Collective
Sensing and Decision-Making in Animal Groups: From Fish Schools to Primate
Societies
Understanding
how social influence shapes biological processes is a central challenge in
contemporary science, 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. Using an integrated experimental and theoretical approach
I will address how, and why, animals exhibit highly-coordinated collective
behavior. I will demonstrate imaging and virtual reality technology that allows
us to reconstruct (automatically) the dynamic, time-varying networks that
correspond to the visual cues employed by organisms when making movement
decisions. Sensory networks are shown to provide a much more accurate
representation of how social influence propagates in groups, and their analysis
allows us to identify, for any instant in time, the most socially-influential
individuals within groups, and to predict the magnitude of complex behavioral
cascades before they actually occur. I will also investigate the coupling
between spatial and information dynamics in groups and reveal that emergent
problem solving is the predominant mechanism by which mobile groups sense, and
respond to complex environmental gradients. Evolutionary modeling demonstrates
such ‘physical computation’ readily evolves within populations of selfish
organisms, allowing individuals to compute collectively the spatial
distribution of resources. Finally, I will reveal the critical role uninformed,
or unbiased, individuals play in effecting fast and democratic consensus
decision-making in collectives, and will test these predictions with
experiments involving schooling fish and groups of wild storks and baboons.