Abstract
A method for storing and retrieving spatio-temporal patterns in large systems of coupled delay differential equations is presented. Spatio-temporal patterns are sets of finite sequences of binary variables of fixed period that are embedded in the network dynamics as stable limit cycles. An input signal converges to the limit cycle that represents it best. A given set of limit cycles is constructed using a generalization of the correlation learning rule in the definition of the couplings.

Keywords: Limit cycles; Delay differential equations; Associative memories