Scientists Build Living Robots With Nervous Systems

Engineers have long tried to mimic life. They’ve built machine learning algorithms modeled after the human brain, designed machines that walk like dogs or fly like insects, and taught robots to adapt, however clumsily, to the world around them.

Now they are skipping imitation altogether.

Instead of taking inspiration from biology, they are building robots out of it: fashioning tiny, free-swimming assemblages of living cells that organize into self-directed systems, complete with neurons that wire themselves into functional circuits.

The result, reported last month in Advanced Science, is what the researchers call a “neurobot.”

These living machines could help scientists better understand how simple neural networks give rise to complex behaviors, a foundational step toward building cyborg systems that integrate biological tissue with engineered control. And with further refinement, they could be put to use in applications ranging from precision tissue repair to environmental cleanup.

“My general reaction is, ‘Wow, this is amazing!’ ” says Kate Adamala, a synthetic biologist at the University of Minnesota Twin Cities, who was not involved in the research. “This truly puts the engineering component into bioengineering.”

Toward Internal Control

Neurobots mark the latest advance in a series of increasingly sophisticated biological machines developed by Tufts University biologist Michael Levin and his collaborators.

First described in 2020, these clusters of living cells, when removed from their normal developmental context and cultured in simple saline conditions, spontaneously self-organize in such a manner that they move and act in novel ways. Under the microscope, they look like irregular, translucent blobs of tissue, but their coordinated motion reveals an emergent order that is unlike anything found in the natural world.

“These things don’t occur naturally,” says Carlos Gershenson, a computer scientist at Binghamton University, State University of New York, who studies artificial life and complex systems but was not involved in the neurobot research. “They’re made with natural cells, but we’re the ones arranging them.”

The earliest examples of this technology, called xenobots, were built from frog-derived tissues and mainly from a single type of structural cell. Despite the simplicity of their construction, however, they could propel themselves through water using beating hair-like projections called cilia. They survived for days without added nutrients. And they could repair minor damage, all without any scaffolding materials or genetic manipulation. Some could even self-replicate by spontaneously sweeping up loose stem cells.

Still, for all the novelty of these biological machines, their behavior was essentially mechanical. Their movements were driven by anatomy and physics, not by anything resembling internal control. They could sense chemical cues, change direction accordingly, and even retain traces of past experiences, as detailed in a preprint posted 17 March on bioRxiv.

But many other simple organisms—fungi, protists, and bacteria included—can do much the same. To achieve more flexible, coordinated behavior, they would need a way to integrate information across the body and dynamically direct their actions. Neurobots begin to provide that missing layer of control.

Small tufts of hairlike cilia, combined with the neurobot’s nervous system, allow it to move on its own. Haleh Fotowat

Linking Neural Activity to Action

Like earlier xenobots, neurobots are still built from frog cells, but they are now endowed with neurons that mature from partially differentiated stem cells. These nerve cells develop alongside structural tissues, forming branching connections throughout the autonomous beings. This means they can relay electrochemical signals from cell to cell.

And unlike other laboratory models of the nervous system—brain organoids, say, or lab-on-a-chip technologies—neurobots move. They swim, explore, and respond to their surroundings in ways that tie electrical signaling to observable movement, producing patterns of physical activity distinct from their non-neural counterparts.

Neurobots spend less time idling and more time exploring. They also trace looping and spiraling paths rather than repeating simple trajectories. And they respond differently to neuroactive drugs.

If the organizing principles that enable these internally guided motions and reflexes can now be deciphered, they could then be harnessed to produce more predictable biological functions, says Haleh Fotowat, a neuroengineer from Harvard’s Wyss Institute for Biologically Inspired Engineering, who collaborated with Levin’s team on the study.

“We’re still very early in terms of understanding the system and its capabilities.” But once the scientists understand how the neurobots self-organize, she says, “then we can begin to engineer on top of that.”

Beyond the practical, neurobots also raise deeper epistemological questions about the nature of biological organization, notes Levin. “Where does form and function come from in the first place?” he asks. “When it’s not evolved and it’s not engineered, where do these patterns come from?”

“This is a model system for asking those kinds of questions,” Levin says—in frog and human constructs alike.

From Discovery to Deployment

Among the many variations on the biobot theme are “anthrobots,” built from clusters of human lung cells instead of frog tissue.

Levin’s team now plans to add human neural cells to their anthrobots, extending the neurobot framework into a fully human context. Then, through further conditioning and guided learning, these living machines—like dogs trained to sniff for bombs—may become capable of adapting their behavior in predictable ways.

“The hope would be that you could teach them or train them to do what you want them to do,” says Josh Bongard, a computer scientist and roboticist at the University of Vermont.

Bongard was not involved in the neurobot study but is a frequent collaborator of Levin’s. Together, they cofounded the nonprofit Institute for Computationally Designed Organisms and a commercial startup, Fauna Systems, to advance biobot-related technologies.

According to Fauna CEO Naimish Patel, the company is initially targeting environmental sensing applications, aiming to deploy xenobots in settings such as aquaculture, wastewater monitoring, and pollutant detection, where the technology’s ability to integrate multiple signals could provide an early readout of ecosystem health.

If the xenobots encounter a mixture of stressors—say, elevated heavy metals, shifts in pH, and traces of agricultural runoff—their collective changes in movement or activity could provide a sensitive, real-time signal that something in the environment is amiss.

Precedent for this idea comes from Poland, where many cities already use freshwater mussels as living sentinels of water quality, wired with sensors that register when the animals clamp their shells shut in response to pollutants. Xenobots could extend this concept further, Patel says, potentially offering greater sensitivity and specificity by integrating multiple environmental cues into a single, measurable behavioral response. And neurobots could eventually push this fusion of sensing and computation into ever more sophisticated territory, he adds.

But the technical hurdles remain substantial—and the practical opportunities with simpler, non-neural versions are already compelling—so the first-gen xenobots, for the time being, remain the focus of Fauna’s initial product-development efforts, Patel says. “Right now, we’re looking for the intersection between unmet commercial need and emerging capability.”