This wasn’t “his brain matter”, these were “neuronal organoids” (clumps of neurons) grown from harvesting white blood cells and turning those into stem cells. Then the clumps were networked together with a literal wire to conduct signals between them, for timing.

Usually in organoids networks the wire delivers either regular, repeating inputs (“clean” pulses) as a reward for succeeding a task, or a random signal (“noise”) for failure; this is how they’re “trained” to play Pong for example:

In more advanced closed-loop setups, organoid cultures are embedded within simulated environments that allow them to “interact” in a game-like world. By using high-density multielectrode arrays (MEAs) to deliver patterns of electrical signals, researchers can create closed-loop feedback systems that enable organoids to process and respond to certain inputs (Kagan et al. [2022]). For instance, in one experiment, monolayer neuronal cultures were given sparse sensory feedback about the consequences of their actions within a simulated game. The organoids displayed short-term memory by organizing themselves in goal-directed ways, effectively learning to complete simple behavioural tasks. This capability, made possible by reinforcement learning, allows organoids to adapt based on feedback, akin to how a human brain might learn from trial and error.

(https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6)

These same methods are being used to train organoids as Machine Learning compute substrates, because they’re much more efficient than silicon: https://aapsopen.springeropen.com/articles/10.1186/s41120-025-00109-3

What’s with the downvotes?