Realization of Associative Memory in an Enzymatic Process: Towards Biomolecular Networks with Learning and Unlearning Functionalities

TL;DR

This paper demonstrates an enzymatic biochemical system that mimics associative memory, capable of learning and unlearning responses to chemical inputs, paving the way for bio-inspired information processing in biomolecular networks.

Contribution

It introduces a novel enzymatic system that exhibits associative learning and unlearning, integrating biochemical reactions with memory functionalities.

Findings

The system responds to inputs with chemical signals.

It can learn associations through a training process.

It can unlearn responses after repeated exposure.

Abstract

We report a realization of an associative memory signal/information processing system based on simple enzyme-catalyzed biochemical reactions. Optically detected chemical output is always obtained in response to the triggering input, but the system can also "learn" by association, to later respond to the second input if it is initially applied in combination with the triggering input as the "training" step. This second chemical input is not self-reinforcing in the present system, which therefore can later "unlearn" to react to the second input if it is applied several times on its own. Such processing steps realized with (bio)chemical kinetics promise applications of bio-inspired/memory-involving components in "networked" (concatenated) biomolecular processes for multi-signal sensing and complex information processing.