  Recent experimental studies of living neural networks reveal that their
global activation induced by electrical stimulation can be explained using the
concept of bootstrap percolation on a directed random network. The experiment
consists in activating externally an initial random fraction of the neurons and
observe the process of firing until its equilibrium. The final portion of
neurons that are active depends in a non linear way on the initial fraction.
The main result of this paper is a theorem which enables us to find the
asymptotic of final proportion of the fired neurons in the case of random
directed graphs with given node degrees as the model for interacting network.
This gives a rigorous mathematical proof of a phenomena observed by physicists
in neural networks.
