Storing and retrieving long-term memories: cooperation and competition in synaptic dynamics

TL;DR

This paper reviews models of synaptic competition and cooperation, emphasizing the importance of slow synaptic dynamics and competitive interactions for long-term memory storage, highlighting recent theoretical advances and remaining challenges.

Contribution

It introduces recent theoretical models incorporating synaptic competition and cooperation, advancing understanding of long-term memory mechanisms beyond traditional approaches.

Findings

Competitive synaptic dynamics are crucial for long-term memory storage.

Recent models use agent-based techniques to incorporate synaptic dynamics.

Understanding synaptic cooperation and competition remains an open challenge.

Abstract

We first review traditional approaches to memory storage and formation, drawing on the literature of quantitative neuroscience as well as statistical physics. These have generally focused on the fast dynamics of neurons; however, there is now an increasing emphasis on the slow dynamics of synapses, whose weight changes are held to be responsible for memory storage. An important first step in this direction was taken in the context of Fusi's cascade model, where complex synaptic architectures were invoked, in particular, to store long-term memories. No explicit synaptic dynamics were, however, invoked in that work. These were recently incorporated theoretically using the techniques used in agent-based modelling, and subsequently, models of competing and cooperating synapses were formulated. It was found that the key to the storage of long-term memories lay in the competitive dynamics of synapses. In this review, we focus on models of synaptic competition and cooperation, and look at the outstanding challenges that remain.