ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2020
A data-driven method for reconstructing and modelling social interactions in moving animal groups.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 58 citations in OpenAlex.
- Closed-loop real-virtual interactions validate 3D model of social coordination in fish.PLoS computational biology · 2026Article
- Swimming with robots: investigating fish locomotion, sensing, and schooling behavior with robotic swimmers.Nature communications · 2026Review
- Collective phases and long-term dynamics in a fish school model with burst-and-coast swimming.Royal Society open science · 2025Article
- Collective responses of flocking sheep (Ovis aries) to a herding dog (border collie).Communications biology · 2024Article
- Collective order and group structure of shoaling fish subject to differing risk-level treatments with a sympatric predator.Royal Society open science · 2024Article
- Selective social interactions and speed-induced leadership in schooling fish.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Collective behavior from surprise minimization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Dynamical order and many-body correlations in zebrafish show that three is a crowd.Nature communications · 2024Article
- Predicting the long-term collective behaviour of fish pairs with deep learning.Journal of the Royal Society, Interface · 2024Article
- Tuning social interactions' strength drives collective response to light intensity in schooling fish.PLoS computational biology · 2023Article
- Smart self-propelled particles: a framework to investigate the cognitive bases of movement.Journal of the Royal Society, Interface · 2023Article
- Article
- The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective.Frontiers in neurorobotics · 2023Article
- The impact of individual perceptual and cognitive factors on collective states in a data-driven fish school model.PLoS computational biology · 2022Article
- A statistical method for identifying different rules of interaction between individuals in moving animal groups.Journal of the Royal Society, Interface · 2021Article
- Collective information processing in human phase separation.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Article
- Multi-scale analysis and modelling of collective migration in biological systems.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Article
- Computational and robotic modeling reveal parsimonious combinations of interactions between individuals in schooling fish.PLoS computational biology · 2020Article
- Examination of an averaging method for estimating repulsion and attraction interactions in moving groups.PloS one · 2020Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Group-living organisms that collectively migrate range from cells and bacteria to human crowds, and include swarms of insects, schools of fish, and flocks of birds or ungulates. Unveiling the behavioural and cognitive mechanisms by which these groups coordinate their movements is a challenging task. These mechanisms take place at the individual scale and can be described as a combination of interactions between individuals and interactions between these individuals and the physical obstacles in the environment. Thanks to the development of novel tracking techniques that provide large and accurate datasets, the main characteristics of individual and collective behavioural patterns can be quantified with an unprecedented level of precision. However, in a large number of studies, social interactions are usually described by force map methods that only have a limited capacity of explanation and prediction, being rarely suitable for a direct implementation in a concise and explicit mathematical model. Here, we present a general method to extract the interactions between individuals that are involved in the coordination of collective movements in groups of organisms. We then apply this method to characterize social interactions in two species of shoaling fish, the rummy-nose tetra (
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