Memory instability as a gateway to generalization

Abstract

Our present frequently resembles our past. Patterns of actions and events repeat throughout our lives like a motif. Identifying and exploiting these patterns are fundamental to many behaviours, from creating grammar to the application of skill across diverse situations. Such generalization may be dependent upon memory instability. Following their formation, memories are unstable and able to interact with one another, allowing, at least in principle, common features to be extracted. Exploiting these common features creates generalized knowledge that can be applied across varied circumstances. Memory instability explains many of the biological and behavioural conditions necessary for generalization and offers predictions for how generalization is produced.

Fig 1. Memory instability as an explanation for the trade-off between detailed knowledge and generalization.

Each memory representation has common (blue bars) and unique features (memory A, red bars; memory B; green bars). (A) When unstable memories interact and interfere with one another, it leads (B) to the loss of detailed information about an event or action. For example, learning tennis (memory A) and badminton (memory B) in quick succession might lead to loss of skills specific to tennis. (C) However, the interaction between memories may allow the identification and extraction of shared common features between memories (blue bars). (D) Exploiting those common features allows knowledge to be applied broadly across a range of related situations. For instance, the skill acquired playing tennis can be applied or transferred to other related racquet sports (dark grey; squash and badminton) and also perhaps even to other somewhat related sports (light grey; cricket and baseball). Instability provides an opportunity for interaction between memories, which can lead to their disruption and the loss of detailed knowledge, while simultaneously allowing shared features to be identified and exploited to allow generalization. As a consequence, (E) instability can explain the trade-off between detailed knowledge and generalization [5,8].