  We study the effect of varying wiring in excitable random networks in which
connection weights change with activity to mold local resistance or
facilitation due to fatigue. Dynamic attractors, corresponding to patterns of
activity, are then easily destabilized according to three main modes, including
one in which the activity shows chaotic hopping among the patterns. We describe
phase transitions to this regime, and show a monotonous dependence of critical
parameters on the heterogeneity of the wiring distribution. Such correlation
between topology and functionality implies, in particular, that tasks which
require unstable behavior --such as pattern recognition, family discrimination
and categorization-- can be most efficiently performed on highly heterogeneous
networks. It also follows a possible explanation for the abundance in nature of
scale--free network topologies.
