Living brain cells playing pong in a dish could shed light on the mechanics of the mind

Living brain cells playing pong in a dish could shed light on the mechanics of the mind

Scientists have created a gaming opponent — out of cells, in a lab.

A team of researchers led by Australia 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 observed that the mini-mind quickly learned the game and improved as it practiced. They were able to follow up by converting 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 display 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 long-standing the mysteries of brain mechanics and lead to better treatments for certain neurological conditions. “DishBrain offers a simpler approach to testing brain function and better understanding debilitating conditions such as epilepsy and dementia,” said Hon Weng Chong, chief executive of biotech startup Cortical Labs.

SBI could also offer an alternative to animal testing, which is often how scientists study the viability 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 (neuronal) computational elements found in your brain and mine,” adds co-author Professor Karl Friston, theoretical neuroscientist at University College London.

artificial intelligence vs biological intelligence

The research team found that biological intelligence, i.e. living brain cells, behave quite differently from a computer in terms of AI.

“In the past, models of the brain have been developed based on how computer scientists think the brain might work,” says Brett Kagan, scientific director of Cortical Labs and co-author of the study. “It’s usually based on our current understanding of information technology, such as silicon computing… But in truth, we don’t really understand how the brain works.”

Interestingly, DishBrain naturally learned to play Pong due to 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” back into Pong, it allowed the system to better predict where it would move next. If DishBrain failed, it would lose the point and a new point would start with the computer releasing a ball from a random starting point, and so on. Because DishBrain uses a feedback loop, it seems to gradually improve as it plays.

“It’s remarkable because you can’t teach this type 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 computer chips to create a generalized form of SBI which, as the team writes in their study, “may arrive before artificial general intelligence due to 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,” says co-author Adeel Razi of Monash University. “Now it looks like we have our fingertips where we can harness this incredibly powerful and cheap biological intelligence.”

The researchers also tried 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 this and have seen good preliminary results, but we still have work to do to create new environments for custom purposes.”

Next, the team intends 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 the game worse, like when people are drinking,” Kagan says.

As we eagerly await the results of the drunk DishBrain study, perhaps let’s keep those drunk neurons away from any self-driving car code.

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