Living brain cells playing ping pong on a plate could illuminate the mechanics of the mind

Living brain cells playing ping pong on a plate could illuminate the mechanics of the mind
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Scientists have created a player, from cells, in a laboratory.

An Australian-led team of researchers placed 800,000 live human and mouse brain cells in a dish, connected them to electrodes and a simulation of the classic game Pong. The scientists then watched as the mini-mind quickly taught itself the game and got better the more it practiced. They were able to go ahead by turning the cellular responses into a visual representation of the game that closely resembles the original.

They call their system DishBrain and say it proves that neurons in a dish can learn and show basic signs of intelligence. The team details the new configuration, dubbed synthetic biological intelligence, or SBI, in a study published Wednesday in the journal Neuron.

Eventually, the authors say, SBI could help unlock mysteries of brain mechanics and lead to better treatments for certain neurological conditions. “DishBrain offers a simpler approach to testing how the brain works and gaining insight into debilitating conditions like epilepsy and dementia,” says Hon Weng Chong, CEO of biotech startup Cortical Labs.

SBI could also offer an alternative to animal testing, which is often how scientists study the feasibility of new drugs and therapies.

“We now have, in principle, the ultimate biomimetic ‘sandbox’ in which to test the effects of drugs and genetic variants: a sandbox made up of exactly the same computing (neuronal) elements found in your brain and in mine,” adds the collaborator. author Professor Karl Friston, theoretical neuroscientist at University College London.

artificial vs biological intelligence

The study team found that biological intelligence, also known as living brain cells, behaves quite differently than a computer would in AI terms.

“In the past, models of the brain were developed according to how computer scientists think the brain might work,” says Brett Kagan, chief scientific officer at Cortical Labs and co-author of the study. “That’s generally based on our current understanding of information technology, like silicon computing… But we don’t really understand how the brain works.”

Interestingly, DishBrain naturally learned to play Pong out of an apparent tendency to act on its environment in ways that made it more predictable and less random. In other words, this system behaves much more like a real living brain than the AI ​​does.

For example, when DishBrain successfully returned the “ball” in Pong, the system was better able to predict where it would move next. If DishBrain failed, it would lose the point and start a new point with the computer launching a ball from a random starting location, and so on. Because DishBrain uses a feedback loop, it seems to get progressively better the more it plays.

“This is remarkable because you can’t teach this kind of self-organization, simply because, unlike a pet, these mini-brains have no sense of reward and punishment,” adds Friston.

Now Cortical Labs, an Australian biotech startup, is working on a new generation of biological computing chips to create a widespread form of SBI that, as the team writes in their study, “may come before artificial general intelligence due to the inherent efficiency and evolutionary advantage of biological systems”.

“We know that our brains have the evolutionary advantage of being tuned for hundreds of millions of years to survive,” explains co-author Adeel Razi of Monash University. “Now, it seems that we have within our reach where we can take advantage of this incredibly powerful and cheap biological intelligence.”

The researchers also tested the system on other simple games.

“You know when the Google Chrome browser crashes and you get this dinosaur that you can jump over obstacles (Project Bolan),” says Kagan. “We have done that and have seen some good preliminary results, but we still have more work to do on creating new environments for custom purposes.”

Next, the team has plans to give DishBrain a good time.

“We’re trying to create a dose-response curve with ethanol — basically ‘get them drunk’ and see if they play worse, like when people drink,” says Kagan.

While we look forward to the results of the Drunk DishBrain study, perhaps we’ll keep those drunken neurons away from any self-driving car code.

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