Scientists create flexible artificial brain synapse for AI

Researchers at the University of Southern California have developed an artificial brain synapse capable of simulating a fundamental function of the human nervous system: the release of inhibitory and stimulatory signals from the same “pre-synaptic” terminal.

The synaptic device can reconfigure itself based on voltages applied at the input terminal of the device. A junction made of black phosphorus and tin selenide enables switching between the excitatory and inhibitory signals, the study said.

It is flexible and versatile, which is highly desirable in artificial neural networks. In addition, the artificial synapses may simplify the design and functions of nervous system simulations, according to the study published in the journal ACS Nano.

One of the greatest challenges facing artificial intelligence development is understanding the human brain and figuring out how to mimic it.

The human nervous system is made up of over 100 trillion synapses, structures that allow neurons to pass electrical and chemical signals to one another. In mammals, synapses can initiate and inhibit biological messages. Many synapses just relay one type of signal, while others can convey both types simultaneously or can switch between the two.

In order to develop artificial intelligence systems that better mimic human learning, cognition and image recognition, researchers are imitating synapses in the lab with electronic components. Most current artificial synapses, however, are only capable of delivering one type of signal.

USC’s Han Wang, Jing Guo and colleagues sought to create an artificial synapse that can send stimulatory and inhibitory signals.

The researchers developed a synaptic device that can reconfigure itself based on voltages applied at the input terminal of the device. A junction made of black phosphorus and tin selenide enables switching between the excitatory and inhibitory signals.

This new device is flexible and versatile, which is highly desirable in artificial neural networks. In addition, the artificial synapses may simplify the design and functions of nervous system simulations, the authors said.

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By: David Beasley, Earth.com Staff Writer

Source: American Chemical Society