Influence of synaptic depression on memory storage capacity

TL;DR

This paper analyzes how synaptic depression, a form of short-term plasticity, affects neural memory storage capacity when considering the influence of noise, using statistical mechanics methods.

Contribution

It introduces a noise parameter into the analysis of synaptic depression's effect on memory capacity and provides an analytical computation using SCSNA.

Findings

Synaptic depression reduces storage capacity at finite noise levels.

At low noise levels, synaptic depression does not affect capacity.

The study highlights the importance of noise in neural memory models.

Abstract

Synaptic efficacy between neurons is known to change within a short time scale dynamically. Neurophysiological experiments show that high-frequency presynaptic inputs decrease synaptic efficacy between neurons. This phenomenon is called synaptic depression, a short term synaptic plasticity. Many researchers have investigated how the synaptic depression affects the memory storage capacity. However, the noise has not been taken into consideration in their analysis. By introducing "temperature", which controls the level of the noise, into an update rule of neurons, we investigate the effects of synaptic depression on the memory storage capacity in the presence of the noise. We analytically compute the storage capacity by using a statistical mechanics technique called Self Consistent Signal to Noise Analysis (SCSNA). We find that the synaptic depression decreases the storage capacity in the case of finite temperature in contrast to the case of the low temperature limit, where the storage capacity does not change.