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Feb 27, 2017

An ultra-low-power artificial synapse for neural-network computing

Posted by in categories: computing, neuroscience

(Left) Illustration of a synapse in the brain connecting two neurons. (Right) Schematic of artificial synapse (ENODe), which functions as a transistor. It consists of two thin, flexible polymer films (black) with source, drain, and gate terminals, connected by an electrolyte of salty water that permits ions to cross. A voltage pulse applied to the “presynaptic” layer (top) alters the level of oxidation in the “postsynaptic layer” (bottom), triggering current flow between source and drain. (credit: Thomas Splettstoesser/CC and Yoeri van de Burgt et al./Nature Materials)

Stanford University and Sandia National Laboratories researchers have developed an organic artificial synapse based on a new memristor (resistive memory device) design that mimics the way synapses in the brain learn. The new artificial synapse could lead to computers that better recreate the way the human brain processes information. It could also one day directly interface with the human brain.

The new artificial synapse is an electrochemical neuromorphic organic device (dubbed “ENODe”) — a mixed ionic/electronic design that is fundamentally different from existing and other proposed resistive memory devices, which are limited by noise, required high write voltage, and other factors*, the researchers note in a paper published online Feb. 20 in Nature Materials.

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