"If you could see a cockroach playing a game of Pong and it was able to hit the ball twice as often as it was missing it, you would be pretty impressed with that cockroach," he says. But interestingly, human brain cells seemed to achieve a slightly higher level of play than mouse brain cells, Kagan says.Īnd the level of play was remarkable, considering that each network contained fewer cells than the brain of a cockroach, Kagan says. The brain cells never got that good at Pong. Cells began to learn to generate patterns of electrical activity that would move the paddle in front of the ball, and gradually rallies got longer. So they would choose predictable stimulation over unpredictable stimulation. The strategy was based on the Free Energy Principle, which states that brain cells want to be able to predict what's going on in their environment. "When they missed it, they got something that was totally unpredictable." "If they hit the ball, we gave them something predictable," Kagan says. When they got it wrong, the result was a chaotic stream of white noise. So the scientists tried to motivate the cells using electrical stimulation: a nicely organized burst of electrical activity if they got it right. They also had no reason to play the game. "So they could move the paddle around."Īt first, the cells didn't understand the signals coming from the computer, or know what signals to send the other direction. "We took that information and we allowed it to influence this Pong game that they were playing," Kagan says. At the same time, it began monitoring information coming from the cells in the form of electrical pulses. To allow the brain cells to play the game, the computer sent signals to them indicating where the bouncing ball was. In the simplified version used in the experiment, there was a single paddle on the left side of the virtual table, and the ball would carom off the other sides until it evaded the paddle. A black rectangle defines the table, and a white cursor represents each player's paddle, which can be moved up or down to intercept a white ball. ![]() ![]() To test the learning ability of the cells, the computer generated a game of Pong, a two-dimensional version of table tennis that gained a cult following as one of the first and most basic video games. The chip, which is linked to a computer, can both detect electrical signals produced by the neurons, and deliver electrical signals to them. This system allowed researchers to train neurons to play the video game Pong.Ī layer of living neurons is grown on a special silicon chip at the bottom of a thumb-size dish filled with nutrients. This scanning electron microscope image shows a neural culture growing on a high-density multi-electrode array. And Kagan says the Pong experiment was a way for the company to answer a key question about how a network of brain cells learns to change its behavior: So Cortical Labs has been trying to understand how living brain cells acquire this sort of intelligence. But even a very powerful computer would struggle to carry out that task in an unfamiliar environment. "You might have never been to someone else's house, but with a bit of rummaging and searching you can probably make a decent cup of tea as long as I've got the ingredients," he says. But people are able to generalize what they've learned in a way a computer can't. "That's something we don't see with biology."įor example, both computers and people can learn to make a cup of tea, Kagan says. ![]() "We've made huge strides with silicon computing, but they're still rigid and inflexible," says Brett Kagan, an author of the study and chief scientific officer at Cortical Labs in Melbourne, Australia. The novel achievement is part of an effort to understand how the brain learns, and how to make computers more intelligent. ![]() A dish of living brain cells has learned to play the 1970s arcade game Pong.Ībout 800,000 cells linked to a computer gradually learned to sense the position of the game's electronic ball and control a virtual paddle, a team reports in the journal Neuron.
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