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A dish full of brain cells has learned to play the computer game Pong

A MARTINEZ, HOST:

A dish full of brain cells has learned to play the computer game Pong.

(SOUNDBITE OF BEEPING)

MARTINEZ: That's right - the original table tennis arcade game from the 1970s. NPR's Jon Hamilton reports that this novel achievement is part of a larger effort to understand how brain cells learn.

JON HAMILTON, BYLINE: A living brain has a kind of intelligence that a computer usually lacks. Take, for example, the average person's ability to make a cup of tea, says Brett Kagan, the chief scientific officer of Cortical Labs in Melbourne, Australia.

BRETT KAGAN: You might have never been in someone else's house, but with a bit of rummaging and searching you can probably make a decent cup of tea as long as they've got the ingredients.

HAMILTON: But even a powerful computer would struggle with that task. So Cortical Labs has been trying to understand how living brain cells acquire their intelligence. Kagan says the Pong experiment was a way for the company to answer a central question about a network of brain cells.

KAGAN: If we do allow these cells to know the outcome of their actions, will they actually be able to change in some sort of goal-directed way?

HAMILTON: To find out, the scientists used a system that links a network of brain cells to a computer. First, the computer generated a game of Pong. Then it began sending signals to the cells, telling them where the ball was. At the same time, Kagan says, the computer began monitoring signals sent by the cells.

KAGAN: And what we did is we took that information, and we allowed it to influence this Pong game that they were playing so they could move the paddle around.

HAMILTON: The cells just had to figure out how to control the paddle's movement. To help them learn, Kagan says, the scientists provided the cells with something you might call motivation. It came in the form of electrical stimulation.

KAGAN: If they hit the ball, we gave them something predictable - so very simple, predictable stimulus was the same every time. When they missed it, they got something that was totally unpredictable - white noise, a different white noise every time.

HAMILTON: Brain cells like predictable stimulation. So they began to learn how to send signals that would move the paddle in front of the ball. The brain cells never got that good, but human brain cells seemed to play a bit better than mouse brain cells. And Kagan says they all did pretty well, considering that the entire network contained fewer cells than the brain of a cockroach.

KAGAN: 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.

HAMILTON: Kagan says the results, which appear in the journal Neuron, hint at a future in which biology helps computers become more intelligent. But Steve M. Potter, an adjunct associate professor at Georgia Tech, says that future is probably still a long way off.

STEVE M POTTER: The idea of a computer that has some living components is exciting, and it's starting to become reality. However, the kinds of learning that these things can accomplish is quite rudimentary right now.

HAMILTON: Even so, Potter says, the Pong-playing system is a great tool for doing research.

POTTER: This is sort of a semi-living animal model that one can use to study all sorts of mechanisms in the nervous system.

HAMILTON: Including learning.

Jon Hamilton, NPR News. Transcript provided by NPR, Copyright NPR.

NPR transcripts are created on a rush deadline by an NPR contractor. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.

Jon Hamilton is a correspondent for NPR's Science Desk. Currently he focuses on neuroscience and health risks.
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