Emulation of Hopfield networks with spiking neurons in temporal coding
A theoretical model for analog computation with temporal coding is introduced and tested through simulations in GENESIS. It turns out that the use of multiple synapses yields very noise robust mechanisms for analog computations with temporal coding in networks of detailed compartmental neuron models. One arrives in this way at a method for emulating arbitrary Hopfield nets with spiking neurons in temporal coding, yielding new models for associative recall of spatio-temporal firing patterns. A corresponding layered architecture yields a refinement of the synfire-chain model that can assume a fairly large set of different firing patterns for different inputs.