Temporal patterns recognized by a network of coordinated time delays and coincidence detectors

A computational model of a neuronal network is described which performs a fundamental task of general perception: recognition of temporal patterns in continuous and uncued neuronal spike trains. The presented network is able to recognize each pattern element (100 ms interval composed of sets of 10, 20, 30 and 40 ms interspike intervals combined in linear order) as it arrives. Its operation is based upon biologically plausible filtering mechanisms and population neurodynamics.