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An Existential Crisis in Neuroscience

m.nautil.us

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Re: An Existential Crisis in Neuroscience

#51

Post by forgotpwagain »

SubiculumCode wrote: post #32
gbjw wrote: post #14

Tangentially related: Could a Neuroscientist Understand a Microprocessor? [1] (short answer: not with current analytic tools) [1] https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...

This is an over-rated article by those outside the field of neuroscience. While it brings up a few good points, it fails to acknowledge the sophistication of our neuroscience and behavioral techniques, and the value of converging evidence across levels of description. Also, its relatedness to the present article is tenuous at best.

Mostly agreed. In my eyes, the takeaway from this piece is not that neuroscience is futile and that we should give up, but rather that we now should redouble efforts on analysis methods to make sense of the large, complex datasets that we are on the cusp of generating.

Re: An Existential Crisis in Neuroscience

#52

Post by friendlybus »

mcilai wrote: post #47
dr_dshiv wrote: post #4

What we need is a Newtonian model of the brain. A model that is incomplete and "wrong", but useful and generative. While Newtonian physics may be "wrong", is much easier to learn than quantum physics or relativity, etc. Neuroscience usually focuses on precision details, but doesn't aim to tell big picture stories. There are a few exceptions, however, like Karl Friston's free energy reduction model.

Deep learning is as close to being a "newtonian theory" of the brain as it gets -- deep learning abstracts away a lot of the complexity of neural systems (e.g., a simple artificial neuron vs a highly complex biological one) while maintaining a number of essential characteristics: massively parallel computation, error tolerance, graceful degradation, distributed representations, information is stored in slowly-changin…

Everybody in the history of humans has said the latest technology is the best model for how a brain works. There used to be a piston model for the brain.

Self driving cars can't leave an enclosed environment and might never do so safely.

Richard Dawkins spoke very highly of the brains ability to do some kind of natural calculus for the sake of tracking a ball in flight, but most animals run on simple tricks and reference points.

Deep learning might be the "good think" for the next ten years, some of us are not going to let go of the transcendent truth that the brain is not defined by what we think it is. I see limited reason to see deep learning as more likely than some emergent behaviour from a vast number of simple rules. Like animals flocking together in a boid sim.

Re: An Existential Crisis in Neuroscience

#53

Post by rusk »

notahacker wrote: post #41
rusk wrote: post #23

Earlier quoted context omitted.

A mind understanding itself may violate the second law, but a few minds understanding one mind should be theoretically possible!

The organization of human thought to achieve that level of understanding might be an issue. From the original article: 'the data footprint of all books ever written come out to less than 100 terabytes, or 0.005 percent of a mouse brain'

That formulation makes the goal seem remote but not implausible. We have the technology to index and analyse 10 Terrabytes certainly and even gmail apparently is an exabyte ... [0]. A mouse brain given your premise is 20 petabytes. Given even linear progress this class of problem is not insurmountable.

[0] https://en.m.wikipedia.org/wiki/Exa-

Re: An Existential Crisis in Neuroscience

#54

Post by mcilai »

friendlybus wrote: post #52
mcilai wrote: post #47

Earlier quoted context omitted.

Deep learning is as close to being a "newtonian theory" of the brain as it gets -- deep learning abstracts away a lot of the complexity of neural systems (e.g., a simple artificial neuron vs a highly complex biological one) while maintaining a number of essential characteristics: massively parallel computation, error tolerance, graceful degradation, distributed representations, information is stored in slowly-changin…

Everybody in the history of humans has said the latest technology is the best model for how a brain works. There used to be a piston model for the brain. Self driving cars can't leave an enclosed environment and might never do so safely. Richard Dawkins spoke very highly of the brains ability to do some kind of natural calculus for the sake of tracking a ball in flight, but most animals run on simple tricks and refer…

There's one minor difference between past models of the brain and deep learning: deep learning can actually perform difficult and useful cognitive tasks that cannot be accomplished by any other means.

Re: An Existential Crisis in Neuroscience

#56

Post by friendlybus »

mcilai wrote: post #54
friendlybus wrote: post #52

Earlier quoted context omitted.

Everybody in the history of humans has said the latest technology is the best model for how a brain works. There used to be a piston model for the brain. Self driving cars can't leave an enclosed environment and might never do so safely. Richard Dawkins spoke very highly of the brains ability to do some kind of natural calculus for the sake of tracking a ball in flight, but most animals run on simple tricks and refer…

There's one minor difference between past models of the brain and deep learning: deep learning can actually perform difficult and useful cognitive tasks that cannot be accomplished by any other means.

Computers beat chess by grinding out the answers, something previously unattainable for humankind. Computers can beat chess,go and starcraft now with curve fitting ml programs.

The problem is for all this power people still play chess,go and starcraft and we don't know how their brain works.

Re: An Existential Crisis in Neuroscience

#57

Post by mjfl »

To identify what the author feels is missing in neuroscience: in order to understand something, you need to figure out how to describe two things about it (1) what its state is at any point in time, and (2) how that state evolves in time. Connectomics gives you the beginnings to solve (1), but it doesn't go the whole way. There's a fundamental misunderstanding that you can collect exabytes of data and glean understanding from it just because how much you had to sweat getting the storage and collecting it. That's not how it works, it needs to have structure too. I wish more biologists / neuroscientists understood this.

Re: An Existential Crisis in Neuroscience

#58

Post by meowface »

mjfl wrote: post #57

To identify what the author feels is missing in neuroscience: in order to understand something, you need to figure out how to describe two things about it (1) what its state is at any point in time, and (2) how that state evolves in time. Connectomics gives you the beginnings to solve (1), but it doesn't go the whole way. There's a fundamental misunderstanding that you can collect exabytes of data and glean understan…

I think they understand this. This is demonstrated by there being little real understanding of ~300 neuron worm connectomes.

The point of the article is discussing how mapping the full human connectome is only going to be a small next step towards understanding what's actually going on. That doesn't mean it's not worth doing.

Re: An Existential Crisis in Neuroscience

#59

Post by hsitz »

SubiculumCode wrote: post #39
SubiculumCode wrote: post #32

Earlier quoted context omitted.

This is an over-rated article by those outside the field of neuroscience. While it brings up a few good points, it fails to acknowledge the sophistication of our neuroscience and behavioral techniques, and the value of converging evidence across levels of description. Also, its relatedness to the present article is tenuous at best.

I don't care how often I get down voted for making the above comment in response to posts about this article. I am a neuroscientist and I will defend my field from overrated, simplistic criticisms that happen to appeal to the HN crowd's sensibilities.

Do you have any suggestions for what the average layperson could read to get a better understanding of contemporary neuroscience? Any articles or books you'd recommend?

Re: An Existential Crisis in Neuroscience

#60

Post by Balgair »

stevebmark wrote: post #40

I'm confused. This article doesn't say anything. It makes no points and has no insight. "There's a lot of data in neuroscience?" Is that the message? An unusual number of Nautilus articles frontpage HN like this one, where there doesn't seem to be any value in the article itself. What is going on?

It's that the author is undergoing a 'crisis', not that the field is. The title is clever, not descriptive.

More broadly, there is a crisis. Our statistical methods/understandings are not working out in these large N-dimensional data sets, at least for the researchers that were raised on excel and not numpy.

Aside: I'm surprised that the FAANGs haven't revolutionized statistics yet. When you have 'phase changes' where a LOT more data becomes available, you get to see very low probability events. It's happened in psych, in bio, in physics most famously, in politics, in economics, etc. We have a LOT more data now in for statistical use, but it's still just Poisson distributions and t-tests. What gives?

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