The research in the Couzin laboratory focuses on revealing the principles that underlie collective animal behavior. Understanding how social influence shape biological processes is a central challenge, essential for achieving progress in a variety of fields ranging from the organization and evolution of coordinated collective action among cells, or animals, to the dynamics of information exchange in human societies. By developing an integrated experimental and theoretical research program we aim to explore functional properties of groups in a context that can reveal how, and why, social behavior has evolved.
This has allowed us to explore the causes and consequences of social behaviors over ecological and evolutionary timescales, and to identify principles in common among what may initially appear to be disparate biological processes. We are particularly interested in the mechanism and evolution of functional collective behavior in groups where relatedness is relatively low such as swarming locusts, and many schooling fish and flocking birds. Our experimental research has been conducted both in the laboratory and the field, and is characterized by a highly quantitative approach, such as our development and use of new imaging technologies that allow us to investigate behavior at multiple scales, simultaneously. We employ both numerical and analytical approaches in our development of theory.
The research in our lab relates to a wide range of areas of scientific inquiry including behavior, ecology, psychology, statistical physics, network theory, self-organization, complexity studies, engineering and evolutionary biology. Consequently members of our lab have come from diverse backgrounds including behavioral ecology, architecture, computational and experimental neuroscience, physics, computer science, applied mathematics and psychology. In addition we often host visiting graduate students and postdoctoral fellows from across the globe.
Please see the following links for information about some ongoing, interrelated, projects:
- Collective decision-making
- Collective sensing
- The dynamics of group hunting and collective evasion
- Revealing the structure of sensory interaction networks in animal groups
- Embedding organisms into Virtual Reality (VR) worlds to understand the evolution and mechanism of social interactions
- Quantitative approaches to the study of animal behaviour (e.g. computer vision, GPS, 3D reconstruction, drone imaging, machine learning)
- Collective behavior in locust swarms
- Modeling collective behavior (collective computation and multi-level selection)