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An Existential Crisis in Neuroscience

m.nautil.us

11–20 of 112 posts

Re: An Existential Crisis in Neuroscience

#11
post #3

If you've seen some of the high resolution videos of neural activity captures from even simple fish, the slightest motor movements activate hundreds of thousands of cells in a chaotic pattern. Neural circuitry is not neatly laid out like a silicon chip, its a forest of inter-connectivity that resists analysis even with extremely detailed visualization and data captures.

I love those videos. We will be getting a lot more, soon, as well with the new voltage-sentitive microscopy.

I think the best story for understanding circuitry in vertebrates comes from the work on hierarchical pattern generators -- where much of the work was done on lampreys.

Grillner, S. (2006). Biological pattern generation: the cellular and computational logic of networks in motion. Neuron, 52(5), 751-766.

Re: An Existential Crisis in Neuroscience

#12
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.

Don't we have that in the model that describes what the parts of the brain do? Proven to be wrong when you watch people with serious brain injuries re learn skills, but shown to have value by how it can predict what tumors or injuries will do to someone's ability.

I would argue not since it doesn't do much for explaining how it works. We know how computers process information. We don't really have a good story for how the brain does it.

We need a story that explains how the brain uses rhythms (oscillations) for computation.

Re: An Existential Crisis in Neuroscience

#13

"If the human brain were so simple that we could understand it, we would be so simple that we couldn't."

That is a cute aphorism, but there is no empirical evidence one way or the other. If you are thinking that it is obviously too much information for a brain to know itself, note that most of what we understand about complex systems, such as the weather, is understood using only a miniscule fraction of the total information present. That is the power of abstraction.

Re: An Existential Crisis in Neuroscience

#15
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.

Don't we have that in the model that describes what the parts of the brain do? Proven to be wrong when you watch people with serious brain injuries re learn skills, but shown to have value by how it can predict what tumors or injuries will do to someone's ability.

We know how to wire FETs, we know this is an i5 and is fast, we also know how to solder thick wires or how to loosen large screws, but no one knows how to build even a Z80 out of some germanium is how neuroscience is understood in my understanding

Re: An Existential Crisis in Neuroscience

#16
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.

Don't we have that in the model that describes what the parts of the brain do? Proven to be wrong when you watch people with serious brain injuries re learn skills, but shown to have value by how it can predict what tumors or injuries will do to someone's ability.

Those models and explanations are not nearly as helpful as one might think. A lot of "neuroscience" explanations of everyday behaviour are mostly nonsense that sounds plausible and appealing (https://www.nature.com/articles/nrn3817, https://www.mitpressjournals.org/doi/abs/10.1162/jocn_a_0075...). In this context plausible doesn't even mean plausible to a neuroscientist, it means more like consistent with the nonsense a layperson has heard before.

What would be really helpful is a model that can add to things we already know. Saying "studying for an exam engages the X part of the brain and uses the Y neurotransmitter" adds literally nothing to your understanding of studying (you can find out much more about studying by talking to people that are good at it and who have done a lot of studying themselves), it's just taking an everyday activity and identifying the small but still vastly complex portion of the brain that is activated more than others. Imagine being told that a particular bug in a 1-billion-lines-of-code codebase is due to some code within a 10-million-lines-of-code portion of it: that's great but how helpful is it really?

Re: An Existential Crisis in Neuroscience

#17
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.

That's a question I asked myself about 10 years ago, so I made one. Is it perfect? Probably not, but I have strived to make it as rational and rigorous as I could. http://behaviorallogic.com/foundations/

Re: An Existential Crisis in Neuroscience

#18
post #3

If you've seen some of the high resolution videos of neural activity captures from even simple fish, the slightest motor movements activate hundreds of thousands of cells in a chaotic pattern. Neural circuitry is not neatly laid out like a silicon chip, its a forest of inter-connectivity that resists analysis even with extremely detailed visualization and data captures.

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.

Re: An Existential Crisis in Neuroscience

#19
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...

That's a bit silly because neuroscience tools are built got biological brains. electrical engineering tools are used on microprocessors, as they should.
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