Discussion on the reverberatory model of short-term memory: a computational approach.

Up to now a number of models have been proposed to underlie memory formation in the central nervous system. Two of these models are the reverberatory circuit model and the other one the self-feedback loop model. This paper considers these two models regarding their ability to preserve neural activity and to hold information. In the self-feedback loop model, the activity level of the loop output is computed regarding the short lasting initial input. In the reverberatory circuit model, the activity levels of the proposed two-layer network outputs were computed regarding the short lasting initial inputs of the network. In the self-feedback loop model, the activity level of the loop output changes with each reverberation until it reaches a specific limit and then remains at that level. In the reverberatory circuit model, the activity levels of the proposed two-layer network outputs display an oscillatory behavior. These models can preserve the input activity, but they change its level with each reverberation. Information carried by a single neuron is related to its activity level. Therefore these models change the information during the reverberation. Short-term memory must hold the information for a certain period of time, so these models cannot be proposed to underlie short-term memory formation.