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Neurons unexpectedly encode information in the timing of their firing

quantamagazine.org

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Re: Neurons unexpectedly encode information in the timing of their firing

#31
post #30

I find a lot of the common explanations of how the brain works in neuroscience to be unsatisfying… compared to molecular biology, it just feels like often we don’t have a solid (falsifiable, etc) grasp of what’s actually happening, yet… too much handwaving (for instance, the lack of any specifics on where precisely some data is located… even “it’s stored in the connections” seems not quite true or falsifiable… althou…

I mean, we can't really completely inspect a working brain to see what's happening. To get that level of inspection, we'd need to dig into the brain while it is functioning. Unfortunately, this kills the patient. And then the brain stops working. It's a black box essentially. We have tools that allow us some degree of insight, but honestly, it is incredibly difficult and progress is slow and staggered.

You might want to ask Google about two-photon microscopy links.

Example papers:

https://pubmed.ncbi.nlm.nih.gov/25391792/ -- "Two-photon excitation microscopy and its applications in neuroscience"

https://www.nature.com/articles/s41598-018-26326-3 -- "Three dimensional two-photon brain imaging in freely moving mice using a miniature fiber coupled microscope with active axial-scanning"

Sure, it's localized and you cannot go deep, but there is so much to learn that that is plenty at this point.

Re: Neurons unexpectedly encode information in the timing of their firing

#32
post #7

Earlier quoted context omitted.

it just feels like often we don’t have a solid (falsifiable, etc) grasp of what’s actually happening, yet… It feels like that, because it is like that: there's probably way more which isn't known about the brain yet, than things known with a decent amount of certainty. Just skimming over recent papers in the fundamental area, a lot of that summarizes as 'So here we found that area A is connected to area B and modulat…

My benchmark of "this thing is well understood" is that it's possible to build that thing, or a replacement for it, again. Kidneys probably meet that criteria - we have dialysis machines which allow someone to survive without kidneys almost perfectly. Yet the idea of replacing someones brain with something artificial and having them function as normal is still a LOOOOOOONG way off.

> My benchmark of "this thing is well understood" is that it's possible to build that thing, or a replacement for it, again.

Something I've been thinking a lot about lately: Implicit in statements like this is the idea of a system. That some complex-seeming artifact is actually composed of a relatively smaller number of essential things and all of the observed complexity is just emergent properties of the simpler underlying system. Find the handful of hidden rules and you can build back up to the whole thing from first principles.

For example, if you were to learn chess purely by watching people play, it would be a huge struggle at first. Does how they hold the pieces matter? What role does timing play? Why does one player rest their head on their cheek while staring at the board? Eventually you start to figure out which actions are essential and which aren't. It doesn't matter where inside a square a piece is placed. All pawns are behaviorally equivalent, etc.

We really really like systems. So much so that we tend to assume everything is one. But I see no evidence to assume that biology and evolution work that. Evolution is a semi-random walk over the phenotype space and fitter organisms are discovered (mutated) entirely randomly. It may be that a kidney mostly filters blood, but also does a little of this other thing, and the fact that it pushes your small intestine out of the way is important, and also and also and also...

We can increase our understanding by learning more, but there may simply be no "first principles" for what makes an organism tick and almost all of its complexity may be irreducible. There may be absolutely no separation between "fundamental property" and "implementation detail". It may be that no terms in the grand equation of life cancel out.

Re: Neurons unexpectedly encode information in the timing of their firing

#35

> For decades, neuroscientists have treated the brain somewhat like a Geiger counter: The rate at which neurons fire is taken as a measure of activity, just as a Geiger counter’s click rate indicates the strength of radiation. This hasn't been true for at least 20 years. There's a classic paper showing evidence of this in 1993 (O'Keefe and Reece) in rats. And has been an active area of discussion both before and sinc…

https://en.wikipedia.org/wiki/Neural_coding is pretty good too.

Re: Neurons unexpectedly encode information in the timing of their firing

#36

> For decades, neuroscientists have treated the brain somewhat like a Geiger counter: The rate at which neurons fire is taken as a measure of activity, just as a Geiger counter’s click rate indicates the strength of radiation. This hasn't been true for at least 20 years. There's a classic paper showing evidence of this in 1993 (O'Keefe and Reece) in rats. And has been an active area of discussion both before and sinc…

They mentioned this in the 3rd paragraph: "This temporal firing phenomenon is well documented in certain brain areas of rats, but the new study and others suggest it might be far more widespread in mammalian brains."

Re: Neurons unexpectedly encode information in the timing of their firing

#37

> For decades, neuroscientists have treated the brain somewhat like a Geiger counter: The rate at which neurons fire is taken as a measure of activity, just as a Geiger counter’s click rate indicates the strength of radiation. This hasn't been true for at least 20 years. There's a classic paper showing evidence of this in 1993 (O'Keefe and Reece) in rats. And has been an active area of discussion both before and sinc…

[deleted]

Re: Neurons unexpectedly encode information in the timing of their firing

#38

> For decades, neuroscientists have treated the brain somewhat like a Geiger counter: The rate at which neurons fire is taken as a measure of activity, just as a Geiger counter’s click rate indicates the strength of radiation. This hasn't been true for at least 20 years. There's a classic paper showing evidence of this in 1993 (O'Keefe and Reece) in rats. And has been an active area of discussion both before and sinc…

"Scholarpedia [.org] : the peer-reviewed open-access encyclopedia (where knowledge is curated by communities of experts)."

Thank you, thank you, thank you.

This fills an important gap.

Re: Neurons unexpectedly encode information in the timing of their firing

#39
post #30

I find a lot of the common explanations of how the brain works in neuroscience to be unsatisfying… compared to molecular biology, it just feels like often we don’t have a solid (falsifiable, etc) grasp of what’s actually happening, yet… too much handwaving (for instance, the lack of any specifics on where precisely some data is located… even “it’s stored in the connections” seems not quite true or falsifiable… althou…

I mean, we can't really completely inspect a working brain to see what's happening. To get that level of inspection, we'd need to dig into the brain while it is functioning. Unfortunately, this kills the patient. And then the brain stops working. It's a black box essentially. We have tools that allow us some degree of insight, but honestly, it is incredibly difficult and progress is slow and staggered.

I mean, we can't really completely inspect a working brain to see what's happening. To get that level of inspection, we'd need to dig into the brain while it is functioning. Unfortunately, this kills the patient

Leave out the completely and it's a different story though: it's perfectly possible to 'dig in while functioning' i.e. inspect small parts using electrode arrays and that will not kill the patient and only do minimal damage (the couple of cells killed by that are nothing in comparison with the entirety). Non-invasive fMRI techniques also have come a long way but temporal resolution is low. But as you say: difficult, slow, and by no means a 'complete' view. On the other hand: no idea how one would even begin to handle the insane amount of data which would come from inspecting a complete brain. So what goes on now, tackling smaller areas/connections thereof one by one, is not even that bad of an approach.

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