12–17 Jul 2026
University of Graz
Europe/Vienna timezone

The Geometry of Decision-Making

PLT-08
17 Jul 2026, 14:00
50m
University of Graz

University of Graz

Plenary Talk

Speaker

Iain Couzin (Max Planck Institute of Animal Behavior Center for the Advanced Study of Collective Behaviour)

Description

Running, swimming, or flying through the world, animals are constantly making decisions while on the move—decisions that allow them to choose where to eat, where to hide, and with whom to associate. Despite this most studies have considered only on the outcome of, and time taken to make, decisions. Motion is, however, crucial in terms of how space is represented by organisms during spatial decision-making. Using a combination of modeling, automated tracking, computational reconstruction of sensory information, and immersive ‘holographic’ virtual reality (VR) experiments with ants, fruit flies, locusts, and zebrafish, I will demonstrate that this time-varying representation results in the emergence of new and fundamental geometric principles that considerably impact decision-making. Specifically, we find that the brain spontaneously reduces multi-choice decisions into a series of abrupt (‘critical’) binary decisions in space-time, a process that repeats until only one option—the one ultimately selected by the individual—remains. Due to the critical nature of these transitions (and the corresponding increase in ‘susceptibility’) even noisy brains are extremely sensitive to very small differences between remaining options (e.g., a very small difference in neuronal activity being in “favor” of one option) near these locations in space-time. This mechanism facilitates highly effective decision-making, and is shown to be robust both to the number of options available, and to context, such as whether options are static (e.g. refuges) or mobile (e.g. other animals). In addition, we find evidence that the same geometric principles of decision-making occur across scales of biological organization, from neural dynamics to animal collectives, suggesting they are fundamental features of spatiotemporal computation.

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