From empirical data to inter-individual interactions: Unveiling the rules of collective animal behavior

Raffaele Santagati

Research output: Contribution to journalArticle (Academic Journal)peer-review

72 Citations (Scopus)


Animal groups represent magni¯cent archetypes of self-organized collective behavior. As such,
they have attracted enormous interdisciplinary interest in the last years. From a mechanistic
point of view, animal aggregations remind physical systems of particles or spins, where the
individual constituents interact locally, giving rise to ordering at the global scale. This analogy
has fostered important research, where numerical and theoretical approaches from physics have
been applied to models of self-organized motion. In this paper, we discuss how the physics
methodology may provide precious conceptual and technical instruments in empirical studies of
collective animal behavior. We focus on three-dimensional groups, for which empirical data have
been extremely scarce until recently, and describe novel experimental protocols that allow
reconstructing aggregations of thousands of individuals. We show how an appropriate statistical
analysis of these large-scale data allows inferring important information on the interactions
between individuals in a group, a key issue in behavioral studies and a basic ingredient of
theoretical models. To this aim, we revisit the approach we recently used on starling °ocks, and
apply it to a much larger data set, never analyzed before. The results con¯rm our previous ¯ndings
and indicate that interactions between birds have a topological rather than metric nature, each
individual interacting with a ¯xed number of neighbors irrespective of their distances.
Original languageEnglish
Pages (from-to)1492-1510
Number of pages20
JournalMathematical Models and Methods in Applied Sciences
Issue numberSuppl
Publication statusPublished - 1 Sept 2010


  • Collective behaviour
  • complex systems


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