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An Existential Crisis in Neuroscience

m.nautil.us

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Re: An Existential Crisis in Neuroscience

#81

Post by ImaTigger »

dr_dshiv wrote: post #77
ImaTigger wrote: post #71

Earlier quoted context omitted.

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…

I know about Smolensky's theories (have probably read that paper, but don't remember it exactly; have def. read others by PS); PS and JE are definitely contemporaries, and work/have worked in similar areas. However, these two theories operate at different levels and time scales. The oscillatory coupling theories of PS et al are related to real time computations carried out by neural networks, whereas the trophic wave theories of JE et al. relate to how these networks come to be organized as they are. As per other posts, both are useful, and probably both true to some extent. Neither is directly applicable yet in a way that makes contact with the cognitive level.

Re: An Existential Crisis in Neuroscience

#82

Post by randcraw »

jayd16 wrote: post #38
erikpukinskis wrote: post #18

Earlier quoted context omitted.

I think it’s interesting that people think we’ll be able to make something that does more in a smaller space. As if there was something other than the laws of physics preventing natural selection from testing smaller structures. Or that there’s something (other than the demands of the computation itself) constraining the architectures that were tested through natural selection.

We out design nature all the time. Evolution doesn't find perfection, it finds whats good enough.

Right. Every tool invented by humans is superior in achieving a certain end than is our inborn equivalent. We don't have to faithfully model nature to surpass it.

Likewise manmade models based in mathematics and statistics have long proved more accurate in predicting outcomes than the human mind, even though we know the mind doesn't employ math.

Human-made machines have made it possible for elephants to fly. Nature never will.

Re: An Existential Crisis in Neuroscience

#83

Post by SubiculumCode »

earthboundkid wrote: post #69
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.

Ah yes, the very mature science that has no consensus description of what memory is.

As someone who did his dissertation on episodic memory development, I see the wry humor, but I think your comment is a non sequitur. It is not that we have figured it all out, but rather can we gleam knowledge about cognition (e.g. episodic memory) and the brain from neuroscience and behavioral techniques. I think the answer is clearly yes. In terms of memory, we understand, for example, that the hippocampus is critical to some forms of memory, most critically memory that requires binding of arbitrary information/percepts representations into a more cohesive event representation, that the hippocmapus may achieve this through computational properties potentially afforded to it in microcircuits in subfields of the hippcampus (e.g. pattern completion from heavy recurrnecy in CA3) and pattern separation of information in the dentate gyrus, etc. and so on.

Re: An Existential Crisis in Neuroscience

#84

Post by buboard »

_xerxes_ wrote: post #27

The article touched upon the C. elegans connectome. There are a few interesting projects attempting to simulate the creature. https://en.wikipedia.org/wiki/OpenWorm https://en.wikipedia.org/wiki/WormBase

tbf it's debatable if there 's a lot to learn from C.elegans. Simple animals have been studied for decades from aplysia to the mouse. But those are not behaviours that are interesting when attempting to learn more about the human brain. The Allen institute's connectome project is more relevant to mammals, even if it's only a tiny volume of the mouse cortex, in order to mildly constrain models of brain function. Even if we had the whole brain, it s too large to be simulatable. These data help our understanding, and we 're lucky we have amazing tools to probe brains at this moment. But we need more and better theories to put them to good use

Re: An Existential Crisis in Neuroscience

#85

Post by asdfgftheaef »

dr_dshiv wrote: post #80
JoeSmithson wrote: post #24

Earlier quoted context omitted.

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.)

Here's a different perspective:

https://aaai.org/ojs/index.php/aimagazine/article/view/2744

"A Standard Model of the Mind: Toward a Common Computational Framework across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics"

Re: An Existential Crisis in Neuroscience

#86

Post by lambdaloop »

ImaTigger wrote: post #75

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 behavior…

As a counterpoint, I am a computational neuroscientist who transitioned form working in human cognition to fruit fly motor control. Fruit fly neuroscience in the past decade has advanced tremendously. With the latest tools, we can record activity from specific genetically labeled neurons while stimulating others. We have identified specific groups of neurons to stimulate to get the fly to groom, walk, turn, and even walk backwards. The full fly brain has been scanned with similar techniques and the connectome is beginning to be mapped out (e.g. see this very recent post from Google AI research https://ai.googleblog.com/2020/01/releasing-drosophila-hemib... ).

I find that as we gain new tools to study the nervous system more specifically, both data and models of how neurons are organized at the circuit level become more important. To advance on an analogy in the article, it's like trying to explore the dynamics of NYC without a map. For instance, it's hard to tell how/why people interact with central park if you don't even know where they live. The more specifically you are able to pin down people, the more it matters where exactly they live to understand.

Granted, the fly is much simpler than humans or even mice, and it will likely take decades and new tools for us to study humans in this way. However, when we get there, mapping out the brain connections will be crucial to make sense of it all.

Re: An Existential Crisis in Neuroscience

#87

Post by garmaine »

Balgair wrote: post #60
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' wher…

> Aside: I'm surprised that the FAANGs haven't revolutionized statistics yet.

What does that even mean?

Re: An Existential Crisis in Neuroscience

#88

Post by dr_dshiv »

SquishyPanda23 wrote: post #79
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. b…

It's a great point. And I agree that precision in stars or mechanics seems much simpler than neuroscience -- but I do actually think that there will be some laws akin to f=ma.

Ok, maybe not quite to that level. But consider this paper, by great neuroscientists and cited over 1000 times, that models brain wave bands as harmonics, with band widths as the golden mean. [1, see figure 4]

My money is on some synthesis of the many theories in oscillatory neurodynamics. Neural resonance, dissonance, harmonics and entrainment... So many of the theories* have borne out empirically, but there has hardly been an attempt at synthesis.

* Theories like "Communication through coherence", "binding by synchrony", "phase amplitude coupling" + "working memory", etc etc etc.

[1] Klimesch, W. (2012). Alpha-band oscillations, attention, and controlled access to stored information. Trends in cognitive sciences, 16(12), 606-617.

Re: An Existential Crisis in Neuroscience

#90

Post by monadic2 »

buboard wrote: post #84
_xerxes_ wrote: post #27

The article touched upon the C. elegans connectome. There are a few interesting projects attempting to simulate the creature. https://en.wikipedia.org/wiki/OpenWorm https://en.wikipedia.org/wiki/WormBase

tbf it's debatable if there 's a lot to learn from C.elegans. Simple animals have been studied for decades from aplysia to the mouse. But those are not behaviours that are interesting when attempting to learn more about the human brain. The Allen institute's connectome project is more relevant to mammals, even if it's only a tiny volume of the mouse cortex, in order to mildly constrain models of brain function. Even…

How do you validate your models if you can't validate a simpler one first?
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