Together with experimental physicists at Sogang University in South Korea, we presented an artificial iontronic synapse that we succesfully applied as a computing element for neuromorphic reservoir computing. This synapse works with water and ions and for the first time shows that a system using the same medium as our brains can process complex information in a brain-like way. The results appeared in the journal Proceedings of the National Academy of Sciences.
The brain’s computing principles (neurons connected by synapses) and information carriers (ions in water) both differ fundamentally from those of conventional computers. Building on this distinction, we present an aqueous memristor that emulates the brain’s short-term synaptic plasticity features through ion transport in water, mirroring the natural processes in the brain. This device, which is inspired by and understood through a theoretical model, is applied as a synaptic element for reservoir computing, a brain-inspired machine learning framework. Thus we implement a brain-inspired computing element in a brain-inspired fluidic medium, representing a considerable step toward computing devices that proverbially both walk and talk like the brain.
The work is nicely described by this news item from the UU:
The paper has also been selected to appear in the PNAS Showcase: