Scientists at Cortical Labs in Australia fitted a robotic dog with lab-grown neurons able to direct it toward a target on a simple map, using electrical signals. The demonstration extends biological computing into the physical world, offering a glimpse of the potential for more adaptive robots.
The technology involves growing neurons directly onto computer chips, forming a biological processor that promises energy-efficiency advantages over conventional systems. The neurons are stimulated with electrodes that provide two-way electrical signals, with their activity translated into the robot’s movements.
Feedback loops of electrical signals were used to get the robot to its target. Brett Kagan, co-founder and CEO of Cortical Labs, said "The robotic dog is a simple demonstration of how progress in biological systems can also be applied into the real world, but it helps make the opportunity tangible." He noted that "Robots that are becoming remarkably capable machines at their physical control, still struggle with the higher order control required to learn quickly or adapt when conditions change."
Cortical Labs has previously demonstrated neurons playing computer games like Pong and Doom. The new robot extends this concept into the physical world. In partnership with Honda Research Institute Europe, a similar experiment was run virtually, testing almost 1,300 different signal combinations across over 4,000 hours of interactions.
Daniel Tanneberg, a Senior Scientist at Honda Research Institute Europe, said "This research collaboration enables us to investigate fundamentally different approaches to intelligent agents. Using living cells as the core computational substrate comes with many challenges but also offers great potential in terms of energy efficiency, robustness, and adaptation – potential that we can now begin to explore and evaluate."
Johnson Zhou, a Research Software Engineer at Cortical Labs, said "The challenge is not simply growing neurons on silicon: It is finding reliable ways to communicate with biological systems, train them and understand which approaches produce consistent results. This research gives us a framework for testing those questions at scale. It establishes a foundation we can build on as biological computing moves towards practical applications."
The navigation research has been presented at the NeurIPS 2026 conference and is available on arXiv, though it has not yet been peer-reviewed. Future goals include scaling up these chips to handle more complex tasks and understanding how the neuron-based chips retain information.
Analysis
Why This Matters
- This development shows progress in biological computing, which could lead to more energy-efficient and adaptable robots.
- It offers an alternative to traditional AI systems for tasks in unpredictable environments.
- The approach could have applications in remote or hazardous conditions, or in systems that learn over time.
Background
Cortical Labs has been working on growing neurons on chips, previously demonstrating them playing games. This latest experiment extends their work into robotics. The partnership with Honda Research Institute Europe explored similar concepts in a virtual environment.
Key Perspectives
Brett Kagan, Cortical Labs: sees the robot dog as tangible progress in biological systems, with potential for real-world applications in autonomous systems.
Daniel Tanneberg, Honda Research Institute Europe: highlights the potential of living cells for energy efficiency and adaptation in intelligent agents.
Johnson Zhou, Cortical Labs: emphasizes the challenges of communicating with biological systems and the importance of developing reliable methods.
What to Watch
- Whether the technology can be scaled up to handle more complex tasks in real-world environments.
- How researchers learn about memory in neuron-based chips.
- Potential commercial applications if the approach becomes more efficient.
Checked
12 claims in this story checked against 1 source: 12 supported.
Show each claim
- SupportedThe headline says Cortical Labs fitted a robot dog with human brain cells.ScienceAlert: “Scientists Have Built a Robot Dog Powered by Human Brain Cells.”
- SupportedThe summary says the demonstration highlights the potential for energy-efficient, adaptable biological computing.ScienceAlert: “Using living neurons as the foundation of computer chips promises to bring significant advantages over conventional systems in terms of both energy efficiency and adaptability”
- SupportedScientists at Cortical Labs in Australia fitted a robotic dog with lab-grown neurons that could direct it toward a target on a simple map using electrical signals.ScienceAlert: “scientists at Cortical Labs in Australia, who have fitted out a robotic dog with neurons grown in the lab that are able to direct it towards a target on a simple map. By growing the neurons right on the chip, and fitting it with electrodes that provide two-way electrical signaling”
- SupportedThe technology grows neurons on computer chips and promises energy-efficiency advantages over conventional systems.ScienceAlert: “Using living neurons as the foundation of computer chips promises to bring significant advantages over conventional systems in terms of both energy efficiency and adaptability”
- SupportedElectrodes provide two-way electrical signals, and the neurons’ activity was translated into the robot’s movements.ScienceAlert: “fitting it with electrodes that provide two-way electrical signaling, the Cortical Labs team was able to translate activity in the small group of neurons into movement for the attached robot.”
- SupportedFeedback loops of electrical signals were used to get the robot to its target.ScienceAlert: “Feedback loops of electrical signals were used to get the robot to its target.”
- SupportedBrett Kagan said, “The robotic dog is a simple demonstration of how progress in biological systems can also be applied into the real world, but it helps make the opportunity tangible.”ScienceAlert: “"The robotic dog is a simple demonstration of how progress in biological systems can also be applied into the real world, but it helps make the opportunity tangible," says Brett Kagan, the co-founder and CEO of Cortical Labs.”
- SupportedBrett Kagan said, “Robots that are becoming remarkably capable machines at their physical control, still struggle with the higher order control required to learn quickly or adapt when conditions change.”ScienceAlert: “"Robots that are becoming remarkably capable machines at their physical control, still struggle with the higher order control required to learn quickly or adapt when conditions change," says Kagan.”
- SupportedCortical Labs has previously demonstrated neurons playing Pong and Doom.ScienceAlert: “Cortical Labs has already demonstrated clusters of neurons completing computer tasks, including playing the games Pong and Doom”
- SupportedA similar experiment was run virtually with Honda Research Institute Europe, testing almost 1,300 signal combinations over more than 4,000 hours of interactions.ScienceAlert: “A similar technology demonstration has also been run by Cortical Labs in partnership with Honda Research Institute Europe. In this demo, everything was run inside a virtual system”
- SupportedDaniel Tanneberg said, “This research collaboration enables us to investigate fundamentally different approaches to intelligent agents. Using living cells as the core computational substrate comes with many challenges but also offers great potential in terms of energy efficiency, robustness, and adaptation – potential that we can now begin to explore and evaluate.”ScienceAlert: “"This research collaboration enables us to investigate fundamentally different approaches to intelligent agents," says Daniel Tanneberg, a Senior Scientist at Honda Research Institute Europe. "Using living cells as the core computational substrate comes with many challenges but also offers great potential in terms of energy efficiency, robustness, and adaptation – potential that we can now begin to explore and evaluate."”
- SupportedJohnson Zhou said, “The challenge is not simply growing neurons on silicon: It is finding reliable ways to communicate with biological systems, train them and understand which approaches produce consistent results. This research gives us a framework for testing those questions at scale. It establishes a foundation we can build on as biological computing moves towards practical applications.”ScienceAlert: “"The challenge is not simply growing neurons on silicon: It is finding reliable ways to communicate with biological systems, train them and understand which approaches produce consistent results," says Johnson Zhou, a Research Software Engineer at Cortical Labs. ... "It establishes a foundation we can build on as biological computing moves towards practical applications."”
