Couzin Lab – Collective Animal Behaviour

Latest posts

Cannibalism and collective behavior in swarming insects (No comment)
Group meeting with Noam Miller: Quantitative analysis of zebrafish schooling (No comment)
Collective Motion and Decision-Making in Animal Groups (No comment)
High performance computing for massively parallel simulations of animal group behavior (No comment)
Pheromone trail networks in ants (No comment)
Roman Stocker lecture at EEB seminar (No comment)

Cannibalism and collective behavior in swarming insects

One of the most striking and devastating examples of collective movement is exhibited by locusts. Swarms of the desert locust, Schistocerca gregaria, can devour large areas of vegetation and have a huge social and economic impact on humans, affecting the livelihood of one in ten people on the planet in plague years. How do these [...]

Cannibalism and collective behavior in swarming insects

Cannibalism and collective behavior in swarming insects

Collective Motion and Decision-Making in Animal Groups

By accessing social cues individuals, who may themselves be limited in sensory range and cognitive capacity, can access higher-order computational capabilities. We have shown how directional information can be effectively disseminated within groups, facilitating both ad-hoc leadership and consensus decision-making even in the absence of signaling or individual recognition. Furthermore we demonstrated that the larger [...]

Collective Motion and Decision-Making in Animal Groups

Collective Motion and Decision-Making in Animal Groups

High performance computing for massively parallel simulations of animal group behavior

We are developing massively parallel simulation models of animal group behavior using General Purpose Graphics Processing Units (GPGPUs) and NVidia’s CUDA programming architecture and OpenCL. This high performance computing environment allows us to harness thousands of processing cores allowing us to simulate millions of interacting individuals in complex environments as well as to explore the [...]

High performance computing for massively parallel simulations of animal group behavior

High performance computing for massively parallel simulations of animal group behavior

Pheromone trail networks in ants

Among the everyday-life challenges an ant colony faces, the exploration and the exploitation of its environment is one of the most critical. In some species food collection is achieved by thousands of workers travelling along well-defined foraging trails. These trails emerge from a succession of pheromone deposits and can result in a complex network of interconnected routes. CouzinLab [...]

Pheromone trail networks in ants

Pheromone trail networks in ants

Animal groups such as bird flocks, fish schools and insect swarms frequently exhibit complex and coordinated behaviors that result from social interactions among individuals. A fundamental problem in a wide range of biological disciplines is understanding how functional complexity at a macroscopic scale (such as the functioning of a biological tissue) results from the actions and interactions among the individual components (such as the cells forming the tissue). Since they can be readily observed and manipulated animal groups present unrivalled opportunities to link the behavior of individuals with the functioning and efficiency of the dynamic group-level properties The CouzinLab is a highly interdisciplinary environment with a closely integrated experimental and theoretical research program to elucidate the fundamental principles that underlie collective behavior across levels of biological organization.

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Latest lab publications
- Torney, C., Neufeld, Z., & Couzin, I. D. (in press) Context-dependent interaction leads to emergent search behavior in social aggregates. Proceedings of the National Academy of Sciences USA.
- Simpson, S. J., Raubenheimer, D., Charleston, M. A., Clissold, F. J., Couzin, I. D., & Clements, K. D., et al. (in press). Modelling nutritional interactions: from individuals to communities. Trends in Ecology & Evolution.
- Deisboeck, T. S., & Couzin, I. D. (2009). Collective behavior in cancer cell populations. BioEssays, 31(2), 190-197.
- Dyer, J. R. G., Johansson, A., Helbing, D., Couzin, I. D., & Krause, J. (2009). Leadership, consensus decision making and collective behaviour in humans. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1518), 781-789.
- Romanczuk, P., Couzin, I. D., & Schimansky-Geier, L. (2009). Collective Motion due to Individual Escape and Pursuit Response. Physical Review Letters, 102(1), 010602.
- Yates, C. A., Erban, R., Escudero, C., Couzin, I. D., Buhl, J., & Kevrekidis, I. G., et al. (2009). Inherent noise can facilitate coherence in collective swarm motion. Proceedings of the National Academy of Sciences, 106(14), 5464-5469.
Tags

Algae Argentine ant Bactariae Cannibalism Collective behaviors Collective cognition collective decision consensus Crickets CUDA decision-making EEB seminar Environmental Microfluidics Group fish Fluid dynamics GPU Group meeting Image analysis informed leadership Linepithema humile Locusts Microorganisms Microzooplankton MIT Models Network Noam Miller OpenCL Oscillations Pheromone Protists Roman Stocker Schistocerca gregaria Schooling Simulations Stigmergy Swarm Tracking Trails Videomicroscopy Zebrafish
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