A principle of neural associative memory

A model based upon a hypothesis of synaptic modification is constructed, and its behaviour is analysed with the aid of computer simulations to demonstrate the selective recall of a large number of signal patterns from an associative memory network based upon assumptions that are anatomically and physiologically feasible.

Abstract

Abstract This paper presents a demonstration of a possible mechanism of distributed memory which by association recalls the missing part of a memorized pattern. A model based upon a hypothesis of synaptic modification is constructed, and its behaviour is analysed with the aid of computer simulations. The hypothesis implies a change in the transmission etficacies of synapses in proportion to both pre- and postsynaptic activity levels. The basic design of this model is applicable to different types of neural networks, but is here exemplified in an idealized cerebral cortex. Incorporation of the principle of lateral inhibition implies that the selectivity of the memory mechanism is made greatly superior to that of many other models of associative memory. This has made it practicable to demonstrate the selective recall of a large number of signal patterns from an associative memory network based upon assumptions that are anatomically and physiologically feasible. A computer simulation with photographic images (faces) is reported in which one of 500 stored images was faithfully recalled when a fragment of it was used as the key excitation.