Abstract:
More than three decades ago, it was proposed that certain natural systems can be viewed as self-organized critical systems, which self-tune themselves to special regions in parameter space close to so-called critical points, where the behavior of a system exhibits a qualitative change at the macroscopic scale, i.e. it undergoes a phase transition. Over the years, theoretical research has shown that various aspects of collective computation become optimal at criticality and it has been conjectured that distributed information processing systems in biology such as the brain or animal groups should operate at, or close to criticality. In this lecture, I will give a brief introduction to the concept of criticality, give a short overview over some selected theoretical studies on optimal information processing at criticality, as well as empirical evidence for the ‘criticality hypothesis’ from neuronal dynamics and collective behavior of animals, including some of our recent work on the topic. I will close with a critical discussion on criticality in the context of collective information processing.

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