Institute Seminar - Dan Gorbonos: Criticality in decision making

Institute Seminar Series

  • Date: Dec 7, 2021
  • Time: 10:30 - 11:30
  • Speaker: Dan Gorbonos
  • Location: Hybrid meeting
  • Room: Seminar room MPI-AB Möggingen + Online
  • Host: Max Planck Institute of Animal Behavior
  • Contact: all.science@ab.mpg.de
Institute Seminar - Dan Gorbonos: Criticality in decision making
Choosing among spatially-distributed options is a central challenge for animals, from deciding among alternative potential food sources or refuges, to choosing with whom to associate. We present a model for the recursive interplay between movement and vectorial integration in the brain during decision-making regarding two, or more, options (potential ‘targets’) in space. This model is an extension of the Ising spin model of ferromagnetism where the spin-spin interactions are interpreted as interactions among neural ensembles in the brain. This simplified model is very general, capturing the essence of both explicit ring-attractor networks, with local excitation and long-range/global inhibition (as found in fruit flies, and other insects), and computation among distributed competing neural groups (as in the mammalian brain).

Studies of this model in the mean field approximation and numerical simulations revealed the occurrence of spontaneous and abrupt "critical" transitions (associated with specific geometrical relationships) whereby organisms spontaneously switch from averaging vectorial information, to suddenly excluding one of the options. For two targets we find one bifurcation point and for three targets we find that the decision is broken down to a series of bifurcations up to a theoretical limit of an infinite number.

As expected at critical points of phase transitions, the susceptibility along the trajectories diverges at bifurcation points and the short-time response function reaches its maximal value there, which corresponds to increased sensitivity of the organism at those points to small differences between the targets.

In addition we present an energetic description of the bifurcations which is successful in explaining which trajectories are more probable than others.

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