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A microprocessor is admittedly a poor metaphor for a brain. However, I think the article still makes a strong point, which is that neuroscientists use many expe

by glial 10y ago

A microprocessor is admittedly a poor metaphor for a brain. However, I think the article still makes a strong point, which is that neuroscientists use many experimental and signal-processing techniques whose utility hasn't even been demonstrated in principle, much less in practice. To me that's the largest take-away from this article. To use a set of techniques to investigate the operation of a device whose function we fully understand, and still fail to draw meaningful conclusions, raises serious questions about the usefulness of those same techniques in a much more complicated and less-well-understood domain.

enord 10y ago
>However, I think the article still makes a strong point, which is that neuroscientists use many experimental and signal-processing techniques whose utility hasn't even been demonstrated in principle, much less in practice. This is the point. There are multiple levels of interpretation layered on top of the physical process. There is no reason to believe that they are tidy or hierarchical either, abstractions and indirections can leak left and right (or top to bottom). We lack the language and tools to describe these structures laid bare, and words like "abstraction" and "indirection" are probably a bad fit. Even "interpretation" might prove to be conceptually misleading when cracking this nut, so to speak.
SubiculumCode 10y ago
and yet we know alot. Hippocampal damage causes deep amnesia, prefrontal damage leads to poor inhibition, introspection, etc. I could go on.
- TheOtherHobbes 10y ago
  That's not a lot - that's actually very little. We have a crude 3D map of some of the top-level systems, but very little idea how or why they work as they do. Which is not a surprise. Imagine someone hands you an encapsulated CPU and you don't know what a clock is, what external memory is, or what an instruction set is. How long will it take you to understand what it does and how it works? Now let's say you know what a gate is, and you take the top off and reverse engineer the circuit. Does that help? IMO, not as much as we'd all like. For a CPU the important information isn't in the connectome, it's in the design manual. It's a fair bet the brain is rather more complicated. And there's no manual. Having a crude map of some top-level systems is a good start, but I'm surprised that there seems to have been a lot of labelling and identification, but comparatively little interest in investigating how information is passed between the subsystems and how they function together.
- drzaiusapelord 10y ago
  That's a bit like saying you're know 'a lot' about SSD design because you know taking a hammer to it breaks the computer in some way. I think we probably know a lot less than laymen assume. Its a big conversation to define "what we know" but "a lot" assumes at theoretical and experimental groundwork that most likely doesn't exist. I find the research I've been exposed to is a mile wide but an inch deep. If we had more depth, we'd be hobby coding AI because we'd understand the basic concepts the same way a even jr developer can do enough research to hobby code a complex and featured 3D game engine, something a coder from the 60 or 70s couldn't do. We simply don't have these kinds of understandings.
- glial 10y ago
  We do know a lot, but I would argue that much of what we know is not a result of the techniques used in this article. The things you mention are results of lesion experiments or observations, which are decades (or more) old. Most of what you mention is sort of negative information - what happens when the brain breaks. How it works is a fundamentally different question, and I suspect we'll only get real understanding by building computational models that are able to do similar computations to those the brain does.

by glial 10y ago

enord 10y ago

>However, I think the article still makes a strong point, which is that neuroscientists use many experimental and signal-processing techniques whose utility hasn't even been demonstrated in principle, much less in practice. This is the point. There are multiple levels of interpretation layered on top of the physical process. There is no reason to believe that they are tidy or hierarchical either, abstractions and indirections can leak left and right (or top to bottom). We lack the language and tools to describe these structures laid bare, and words like "abstraction" and "indirection" are probably a bad fit. Even "interpretation" might prove to be conceptually misleading when cracking this nut, so to speak.

SubiculumCode 10y ago

and yet we know alot. Hippocampal damage causes deep amnesia, prefrontal damage leads to poor inhibition, introspection, etc. I could go on.

TheOtherHobbes 10y ago
That's not a lot - that's actually very little. We have a crude 3D map of some of the top-level systems, but very little idea how or why they work as they do. Which is not a surprise. Imagine someone hands you an encapsulated CPU and you don't know what a clock is, what external memory is, or what an instruction set is. How long will it take you to understand what it does and how it works? Now let's say you know what a gate is, and you take the top off and reverse engineer the circuit. Does that help? IMO, not as much as we'd all like. For a CPU the important information isn't in the connectome, it's in the design manual. It's a fair bet the brain is rather more complicated. And there's no manual. Having a crude map of some top-level systems is a good start, but I'm surprised that there seems to have been a lot of labelling and identification, but comparatively little interest in investigating how information is passed between the subsystems and how they function together.
drzaiusapelord 10y ago
That's a bit like saying you're know 'a lot' about SSD design because you know taking a hammer to it breaks the computer in some way. I think we probably know a lot less than laymen assume. Its a big conversation to define "what we know" but "a lot" assumes at theoretical and experimental groundwork that most likely doesn't exist. I find the research I've been exposed to is a mile wide but an inch deep. If we had more depth, we'd be hobby coding AI because we'd understand the basic concepts the same way a even jr developer can do enough research to hobby code a complex and featured 3D game engine, something a coder from the 60 or 70s couldn't do. We simply don't have these kinds of understandings.
glial 10y ago
We do know a lot, but I would argue that much of what we know is not a result of the techniques used in this article. The things you mention are results of lesion experiments or observations, which are decades (or more) old. Most of what you mention is sort of negative information - what happens when the brain breaks. How it works is a fundamentally different question, and I suspect we'll only get real understanding by building computational models that are able to do similar computations to those the brain does.