How Brain Scientists Forgot That Brains Have Owners

Interesting take on this. If we had a defined strategy to answer specific questions neuroscientists wouldn't have time to play with their toys. This is why we should write up very specific RFPs if we had a great stroke association.
https://www.theatlantic.com/science/archive/2017/02/how-brain-scientists-forgot-that-brains-have-owners/517599/

Five neuroscientists argue that fancy new technologies have led the field astray.

A rat's brain activity is recorded by sensors connected to its head. Reuters

• Ed Yong
• Feb 27, 2017
• Science

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It’s a good time to be interested in the brain. Neuroscientists can now turn neurons on or off with just a flash of light, allowing them to manipulate the behavior of animals with exceptional precision. They can turn brains transparent and seed them with glowing molecules to divine their structure. They can record the activity of huge numbers of neurons at once. And those are just the tools that currently exist. In 2013, Barack Obama launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative—a $115 million plan to develop even better technologies for understanding the enigmatic gray blobs that sit inside our skulls.
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.”

He and his fellow curmudgeons argue that brains are special because of the behavior they create—everything from a predator’s pounce to a baby’s cry. But the study of such behavior is being de-prioritized, or studied “almost as an afterthought.” Instead, neuroscientists have been focusing on using their new tools to study individual neurons, or networks of neurons. According to Krakauer, the unspoken assumption is that if we collect enough data about the parts, the workings of the whole will become clear. If we fully understand the molecules that dance across a synapse, or the electrical pulses that zoom along a neuron, or the web of connections formed by many neurons, we will eventually solve the mysteries of learning, memory, emotion, and more. “The fallacy is that more of the same kind of work in the infinitely postponed future will transform into knowing why that mother’s crying or why I’m feeling this way,” says Krakauer. And, as he and his colleagues argue, it will 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.

But you would never have been able to predict the latter from the former. No matter how thoroughly you understood the physics of feathers, you could never have predicted a murmuration of starlings without first seeing it happen. So it is with the brain. As British neuroscientist David Marr wrote in 1982, “trying to understand perception by understanding neurons is like trying to understand a bird’s flight by studying only feathers. It just cannot be done.”

“It’s as if every paper needs to be a methodological decathlon in order to be considered important.”  

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?