Scientists at the USC Viterbi School of Engineering and the School of Advanced Computing have created artificial neurons that reproduce the intricate electrochemical behavior of real brain cells. The discovery, published in Nature Electronics, marks a major milestone in neuromorphic computing, a field that designs hardware modeled after the human brain. This advancement could shrink chip sizes by orders of magnitude, cut energy use dramatically, and push artificial intelligence closer to achieving artificial general intelligence.
Unlike digital processors or earlier neuromorphic chips that only simulate brain activity through mathematical models, these new neurons physically reproduce how real neurons operate. Just as natural brain activity is triggered by chemical signals, these artificial versions use actual chemical interactions to start computational processes. This means they are not just symbolic representations but tangible recreations of biological function.
A New Class of Brain-Like Hardware
The research, led by Professor Joshua Yang of USC's Department of Computer and Electrical Engineering, builds on his earlier pioneering work on artificial synapses more than a decade ago. The team's new approach centers on a device called a "diffusive memristor." Their findings describe how these components could lead to a new generation of chips that both complement and enhance traditional silicon-based electronics. While silicon systems rely on electrons to perform computations, Yang's diffusive memristors use the motion of atoms instead, creating a process that more closely resembles how biological neurons transmit information. The result could be smaller, more efficient chips that process information the way the brain does and potentially pave the way toward artificial general intelligence (AGI).
In the brain, both electrical and chemical signals drive communication between nerve cells. When an electrical impulse reaches the end of a neuron at a junction called a synapse, it converts into a chemical signal to transmit information to the next neuron. Once received, that signal is converted back into an electrical impulse that continues through the neuron. Yang and his colleagues have replicated this complex process in their devices with striking accuracy. A major advantage of their design is that each artificial neuron fits within the footprint of a single transistor, whereas older designs required tens or even hundreds.
In biological neurons, charged particles known as ions help create the electrical impulses that enable activity in the nervous system. The human brain relies on ions such as potassium, sodium, and calcium to make this happen.
Using Silver Ions to Recreate Brain Dynamics
In the new study, Yang -- who also directs the USC Center of Excellence on Neuromorphic Computing -- used silver ions embedded in oxide materials to generate electrical pulses that mimic natural brain functions. These include fundamental processes like learning, movement, and planning.
"Even though it's not exactly the same ions in our artificial synapses and neurons, the physics governing the ion motion and the dynamics are very similar," says Yang.
Yang explains, "Silver is easy to diffuse and gives us the dynamics we need to emulate the biosystem so that we can achieve the function of the neurons, with a very simple structure." The new device that can enable a brain-like chip is called the "diffusive memristor" because of the ion motion and the dynamic diffusion that occurs with the use of silver.
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