Artificial Neuron as a Base for Electronic Memories

Scientists have developed a new artificial ionic neuron that may aid in implementing simple learning algorithms that would serve as the basis for tomorrow’s electronic memories.

Harnessing the Brain’s superpower through electronic gadgets has attracted multiple pieces of research. One of the basic principles by which neurons (brain cells) transmit information is by the passage of ions.

A new device made of a single layer of water transporting ions within graphene nanoslits has been developed with the same transmission capacity as a neuron, by the scientists from CNRS and the Ecole Normale Supérieure – PSL, published in the journal Science.

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‘Scientists have developed a new artificial ionic neuron that may aid in implementing simple learning algorithms that would serve as the basis for tomorrow’s electronic memories. ’

Neurons are highly energy efficient which works by opening and closing ion channels according to the stimuli received. The resulting ion flows create an electric current responsible for the emission of action potentials, signals that allow neurons to communicate with each other.

The Artificial Memory

However reciprocating these functions through artificial intelligence costs lots of energy consumption almost tens of thousands of times that of the human brain. The study team was thereby challenged to design electronic systems using ions to carry the information.

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The device worked on a property known as the memristor effect, i.e., under the effect of an electric field, the ions from the layer of water assemble into elongated clusters and these clusters retain some of the stimuli that have been received in the past (as similar to a memory in brain).

Moreover, using theoretical and digital tools, the study team has also shown how to assemble these clusters to reproduce the physical mechanism of emission of action potentials, and thus the transmission of information.

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The team continues to work on this theoretical work to prove experimentally that such systems can implement simple learning algorithms that can serve as the basis for tomorrow’s electronic memories.

Source-Medindia