  Learning or memory formation are associated with the strengthening of the
synaptic connections between neurons according to a pattern reflected by the
input. According to this theory a retained memory sequence is associated to a
dynamic pattern of the associated neural circuit. In this work we consider a
class of network neuron models, known as Hopfield networks, with a learning
rule which consists of transforming an information string to a coupling
pattern. Within this class of models we study dynamic patterns, known as robust
heteroclinic cycles, and establish a tight connection between their existence
and the structure of the coupling.
