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An Existential Crisis in Neuroscience

m.nautil.us

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Re: An Existential Crisis in Neuroscience

#71

Post by ImaTigger »

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.

What you're looking for is Elman et al's theory in Rethinking Innateness (https://mitpress.mit.edu/books/rethinking-innateness) It's more like Darwin than Newton, and is (to the point of another post off this thread) an early deep-learning-like theory of how the brain (or at least the cortex) becomes organized.

Re: An Existential Crisis in Neuroscience

#72

Post by starpilot »

JoeSmithson wrote: post #24
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.

There are several of these (cognitive architectures) e.g. the ACT-R model[0]. [0] https://en.m.wikipedia.org/wiki/ACT-R

I've noticed a trend of software engineers proposing that other fields create some abstraction that already exists. Last week someone avowed that a citizen regulatory body for aviation be created. Of course, that is the FAA.

Re: An Existential Crisis in Neuroscience

#73

Post by ImaTigger »

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…

See my post in another thread re Elman et al. Rethinking Innateness (https://mitpress.mit.edu/books/rethinking-innateness).

Re: An Existential Crisis in Neuroscience

#74

Post by Strilanc »

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…

> 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.

Is this the same mistake as in "The Relativity of Wrong" [1]?

> people have thought they understood the Universe at last, and in every century they were proven to be wrong. It follows that the one thing we can say about out modern "knowledge" is that it is wrong.

> [...]

> My answer to him was, "John, when people thought the Earth was flat, they were wrong. When people thought the Earth was spherical, they were wrong. But if you think that thinking the Earth is spherical is just as wrong as thinking the Earth is flat, then your view is wronger than both of them put together."

Modelling the brain as a bunch of pistons or as a complicated machine or clockwork thing is a lot better than as a magical clay golem or opaque soul. Modelling it as a computer is even better than that. Not a computer in the sense of an x86 desktop exactly, of course, but the concept of computation is clearly fundamental to understanding the system. Similarly, the brain is not ResNet but concepts like backpropagation are probably useful.

So, sure, maybe people have been using the latest fad to explain the brain forever. But that's only bad to the extent that the latest fad is getting further away instead of closer.

1: http://hermiene.net/essays-trans/relativity_of_wrong.html

Re: An Existential Crisis in Neuroscience

#75

Post by ImaTigger »

I am a computational cognitive neuroscientist, an have worked at many levels. I find each kind of data and model useful to some extent, but I have to admit that the least useful, are, to my mind, those at the detailed neural network level, like the ones discussing in this paper. Somewhat more useful are higher level dynamic architecture models, and, at the highest level, cognitive models, which constrain the behavioral target we are trying to explain. I personally (as one can tell from my other posts here) find the dynamics brain development models to be the most compelling as overall models, but they are not particularly explanatory at the detailed level. Brain science is trying to do the hardest thing you can imagine, that is, explain the most complex machine in the known universe. We persist, but no one entering this field should have very high expectations of near term grand successes.

Re: An Existential Crisis in Neuroscience

#76

Post by dr_dshiv »

hsitz wrote: post #59
SubiculumCode wrote: post #39

Earlier quoted context omitted.

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?

"rhythms in the brain" is highly recommended

Re: An Existential Crisis in Neuroscience

#77

Post by dr_dshiv »

ImaTigger wrote: post #71
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.

What you're looking for is Elman et al's theory in Rethinking Innateness ( https://mitpress.mit.edu/books/rethinking-innateness ) It's more like Darwin than Newton, and is (to the point of another post off this thread) an early deep-learning-like theory of how the brain (or at least the cortex) becomes organized.

Have you read smolensky's harmonium paper? It's the first restricted Boltzmann Machine -- and I believe elman and smolensky were colleagues with hinton back at UCSD (with rumelhart and Don Norman, et al).

The approach was focused on presymbolic processing -- and tried to optimize harmony. Harmony was, interestingly, the first mathematical model of the mind (by Pythagoreans/platonists in ancient Greece). It has a lot going for it these days, too, to understand oscillatory coupling in neural circuits. I learned recently that brain waves are harmonics (frequency doublings), which somehow I missed before!

Re: An Existential Crisis in Neuroscience

#78

Post by randcraw »

SubiculumCode wrote: post #29

From the article, a quote that is enlightening: 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 c…

True, but the equating of a brain with a city is largely specious, especially when trying to understand cognition. Yes a brain regulates many low level parasympathetic processes. But it's the decision making and memory systems that we most want to understand and replicate in silico. And the coordination of a city of mostly independent self-interested humans is a poor analogue for the biological bases for a coherent thought process, unless it's only the medulla or pons that we hope to model.

Re: An Existential Crisis in Neuroscience

#79

Post by SquishyPanda23 »

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.

> What we need is a Newtonian model of the brain.

This seems like an odd take on Newton to me. What made his contributions important is that they were correct up to the precision we could measure for centuries.

We are nowhere near that for a subject like neuroscience.

There have been models adopted by scientests who at the time knew they were wrong and incomplete. For example ancient astronomy or medicine or logic. but their adherents tended to hold back science when new discoveries were made. So they are double edged swords.

Re: An Existential Crisis in Neuroscience

#80

Post by dr_dshiv »

JoeSmithson wrote: post #24
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.

There are several of these (cognitive architectures) e.g. the ACT-R model[0]. [0] https://en.m.wikipedia.org/wiki/ACT-R

Yes, in "you can't play 20 questions with nature", Alan newell advocated for computational "unified models" of cognition. But they were heavily symbolic. While useful, they don't really make it more understandable. (That's my experience with act-r, anyway! It's useful, but doesn't give big picture synthesis, like a Newtonian model might. It's a lot of little models.)
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