John Krakaeur, a neuroscientist at Johns Hopkins Hospital, has been asked to BRAIN Initiative meetings before, and describes it like “Maleficent being invited to Sleeping Beauty’s birthday.” That’s because he and four like-minded friends have become increasingly disenchanted by their colleagues’ obsession with their toys. And in a new paper that’s part philosophical treatise and part shot across the bow, they argue that this technological fetish is leading the field astray. “People think technology + big data + machine learning = science,” says Krakauer. “And it’s not.”
That’s because behavior is an emergent property—it arises from large groups of neurons working together, and isn’t apparent from studying any single one. You can draw parallels with the flocking of birds. Biologists have long wondered how they manage to wheel about the skies in perfect coordination, as if they were a single entity. In the 1980s, computer scientists showed that this can happen if each bird obeys a few simple rules, which dictate their distance and alignment relative to their peers. From these simple individual rules, collective complexity emerges.
A landmark study, published last year, beautifully illustrated his point using, of all things, retro video games. Eric Jonas and Konrad Kording examined the MOS 6502 microchip, which ran classics like Donkey Kong and Space Invaders, in the style of neuroscientists. Using the approaches that are common to brain science, they wondered if they could rediscover what they already knew about the chip—how its transistors and logic gates process information, and how they run simple games. And they utterly failed.
“What we extracted was so incredibly superficial,” Jonas told me last year. And “in the real world, this would be a millions-of-dollars data set.” If the kind of neuroscience that has come to dominate the field couldn’t explain the workings of a simple, dated microchip, how could it hope to explain the brain—reputedly the most complex object in the universe?