Rather than working with an actual chip, Jonas and Kording used a simulation, albeit one accurate enough to run classic games like Donkey Kong, Space Invaders, and Pitfall. That gave them experimental omniscience and omnipotence—they knew everything and could tweak anything. For example, they could disable each of the chip’s transistors one at a time. And by doing so, they found several that were essential for booting up all three games, and others that were essential for just one.
Brain scientists have doing something similar for centuries, either by studying people with localized brain damage or by temporarily shutting down specific brain regions. Through such studies, they’ve labelled different areas as memory centers or language centers or emotional centers. But Jonas and Kording’s work shows why such inferences can be deceptive. They didn’t find “Donkey Kong transistors” or “Space Invaders transistors”; instead, they found components that carry out basic processes that just so happen to be important for those particular games.
They also tried out five other common approaches—the equivalents of analyzing individual neurons, or averaging activity in a small region as in fMRI brain-scanning, or taking a god-like view and look for patterns across the entire brain. None of these told the team anything useful about how the chip works. Kelly Clancy from the University of Basel says, “I see this paper as a fantastic reality check for the field. We may not lack in data but in ways of interpreting it.”
This doesn’t mean that neuroscientists have been wasting their time, or that we know nothing about the brain. We know that some medicines can affect the brain and improve people’s lives, without knowing exactly how they work. We can see that damage to a certain area robs people of a particular ability, without knowing what that area normally does. “The techniques of neuroscience are far from useless,” says Clancy. “They’re effective readouts of health and illness, marking changes related to disease, learning, pharmaceuticals, and so on. But using them to sieve meaning about the fundamental logic of our nervous system is another matter.”
To move forward, Jonas says that neuroscientists need to put more effort into testing their theories about the brain. “There are a lot of theories about how different parts of the brain might function, but they don’t make falsifiable predictions. They have so many different knobs you can turn that they can be arbitrarily extended to fit arbitrary bits of data. It’s very hard to kick any of these ideas to the curb.”
Microprocessors might help. If someone has a new theory about how the brain deals with information, or a technique for analyzing brain data, “let’s see how much closer it gets us to understanding the chip,” says Kording. “If it doesn’t work on the chip, how can we expect it to work on the brain?”
And in the meantime, Jonas wants his peers to be more cautious about the promises they make. The launch of the BRAIN Initiative was accompanied by much rhetoric about understanding and treating neurological and psychiatric conditions. “We’re so far from that,” he says. “I worry that if we overpromise and underdeliver, we could end up in a not-great situation.”