Talk: Brain on the brink: Self-organizing neural networks between chaos and order

Stefan is a Professor of Theoretical Physics at University of Bremen. He uses methods from theoretical physics to study origin, dynamics, and function of complex systems from diverse disciplines from biological networks as gene regulation networks and neural networks, to social networks and socio-economic systems, where collective phenomena in human society are approached from a statistical physics and dynamical systems perspective. 

Abstract:

Nerve cells in the brain act like tiny loaded Colts—always ready to fire—and form a dense signaling network that appears prone to runaway activity. Yet the brain remains stable during thought, perception, and rest. Recent measurements show that even in the resting state the brain “crackles”: sparse, irregular firings produce avalanche-like activity whose statistics match those of classical critical phenomena in physics, from earthquakes and slowly crumpling paper to the snap-crackle-pop of Rice Krispies. Motivated by these observed scale-free statistics of neural avalanches, I will review  mechanisms of self-organized criticality in adaptive networks and their use as simplified models of brain criticality. The architectural features of cortical networks suggest a fresh perspective on the phase transition of the classical spin-glass model of random neural networks. This viewpoint points to an alternative route to self-organized criticality in networks and highlights the interplay between network topology and self-organization. Brief remarks on possible implications beyond neuroscience conclude the talk. Concepts from statistical physics and complex systems—self-organized criticality, phase transitions, and collective dynamics—thus offer a coherent framework for understanding how the brain maintains its delicate balance between order and chaos.