
  26. G. Bradski, The OpenCV Library, Dr. Dobb’s Journal: Software Tools for the Professional Programmer 25 (2000).
Citations (4)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com