This action funds an NSF Postdoctoral Research Fellowship for FY 2009. The fellowship supports a research and training plan entitled "Information processing in animal groups" for Yael Katz. The host institution for this research is Princeton University and the sponsoring scientist is Iain D. Couzin.
Grouping organisms, such as schooling fish, often have to make rapid decisions in uncertain and dangerous environments. Decision-making by individuals within such aggregates is so seamlessly integrated that it has been associated with the concept of a "collective mind". As each organism has relatively local sensing ability, coordinated animal groups have evolved collective strategies that allow individuals to access higher-order computational abilities at the collective level. This research integrates various approaches to understand the functional organization of collective biological systems. On the theory side, this research investigates whether analogues to the strategies used by neural systems to integrate information over a wide range of spatial and temporal scales lead to biologically realistic behaviors in schooling models. On the experimental side, this research uses a laboratory schooling fish system that is easy to observe at high resolution and can interact in real-time with robotic fish. Computer-vision software is being developed to track the fish and use tools from statistical physics to uncover the dynamics of the fish-schooling network, investigate how a focal point of information spreads among individuals leading to a change of state, and test mathematical models that link the behavior of individuals and group-level properties.
Training goals include learning about fish biology and ecology, computer vision, robotics, programming of graphics processing units, and how to effectively coordinate and communicate research across disciplines. The research findings will be published in scientific journals and made publically available through the internet. A deeper understanding of collective animal behavior can be applied to an extremely diverse array of research areas that benefit society, such as plague prevention, tumor suppression, and traffic control.
