In vitro neurons learn and exhibit sentience when embodied in a simulated game-world
TL;DR
Imagine taking brain cells from humans and mice, growing them in a petri dish, and then connecting them to a computer so they can play the classic video game Pong. That's essentially what these researchers did. They created a system called 'DishBrain' where real neurons (brain cells) were hooked up to electrodes that could both send signals to the cells and read their electrical activity. When the 'paddle' hit the ball in Pong, the cells got predictable feedback, but when they missed, the feedback was chaotic and unpredictable. Amazingly, within just 5 minutes, these brain cells learned to play better - they got better at keeping the ball in play. The cells essentially figured out that hitting the ball led to orderly, predictable signals, while missing led to chaos, so they adapted their behavior to hit the ball more often.
Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game "Pong." Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.
- 1In vitro cortical neurons from both human (hiPSC-derived) and mouse (primary E15.5) sources demonstrated significant learning within five minutes of real-time gameplay in a simulated Pong environment, as measured by increased average rally length over time.
- 2Closed-loop feedback was essential for learning: cultures receiving structured stimulus feedback (predictable on hit, unpredictable on miss) outperformed those with silent feedback or no feedback, demonstrating that information alone is insufficient to drive learning.
- 3Human cortical cells initially performed worse than controls but ultimately outperformed mouse cortical cells at the second timepoint, providing preliminary empirical evidence that human neurons may have superior information-processing capacity.
- 4Electrophysiological analysis revealed that gameplay increased functional plasticity, strengthened sensory-motor cross-correlations, and reduced information entropy during predictable exchanges, while unpredictable feedback increased entropy, consistent with the free energy principle.
- 5The DishBrain system demonstrated that monolayers of neurons can self-organize firing activity in a goal-directed manner through closed-loop embodiment, representing the first synthetic biological intelligence device to exhibit adaptive real-time behavior.
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