Partially Structured Synaptic Transitions

We show that stochastic learning of attractors can take place in a situation in which either only potentiation or only depression of synaptic eecacies are caused in a structured Hebbian way. In each case the transition in the opposite sense take place at random, but occurs only upon presentation of a stimulus. The outcome is an associative memory with the palimpsest property. It is shown that structured potentiation produces more eeective learning than structured depression, i.e. it creates a network with a much higher number of retrievable memories.