Artificial neurons successfully communicate with living brain cells
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Artificial neurons successfully communicate with living brain cells
Printed artificial neurons that can “talk” to the brain could revolutionize both neurotechnology and energy-hungry AI.
Date:
April 18, 2026
Source:
Northwestern University
Summary:
Engineers at Northwestern University have taken a striking leap toward merging machines with the human brain by printing artificial neurons that can actually communicate with real ones. These flexible, low-cost devices generate lifelike electrical signals capable of activating living brain cells, a breakthrough demonstrated in mouse brain tissue.
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An aerosol jet printer in Hersam's laboratory deposits electronic inks onto a flexible polymer substrate. Credit: Mark Hersam/Northwestern University
Engineers at Northwestern University have created printed artificial neurons that go beyond imitation and can directly interact with real brain cells. These flexible, low-cost devices produce electrical signals that closely resemble those generated by living neurons, allowing them to activate biological brain tissue.
In experiments using slices of mouse brain, the artificial neurons successfully triggered responses in real neurons. This result shows a new level of compatibility between electronic devices and living neural systems.
Toward Brain Interfaces and Energy-Efficient AI
This advance moves researchers closer to electronics that can directly interface with the nervous system. Potential uses include brain-machine interfaces and neuroprosthetics, such as implants that could help restore hearing, vision, or movement.
The technology also points toward a new generation of computing systems inspired by the brain. By replicating how neurons communicate, future hardware could perform complex tasks using far less energy. The brain remains the most energy-efficient computing system known, and scientists hope to apply its principles to modern technology.
The study will be published on April 15 in the journal Nature Nanotechnology.
"The world we live in today is dominated by artificial intelligence (AI)," said Northwestern's Mark C. Hersam, who led the study. "The way you make AI smarter is by training it on more and more data. This data-intensive training leads to a massive power-consumption problem. Therefore, we have to come up with more efficient hardware to handle big data and AI. Because the brain is five orders of magnitude more energy efficient than a digital computer, it makes sense to look to the brain for inspiration for next-generation computing."
Hersam is an expert in brain-inspired computing and holds multiple roles at Northwestern University, including the Walter P. Murphy Professor of Materials Science and Engineering at the McCormick School of Engineering. He also is a professor of medicine at Northwestern University Feinberg School of Medicine and a professor of chemistry at the Weinberg College of Arts and Sciences. In addition, he serves as chair of the department of materials science and engineering, director of the Materials Research Science and Engineering Center, and a member of the International Institute for Nanotechnology. He co-led the study with Vinod K. Sangwan, a research associate professor at McCormick.
Why the Brain Outperforms Traditional Silicon
Modern computers handle increasing workloads by packing billions of identical transistors onto rigid, two-dimensional silicon chips. Each component behaves the same way, and once manufactured, the system remains fixed.
The brain works very differently. It consists of many types of neurons, each with specialized roles, arranged in soft, three-dimensional networks. These networks are constantly changing, forming and adjusting connections as learning occurs.
"Silicon achieves complexity by having billions of identical devices," Hersam said. "Everything is the same, rigid and fixed once it's fabricated. The brain is the opposite. It's heterogeneous, dynamic and three-dimensional. To move in that direction, we need new materials and new ways to build electronics."
Although artificial neurons have been developed before, most produce overly simple signals. To achieve more complex behavior, engineers typically need large networks of devices, which increases energy use.
Printable Materials Enable Brain-Like Behavior
To better replicate real neural activity, Hersam's team built artificial neurons using soft, printable materials that more closely match the brain's structure. Their approach relies on electronic inks made from nanoscale flakes of molybdenum disulfide (MoS2), which acts as a semiconductor, and graphene, which serves as an electrical conductor. These materials were deposited onto flexible polymer surfaces using aerosol jet printing.
Previously, researchers treated the polymer in these inks as a flaw because it interfered with electrical performance. As a result, they r