Long term memory: Encoding and storing strategies of the brain

Abstract Plastic material devices, either artificial or biological, should be capable of rapidly modifying their internal state to acquire information and, at the same time, preserve it for long periods (the stability–plasticity dilemma). Here we compare, in a simple and intuitive way, memory stability against noise of two different strategies based, respectively, on fully analog devices that accumulate linearly small changes and on systems with a limited number of stable states and threshold mechanisms. We show that the discrete systems are more stable, even with short inherent time constants, and can easily exploit the noise in the input to control the learning rate. We finally demonstrate the strategy by discussing a model of a biologically plausible spike-driven synapse.