Brain Organoids Trained to Solve Tasks

Researchers demonstrate first rigorous academic demonstration of goal-directed learning in lab-grown brain organoids

Published on Feb. 27, 2026

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Researchers at the University of California, Santa Cruz, have trained brain organoids, tiny pieces of brain tissue grown in the lab, to solve the "inverted pendulum" or "cart-pole" problem, a fundamental benchmark used in robotics, control theory, and artificial intelligence. By using electrical signals to send and receive information from the organoids, the researchers' software coached the lab-grown brain tissue to significantly improve its performance at the cart-pole problem.

Why it matters

This research aims to uncover how information is transmitted in the brains of complex organisms through the electrical spiking of neurons in such a way that they can learn to get better at tasks, and has implications for basic science and health research. Understanding how complex neural circuits function and adapt could provide a powerful new tool for studying how neurological conditions can change or impair the brain's capacity to learn.

The details

The research team, associated with the Braingeneers group within the UC Santa Cruz Genomics Institute, set out to understand if the organoid neurons could succeed at the cart-pole task. Using organoids derived from mouse stem cells and an electrophysiology system, the researchers use electrical simulation to send and receive information to and from neurons. By using stronger or weaker signals, they communicate to the organoid the angle of the pole, which exists in a virtual environment, as it falls in one direction or the other. The researchers observe the organoid's progress in five-episode increments, and if the organoid does not improve, it receives a training signal through an AI algorithm called reinforcement learning.

  • The researchers observe the organoid's progress in five-episode increments.
  • After balancing the pole over many episodes for 15 minutes, the organoid rests for 45 minutes, and the researchers found that after this rest period, the organoid's performance drops back to baseline.

The players

Ash Robbins

Baskin School of Engineering Electrical and Computer Engineering (ECE) Ph.D. student at the University of California, Santa Cruz.

Mircea Teodorescu

ECE Professor at the University of California, Santa Cruz.

David Haussler

Distinguished Professor of Biomolecular Engineering at the University of California, Santa Cruz.

Keith Hengen

Associate professor of biology at Washington University in St. Louis.

Steve Potter

Researcher at Caltech and Georgia Tech who conducted foundational work on the cart-pole task decades earlier.

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What they’re saying

“We're trying to understand the fundamentals of how neurons can be adaptively tuned to solve problems. If we can figure out what drives that in a dish, it gives us new ways to study how neurological disease can affect the brain's capacity to learn.”

— Ash Robbins, Baskin School of Engineering Electrical and Computer Engineering (ECE) Ph.D. student

“These are incredibly minimal neural circuits. There's no dopamine, no sensory experience, no body to sustain, no goals to pursue. And yet, when given targeted electrical feedback, this tissue is plastic enough and structured enough to be pushed toward solving a real control problem. That tells us something important: the capacity for adaptive computation is intrinsic to cortical tissue itself, separate from all the scaffolding we usually assume is necessary.”

— Keith Hengen, Associate professor of biology

“From an engineering perspective, what makes this powerful is that we can measure, stimulate, and adapt in the same system. This is not just recording neural activity. It is a closed-loop bioelectrical interface where the tissue's response directly shapes the next input. That is what allows us to study learning as a physical process, which has been very difficult to study directly in intact brains.”

— Mircea Teodorescu, ECE Professor

“You could think of it like an artificial coach that says, 'you're doing it wrong, tweak it a little bit in this way.' We're learning how to best give it these coaching signals.”

— Ash Robbins, Baskin School of Engineering Electrical and Computer Engineering (ECE) Ph.D. student

“It is likely that more sophisticated organoids, perhaps grown to include multiple brain regions involved in animal learning, will be needed to recapitulate the kind of long-term adaptive performance improvement we see in animals”

— David Haussler, Distinguished Professor of Biomolecular Engineering

What’s next

The researchers are interested in further exploring why their coaching technique works—which neurons are best to target, which training signals might work best, and how long-term learning may arise.

The takeaway

This research demonstrates the potential of using brain organoids to study the fundamental mechanisms of how neurons can learn and adapt, which could provide new insights into neurological conditions and how the brain functions. The development of open-source software to enable more researchers to conduct these types of experiments could accelerate progress in this field.