Transition to chaos in random networks with cell-type-specific   connectivity
  In neural circuits, statistical connectivity rules strongly depend on neuronal type. Here we study dynamics of neural networks with cell-type specific connectivity by extending the dynamic mean field method, and find that these networks exhibit a phase transition between silent and chaotic activity. By analyzing the locus of this transition, we derive a new result in random matrix theory: the spectral radius of a random connectivity matrix with block-structured variances. We apply our results to show how a small group of hyper-excitable neurons within the network can significantly increase the network's computational capacity. 
Johnatan Aljadeff, Merav Stern, Tatyana O. Sharpee
q-bio.NC cond-mat.dis-nn math.PR nlin.CD