In vitro neurons learn and exhibit sentience when embodied in a simulated game-world

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.

Automated summary

Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, the researchers developed a system called DishBrain that combines in vitro neural networks with in silico computing to harness the adaptive computation of neurons. By embedding the cultures in a simulated game-world, they observed apparent learning in the networks within five minutes of real-time gameplay, demonstrating the importance of closed-loop structured feedback in eliciting learning over time.