  We study a model of associative memory based on a neural network with
small-world structure. The efficacy of the network to retrieve one of the
stored patterns exhibits a phase transition at a finite value of the disorder.
The more ordered networks are unable to recover the patterns, and are always
attracted to mixture states. Besides, for a range of the number of stored
patterns, the efficacy has a maximum at an intermediate value of the disorder.
We also give a statistical characterization of the attractors for all values of
the disorder of the network.
