Human brain cells on a chip learned to play Doom in a week

A Breakthrough in Biological Computing: Human Neurons Play Doom

A remarkable achievement in the realm of biological computing has been witnessed as a clump of human brain cells successfully played the iconic computer game Doom. While the performance of the neurons is not at par with that of humans, experts believe that this milestone brings biological computers closer to practical real-world applications, such as controlling robotic arms.

In a groundbreaking development in 2021, the Australian company Cortical Labs utilized neuron-powered computer chips to play the classic game Pong. These chips comprised clusters of over 800,000 living brain cells grown on microelectrode arrays capable of transmitting and receiving electrical signals. Researchers meticulously trained the chips to maneuver the paddles on the screen.

Building on this achievement, Cortical Labs has now introduced an interface that simplifies the programming of these chips using Python, a widely-used programming language. Taking advantage of this new interface, independent developer Sean Cole employed Python to teach the chips to engage in the complex gameplay of Doom, achieving this feat in just about a week.

Brett Kagan from Cortical Labs expressed his excitement over the rapid progress, stating, “Unlike the Pong work that we did a few years ago, which represented years of painstaking scientific effort, this demonstration has been done in a matter of days by someone who previously had relatively little expertise working directly with biology. It’s this accessibility and flexibility that makes it truly exciting.”

The neuronal computer chip, containing approximately a quarter of the neurons used in the Pong demonstration, exhibited gameplay in Doom surpassing that of a randomly firing player, although falling short of human-level performance. Nevertheless, it displayed a much quicker learning curve compared to traditional silicon-based machine learning systems and is expected to enhance its capabilities with advanced learning algorithms, as per Kagan.

Kagan emphasized the uniqueness of the biological system, stating, “Yes, it’s alive, and yes, it’s biological, but really what it is being used as is a material that can process information in very special ways that we can’t recreate in silicon.”

Andrew Adamatzky from the University of the West of England hailed the advancement, noting that successfully interacting with a complex game like Doom signifies significant progress in the control and training of living neural systems. Similarly, Steve Furber from the University of Manchester acknowledged the complexity of Doom as a notable step up from Pong, although acknowledging the mysteries surrounding how the neurons comprehend expectations and “see” the screen without visual organs.

Yoshikatsu Hayashi from the University of Reading highlighted the potential real-world applications of such advancements, such as utilizing biological computers to control robotic arms. He and his team are currently exploring similar endeavors with a biological computer constructed from hydrogel, comparing the gameplay in Doom to a simplified version of controlling an entire robotic arm.

Adamatzky concluded by emphasizing the significance of the biological system’s ability to handle complexity, uncertainty, and real-time decision-making, traits crucial for future biological or hybrid computers facing diverse challenges.