Binding and multiple instantiation in a distributed network of spiking nodes
An implementation of a distributed connectionist network of spiking neuron-like elements is presented. Spiking nodes fire at a precise moment and transmit their activation, with particular strengths and delays, to nodes connected to them. When the potential of the node reaches a particular threshold, it emits a spike. Thereafter, the potential is reset to a resting value. The receiving nodes accumulate potential, but also slowly lose their potential through decay. As with real neurons., after firing there is a short refractory period during which the node will be completely insensitive to incoming signals, after which its sensitivity will slowly increase. Precise timing properties are used to represent symbols in a distributed manner and to solve the problems of variable binding and multiple instantiation. Several predictions about human short-term memory, predicate processing, complex reasoning and multiple instantiation arise from this model. This network shows how symbolic processing can be achieved using neurobiologically and psychologically plausible mechanisms that also have the advantages of generalization and noise tolerance found in connectionist networks.
multiple instantiation spiking nodes memory symbolic processing binding problem inference