Artificial Neurons Bridge Bio-Electronic Gap

Bacteria Geobacter sulfurreducens came from humble beginnings; it was first isolated from the earth in a ditch in Norman, Oklahoma. But today, these surprisingly remarkable microbes hold the key to the first-ever artificial neurons capable of interacting directly with living cells.

G. sulfurreducens communicate with each other via tiny protein-based wires that researchers at the University of Massachusetts Amherst have harvested and used to make artificial neurons capable, for the first time, of processing information from living cells without an intermediary device amplifying or modulating the signals, the researchers say.

Although some artificial neurons already exist, they require electronic amplification to detect signals produced by our bodies, says Jun Yao, who works on bioelectronics and nanoelectronics at UMass Amherst. Amplification inflates both power consumption and circuit complexity, and thus counteracts the efficiency found in the brain.

Yao’s team’s neuron can understand signals from the body at their natural amplitude of about 0.1 volt. It’s “completely new,” says Bozhi Tian, ​​a biophysicist who studies living bioelectronics at the University of Chicago and was not involved in the work. This work “bridges the long-standing gap between electronic and biological signaling” and demonstrates an interaction between artificial neurons and living cells that Tian calls “unprecedented.”

Real neurons and artificial neurons

Biological neurons are the fundamental building blocks of the brain. If external stimuli are strong enough, charge builds up in a neuron, triggering an action potential, a voltage spike that runs through the neuron’s body to activate all types of bodily functions, including emotions and movements.

Scientists have been working for decades to design a synthetic neuron, pursuing the efficiency of the human brain, which until now seemed to elude the capabilities of electronics.

Yao’s group designed new artificial neurons that mimic the way biological neurons detect and respond to electrical signals. They use sensors to monitor external biochemical changes and memristors (essentially resistors with memory) to mimic the action potential process.

As the voltage from external biochemical events increases, the ions accumulate and begin to form a filament across a gap in the memristor, which in this case was filled with protein nanowires. If there is enough tension, the filament completely bridges the gap. Current passes through the device and the filament then dissolves, dispersing the ions and stopping the current. The entire process mimics the action potential of a neuron.

The team tested their artificial neurons by connecting them to heart tissue. The devices measured a baseline amount of cell contraction, which did not produce enough of a signal to trigger the artificial neuron. Next, the researchers took another measurement after the tissue was dosed with norepinephrine, a drug that increases the frequency of cell contraction. The artificial neurons only fired action potentials during the top drug trial, proving they can detect changes in living cells.

The experimental results were published on September 29 in Natural communications.

Natural nanowires

The group has G. sulfurreducens thank you for the breakthrough.

Microbes synthesize miniature cables, called protein nanowires, which they use for intra-species communication. These cables are charge conductors that survive for long periods of time in nature without breaking down. (Remember, they evolved for the ditches of Oklahoma.) They’re extremely stable, even for making devices, Yao says.

For engineers, the most remarkable property of nanowires is how efficiently ions move along them. Nanowires offered a low-energy way to transfer charges between human cells and artificial neurons, avoiding the need for a separate amplifier or modulator. “And surprisingly, the material is designed for this,” Yao says.

The group developed a method to cut the cables of bacterial bodies, purify the material and suspend it in a solution. They spread the mixture and let the water evaporate, leaving a thin film of one molecule made of protein nanowires.

This efficiency allows the artificial neuron to generate enormous energy savings. Yao’s group integrated the film into the memristor at the neuron’s core, lowering the energy barrier of the reaction that causes the memristor to respond to signals recognized by the sensor. With this innovation, the researchers say, the artificial neuron uses 1/10th the voltage and 1/100th the power of the others.

Chicago’s Tian believes this “extremely impressive” energy efficiency is “essential for future low-power, implantable, biointegrated computing systems.”

The power advantages make this synthetic neuron design attractive for all sorts of applications, the researchers say.

Responsive wearable electronic devices, such as prosthetics that adapt to the body’s stimuli, could use these new artificial neurons, Tian says. Ultimately, implantable systems that rely on neurons could “learn like living tissues, advancing personalized medicine and brain-inspired computing” to “interpret physiological states, leading to biohybrid networks that merge electronics with living intelligence,” he says.

Artificial neurons could also be useful in electronics outside of the biomedical field. Millions of them on a chip could replace transistors, performing the same tasks while reducing power consumption, Yao says. The neuron manufacturing process doesn’t involve high temperatures and uses the same type of photolithography that silicon chip makers use, he says.

Yao, however, points out two possible bottlenecks that producers could encounter when scaling these artificial neurons for electronics. The first is to obtain more protein nanowires from G. sulfurreducens. His lab is currently working for three days to generate just 100 micrograms of material, about the mass of a grain of table salt. And that quantity can only cover a very small device, so Yao wonders how this step in the process could be scaled up to production.

His other concern is how to achieve uniform film coating on the scale of a silicon wafer. “If you want to make small, high-density devices, film thickness uniformity is actually a critical parameter,” he explains. But the artificial neurons developed by his group are too small to perform meaningful uniformity tests at the moment.

Tian doesn’t expect artificial neurons to replace silicon transistors in conventional computing, but rather sees them as a parallel offering for “hybrid chips that merge biological adaptability with electronic precision,” he says.

In the distant future, Yao hopes that these bio-derived devices will also be appreciated for not contributing to electronic waste. When a user no longer wants a device, they can simply throw the biological component into the environment, Yao says, because it won’t pose an environmental hazard.

“By using this type of naturally occurring microbial material, we can create greener and more sustainable technology for the world,” says Yao.