Realization of Associative Memory in an Enzymatic Process: Toward Biomolecular Networks with Learning and Unlearning Functionalities.
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 bioinspired/memory-involving components in "networked" (concatenated) biomolecular processes for multisignal sensing and complex information processing.
§Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6197, United States.
Vera
V
Bocharova
Kevin
K
MacVittie
Soujanya
S
Chinnapareddy
Jan
J
Halámek
Vladimir
V
Privman
Evgeny
E
Katz
associative memory; biocomputing; biomolecular information processing; biomolecular network; enzyme; unconventional computing