In a pioneering advance that blurs the line between biology and electronics, engineers at the University of Massachusetts Amherst (UMass) have announced the creation of the first artificial neurons that can communicate directly with living cells. The project, detailed in Nature Communications, employs protein nanowires derived from bacteria, enabling ultra-low voltage operation and unprecedented biocompatibility.
This breakthrough promises to accelerate progress in bio-inspired computing, brain–machine interfaces, and medical implants—ushering in a new era where electronics don’t just talk to living systems, they become part of them.
Neurons in the human body send and receive electrical impulses at remarkably low energy thresholds. One of the biggest challenges in biohybrid electronics has been recreating that sensitivity and efficiency in synthetic devices. Conventional artificial neurons or neuromorphic circuits often require higher voltages—orders of magnitude more than biological neurons do—and are poorly suited to direct interaction with living tissue.
To overcome this, the UMass team turned to protein nanowires produced by electricity-generating bacteria. These nanowires form conductive webs that can support ion and electron transfers at low voltages. The researchers integrated them into microcircuit architectures to build “neurons” that generate and propagate electrical spikes at about 0.1 volts—roughly the same as natural neurons in the body.
In tests, their artificial neurons exhibited behaviors analogous to basic excitatory and gating functions, and crucially, they could interface directly with living cells, allowing two-way communication. “Our brains process enormous data loads while consuming only a tiny fraction of the power needed by digital computers,” says Shuai Fu, lead author and a graduate researcher in electrical and computer engineering at UMass. “Mimicking that efficiency is one of our greatest challenges.”
Jun Yao, associate professor and senior author, adds that earlier synthetic neurons consumed ten times more voltage and 100 times more power than their new design. “We’ve narrowed that gap dramatically. At 0.1 V, we’re in the same ballpark as nature itself.”
The implications of this invention are profound across multiple fields:
- Biocompatible computing
Traditional electronic circuits face severe limitations when interfacing with biological tissues—issues of heat, power consumption, and signal mismatch. The UMass approach, built from biologically derived conductors, offers a gentler, more natural bridge. Devices based on such artificial neurons could potentially be implanted or integrated with living systems with minimal disruption. - Next-generation neural prosthetics & implants
In neuroprosthetics—devices designed to restore or mimic neural function—seamless interaction between manmade circuits and living neurons is critical. These protein-nanowire neurons may serve as intermediaries or scaffolds that communicate effectively with native nerve cells, enabling implants that feel more like natural extensions of the nervous system. - Biohybrid computing and neuromorphic systems
The artificial neuron design represents a step toward hybrid systems that combine biological and synthetic components. Combined with stem-cell-derived neurons or tissue cultures, such hybrid architectures may develop new classes of computing platforms—ones that compute with living materials. This is along the same trajectory as other ambitious efforts, such as the CL1 “biological computer” developed by Cortical Labs, which fuses human neurons with silicon hardware to create a biological computing substrate. - Drug discovery, cell modeling, disease simulation
Devices that can mimic neural behavior while interacting with real cells are powerful tools in neuroscience and pharmacology. One could imagine “testbeds” of tissue-coupled circuits that respond to drugs, toxins, or stimuli in lifelike ways, accelerating development of therapies for neurological disorders.
This advance sits within a wider movement toward fusing biology and computation. Only earlier this year, Cortical Labs launched the CL1, a system that fuses lab-grown human neurons onto silicon electronics, creating what they call a “synthetic biological intelligence.” The CL1 system is designed for research uses in modeling diseases and neuromorphic systems, and can sustain neuron cultures for months. Unlike purely electronic AI, the biological layer adapts, rewires, and learns in ways closer to organic brains.
Similarly, researchers elsewhere are exploring organic electrochemical neurons—flexible, printed circuits that use ions (rather than electrons) to mimic neural spiking behavior—and blending them with living tissues. These “soft” devices can operate at sub-1-volt scales and even interface with plant systems.
In another frontier, scientists have managed to recreate aspects of neural circuitry in vitro: In a breakthrough at Stanford, researchers combined multiple neuron types derived from human stem cells into a “sensory pain pathway” model. When exposed to stimuli like capsaicin, the circuit transmitted electrical waves mimicking pain signaling.
Researchers have also toyed with “hybrots”—robots whose control circuits are built from living neurons, forming a direct feedback loop between biology and machine. All these threads converge toward a future where the boundary between living and engineered intelligence is increasingly permeable.
Despite the promise, formidable challenges lie ahead.
- Longevity and stability
Living systems age and degrade. Even with nutrient delivery and maintenance systems, keeping synthetic-biohybrid circuits functional over years or decades is an enormous undertaking. The CL1 system, for instance, reportedly sustains neuron cultures up to about six months. - Control, signal accuracy, noise
Biological variability is high. Ensuring that artificial neurons reliably mimic precise firing patterns, resist drift, and resist interference is nontrivial. Cross-talk, biofouling, and immune responses in vivo may further complicate matters. - Ethical and philosophical considerations
As synthetic neurons become more biologically integrated, questions around sentience, consciousness, and moral status emerge. When do clusters of biohybrid circuitry cross a threshold into something more than “device”? Early-stage experiments will require careful oversight and regulatory frameworks. - Scalability and cost
Building thousands or millions of hybrid neurons at scale, with quality control and uniformity, is a huge engineering challenge. More so, making them economically viable for widespread application in medicine or computing will require breakthroughs in fabrication and materials. - Regulation and safety
Implantable systems merging living cells with electronics must meet safety standards, biocompatibility, sterility, and durability. Regulatory pathways for such hybrid devices remain underdeveloped.
If matured, this technology could transform computing, healthcare, and neural science.
One possible trajectory is brain–computer symbiosis: implantable modules that translate neural signals into digital formats and relay signals back, mediated by hybrid neurons that minimize energy loss and maximize fidelity.
In precision neuroscience, artificial neurons could monitor, stimulate, or modulate neural circuits in situ—serving as “therapeutic bridges” in neurodegenerative diseases, spinal injury, or epilepsy.
At a higher level, adaptive biohybrid computers may emerge, blending silicon logic, organic circuits, and living cells into systems that rethink what a “machine” is. Instead of passive processors, these could evolve, adapt, and rewire themselves dynamically.
Such machines might power novel AI that isn’t purely algorithmic, but augmented by living, plastic neural substrates. The CL1 model hints at that direction—though the UMass artificial neuron adds a design that’s more modular, low-power, and cell-compatible.
This development from UMass marks a milestone—creating artificial neurons that speak the same electrical language as biological ones, at comparable voltages, and communicating with living cells. It’s not just a scientific curiosity, but a foundation for a new class of hybrid devices that combine the best of biology and electronics.
While many challenges remain, the roadmap is tantalizing: smarter brain–machine interfaces, bio-integrated prosthetics, synthetic neural circuits for research and therapy, and biohybrid computing architectures. In decades to come, we may look back on this as the moment when electronics stopped being “other” and became part of life’s continuum.
