Scientists Build Living Robots With Nervous Systems

2026-04-02 · Source: IEEE Spectrum · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Expert, short

Summary

Researchers have developed "neurobots," free-swimming assemblages of living cells that self-organize into systems with functional neural circuits, as reported in *Advanced Science*. These biological machines, an evolution of earlier xenobots, are built from frog cells but incorporate neurons that mature from stem cells, forming branching connections that relay electrochemical signals. Unlike non-neural counterparts or static brain organoids, neurobots exhibit internally guided motions, exploring their environment and responding to neuroactive drugs with distinct looping and spiraling paths. This development aims to provide a model for understanding how simple neural networks generate complex behaviors, with potential applications in precision tissue repair, environmental cleanup, and the integration of biological tissue with engineered control systems. The technology is being advanced by Tufts University biologist Michael Levin and collaborators, including through the commercial startup Fauna Systems.

Key takeaway

For AI Scientists and Research Scientists exploring bio-integrated systems, this neurobot development signals a shift from biomimicry to direct bioengineering. You should consider how these internally controlled biological machines could serve as dynamic models for understanding neural network emergence and for developing future cyborg systems. Your research could leverage neurobots to investigate complex adaptive behaviors or to prototype novel bio-sensing applications, pushing beyond purely mechanical biological machines.

Key insights

Neurobots integrate living cells with functional neural networks to create self-organizing, motile biological machines.

Principles

• Biological systems can self-organize into novel forms.
• Neural integration enables complex, adaptive behaviors.
• Emergent order can arise from simple cellular clusters.

Method

Neurobots are constructed from frog cells and partially differentiated stem cells, which mature into neurons that form branching connections throughout the autonomous cellular clusters, enabling electrochemical signaling and coordinated movement.

In practice

• Use neurobots to study neural network behavior.
• Explore neurobots for targeted tissue repair.
• Apply biobots for environmental sensing and cleanup.

Topics

• Neurobots
• Living Robots
• Neural Networks
• Xenobots
• Bioengineering

Best for: AI Scientist, Research Scientist, Robotics Engineer

Related on AIssential

• Leiden scientists 3D-print microrobots that “swim” without a brain — Microrobots can achieve complex navigation through physical design and environmental feedback, not just electronics.
• Robots run this laboratory in Japan — and are changing how scientists work — AI-powered laboratory robots can autonomously manage complex biological experiments, accelerating discovery and freeing human researchers.
• IEEE Transactions on Cognitive and Developmental Systems, Volume 18, Issue 1, February 2026 — The issue highlights advancements in embodied intelligence, human-robot interaction, and cognitive AI systems.
• Princeton builds bio-hybrid computer using living neurons — A 3D bio-hybrid computer integrates living neurons with electronics to create energy-efficient, pattern-recognizing neural networks.
• Neuromorphic Spikes Unify Control and Decision Making — Neuromorphic spikes unify continuous and discrete control, enabling efficient, event-based machine intelligence.
• A neural blueprint for human-like intelligence in soft robots — A neural-inspired AI control system enables soft robots to learn once and adapt instantly to diverse tasks and disturbances.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by IEEE Spectrum.