Synaptic Transistor Mimics Behavior of the Human Brain by Learning

Scientists have made a huge step toward creating more efficient and capable supercomputers. They've designed a new type of transistor that mimics the behavior of a synapse in a human brain. The novel device simultaneously modulates the flow of information in a circuit and physically adapts to changing signals.

"The transistor we've demonstrated is really an analog to the synapse in our brains," said Jian Shi, co-lead author of the new study, in a news release. "Each time a neuron initiates an action and another neuron reacts, the synapse between them increases the strength of its connection. And the faster the neurons spike each time, the stronger the synaptic connection. Essentially, it memorizes the action between the neurons."

How does this new transistor work? While calcium ion and receptors effect a change in a biological synapse, the artificial version achieves the same plasticity with oxygen ions. Votage is applied and these ions slip in and out of the crystal lattice of a very thin film of samarium nickelate, which acts as the synapse channel between two platinum "axon" and "dendrite" terminals. The varying concentration of ions in the nickelate raises or lowers its conductance (its ability to carry information on an electrical current) and the strength of the connection depends on the time delay in the electrical signal.

The new synaptic transistor has several advantages over traditional silicon transistors. First off, it's not restricted to the binary system of ones and zeros. In addition, it has a non-volatile memory. This means that even when power is interrupted, the device remembers its state. It's also inherently energy efficient; the nickelate belongs to an unusual class of materials, called correlated electron systems, that can undergo an insulator-metal transition.

That said, it will be quite some time before these transistors are employed in devices on a regular basis. However, the proof-of-concept device does show the potential for the transistors in the future.

"This kind of proof-of-concept demonstration carries that work into the 'applied' world, where you can really translate these exotic electronic properties into compelling, state-of-the-art devices." said Shriram Ramanathan, one of the researchers, in a news release.

The findings are published in the journal Nature Communications.