Neuroscience’s Existential Crisis

Neuroscience’s Existential Crisis

Grigori Guitchounts

...When I asked if a completed connectome would give us a full understanding of the brain, he didn’t pause in his answer. I got the feeling he had thought a great deal about this question on his own.

“I think the word ‘understanding’ has to undergo an evolution,” Lichtman said, as we sat around his desk. “Most of us know what we mean when we say ‘I understand something.’ It makes sense to us. We can hold the idea in our heads. We can explain it with language. But if I asked, ‘Do you understand New York City?’ you would probably respond, ‘What do you mean?’ There’s all this complexity. If you can’t understand New York City, it’s not because you can’t get access to the data. It’s just there’s so much going on at the same time. That’s what a human brain is. It’s millions of things happening simultaneously among different types of cells, neuromodulators, genetic components, things from the outside. There’s no point when you can suddenly say, ‘I now understand the brain,’ just as you wouldn’t say, ‘I now get New York City.’ ”

“Maybe human brains aren’t equipped to understand themselves,” I offered.

“And maybe there’s something fundamental about that idea: that no machine can have an output more sophisticated than itself,” Lichtman said. “What a car does is trivial compared to its engineering. What a human brain does is trivial compared to its engineering. Which is the great irony here. We have this false belief there’s nothing in the universe that humans can’t understand because we have infinite intelligence. But if I asked you if your dog can understand something you’d say, ‘Well, my dog’s brain is small.’ Well, your brain is only a little bigger,” he continued, chuckling. “Why, suddenly, are you able to understand everything?”

It seems likely that Lichtman’s two exabytes of brain slices, and even my 48 terabytes of rat brain data, will not fit through any individual human mind. Or at least no human mind is going to orchestrate all this data into a panoramic picture of how the human brain works. As I sat at my office desk, watching the setting sun tint the cloudless sky a light crimson, my mind reached a chromatic, if mechanical, future. The machines we have built—the ones architected after cortical anatomy—fall short of capturing the nature of the human brain. But they have no trouble finding patterns in large datasets. Maybe one day, as they grow stronger building on more cortical anatomy, they will be able to explain those patterns back to us, solving the puzzle of the brain’s interconnections, creating a picture we understand. Out my window, the sparrows were chirping excitedly, not ready to call it a day.

Neuroscience’s Existential Crisis

Grigori Guitchounts

A paragraph I loved:

The nature of the scientific process is such that researchers have to pick small, pointed questions. Scientists are like diners at a restaurant: We’d love to try everything on the menu, but choices have to be made. And so we pick our field, and subfield, read up on the hundreds of previous experiments done on the subject, design and perform our own experiments, and hope the answers advance our understanding. But if we have to ask small questions, then how do we begin to understand the whole?

oh noooooo

 The tape goes on silicon wafers, and into Lichtman’s electron microscope, where billions of electrons blast the brain slices, generating images that reveal nanometer-scale features of neurons, their axons, dendrites, and the synapses through which they exchange information. The Technicolor images are a beautiful sight that evokes a fantastic thought: The mysteries of how brains create memories, thoughts, perceptions, feelings—consciousness itself—must be hidden in this labyrinth of neural connections.

A batshit assumption -- because the wiring (copper, fiber, electro-chemical) doesn't dictate the outcomes of logical processes encoded in the electronic signals they carry.

My prediction is that science will abstract natural patterns from the data.  Patterns from structures and activities that describe information processing, both subconscious and conscious, in a way that it will be understood in a cohesive and general manner.

This is just like the "magic" understanding that mapping the genome will bring and never found.  Good research - bad analysis from a wrong metaphysical assumption.   Sincere research has uncovered valuable data on epigenetics and other new discoveries.

I tend to think the fad for 'big data' is often a sign of science losing its way. You collect some data in the hopes it will give you inspiration, but when it doesn't you collect ten times as much.

Repeat until grant runs out

David