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Neuroscience Can't Explain How a Microprocessor Works (economist.com)

mspohr writes: The Economist has an interesting story about two neuroscientists/engineers -- Eric Jonas of the University of California, Berkeley, and Konrad Kording of Northwestern University, in Chicago -- who decided to test the methods of neuroscience using a 6502 processor. Their results are published in the PLOS Computational Biology journal. Neuroscientists explore how the brain works by looking at damaged brains and monitoring inputs and outputs to try to infer intermediate processing. They did the same with the 6502 processor which was used in early Atari, Apple and Commodore computers. What they discovered was that these methods were sorely lacking in that they often pointed in the wrong direction and missed important processing steps.

8 of 169 comments (clear)

  1. Modern (pseudo)-"Science" by Anonymous Coward · · Score: 5, Insightful

    In order to understand the DNA of an Orange, we "scientists" dissected an alarm clock. This _proved_ that our methods of studing oranges, and fruit in general, have been wrong for centuries.

    1. Re:Modern (pseudo)-"Science" by Tablizer · · Score: 4, Insightful

      I see a lesson in humility here by looking at how poor human scientists do at modelling-by-studying-defects in a general sense.

      It suggests that models of the brain derived by seeing what effects damaged sections have on patient behavior may be worse than originally expected.

  2. Re:Massive failure from all involved by im_thatoneguy · · Score: 5, Insightful

    This isn't so much about modeling thought processes as it is about illustrating how even in a simplified model one of our debugging approaches fails.

    The logic that they're arguing appears to be:

    "If we can't even properly reverse engineer an extremely simple deterministic computer chip using fault modeling, it's extremely unlikely that we can infer the mechanisms of an extremely complex non-deterministic processor like the brain."

  3. Re:Massive failure from all involved by ShanghaiBill · · Score: 5, Insightful

    "If we can't even properly reverse engineer an extremely simple deterministic computer chip using fault modeling, it's extremely unlikely that we can infer the mechanisms of an extremely complex non-deterministic processor like the brain."

    But that logic only makes sense if microprocessors and brains were similar enough that comparable methods could be used to attempt to understand them. But that isn't true. That is like saying you can't understand how to plow a field with a horse if you don't understand how a tractor engine works. Although horses and tractors have some similarities, understanding how one works doesn't really help you with the other.

  4. Re:Intelligent design by Anonymous Coward · · Score: 5, Insightful

    All jokes asside, I think the point here was that both devices (6502 or fatty-thinkmeats) were modeled as a black box. I'd be willing to be that a significant fraction of the neuroscientist population would argue for a 6502 being the simpler system, so the blackbox approach should (one would hope) be able to model that device more easily. If they find that their blackbox approach to understanding a 6502 leads to incorrect results, then it raises questions as to the effectiveness of the approach on the thinkmeats.

  5. Re:No Surprises There... by TapeCutter · · Score: 1, Insightful

    Neuroscience can't explain a microprocessor, computer science can't explain a mind. In no way does this mean that neuroscience cannot be advanced by computer science or visa versa.

    --
    And did you exchange a walk on part in the war for a lead role in a cage? - Pink Floyd.
  6. Re:Massive failure from all involved by John+Allsup · · Score: 5, Insightful

    The point of the argument is to challenge the implicit assumption that current neuroscience methods work as well as people think they do. If you just assume your research methods work, you are resting on blind faith in your methods. One step in showing the need to challenge those foundational assumptions is to use this example to //illustrate// how then can fail. Using microprocessors allows is the luxury of total knowledge as to what we are investigating, at the expense of being quite different to the brain. The quoted bit needs fixing:

    "If we can't even properly reverse engineer an extremely simple deterministic computer chip using fault modeling, it's extremely unlikely that the same fault modelling will work reliably with something extremely complex like the brain."

    It does not show whether or not 'fault modelling' works or not for the brain, but gives good justification for the claim that we cannot take the efficacy of 'fault modelling' for granted when studying the brain.

    --
    John_Chalisque
  7. Re:Massive failure from all involved by hey! · · Score: 3, Insightful

    Or, for that matter, why alt-right trolls are such stupid bigots?

    Neuroscience can't, but eugenics can. Eugenics can explain anything. There are some thing neuroscience can't explain.

    That's why neuroscience is science but eugenics is not.

    --
    Post may contain irony: discontinue use if experiencing mood swings, nausea or elevated blood pressure.