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NeuroCOLT
Technical Report NC-TR-97-022
Networks
of Spiking Neurons Can Emulate Arbitrary Hopfield Nets in Temporal
Coding
Wolfgang
Maass and Thomas Natschlager
Technische Universitaet Graz
Austria
Abstract
A theoretical model for analog computation in networks of spiking
neurons 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 via the timing
of single spikes 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.
We also show that it suffices to store these patterns in the efficacies
of excitatory synapses. A corresponding layered
architecture yields a refinement of the synfire-chain model that can
assume a fairly large set of different stable firing patterns for
different inputs.
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