1206.0166 (Matthias Rybarsch et al.)

Self-organization to criticality in neural networks: A minimal model
with binary threshold nodes    [PDF]

Matthias Rybarsch, Stefan Bornholdt

Spin models on adaptive networks have been shown to exhibit self-organized critical behavior from simple, biologically inspired and locally defined adaptation rules, and have been used to argue for similar adaptive mechanisms in the brain [1]. Subsequently, activity avalanches have been observed in cortical cultures which support the hypothesis of neural dynamics near criticality [2]. This key experiment sparked a wealth of model studies as well as further experimental studies. We here revisit the earlier self-organized critical spin model in the light of the new data. In particular we translate the spin model to a network of biologically plausible threshold nodes, and adapt the original correlation-based rewiring algorithm. As a result the new model allows to quantify neuronal avalanches in the evolved networks, which compare well with the observed activity avalanches in real cortical cultures.

View original: http://arxiv.org/abs/1206.0166