Learning or memory in the cortex 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 corresponds to a dynamic pattern of the associated neural circuit. I present a recent work with M. Krupa in which we consider neuronal network 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 defined by robust heteroclinic cycles, and establish a tight connection between their existence and the structure of the coupling.