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Our Brains Use Binary Logic, Say Neuroscientists (sciencedaily.com)

"The brain's basic computational algorithm is organized by power-of-two-based logic," reports Sci-News, citing a neuroscientist at Augusta University's Medical College. hackingbear writes: He and his colleagues from the U.S. and China have documented the algorithm at work in seven different brain regions involved with basics like food and fear in mice and hamsters. "Intelligence is really about dealing with uncertainty and infinite possibilities," he said. "It appears to be enabled when a group of similar neurons form a variety of cliques to handle each basic like recognizing food, shelter, friends and foes. Groups of cliques then cluster into functional connectivity motifs to handle every possibility in each of these basics. The more complex the thought, the more cliques join in."

69 comments

  1. 0001'st post by Anonymous Coward · · Score: 0, Insightful

    0001' st post

  2. Not sure by Anonymous Coward · · Score: 0

    Is this true or false?

    1. Re:Not sure by alvinrod · · Score: 3, Insightful

      Yes

    2. Re:Not sure by Anonymous Coward · · Score: 0

      Ahhh....... A PHP developer...

      CAP === 'discreet' (the CAP had it spelt wrong)

    3. Re: Not sure by Anonymous Coward · · Score: 0

      There are various languages that support this, doesn't have to be a lame old web language.

    4. Re:Not sure by istartedi · · Score: 1

      Kind of the first joke I thought of too; but... what if our desire to ask such questions is the result of some sort of built-in bias? What if truth is N-dimensional and we just can't conceive of it in any real way? Note, not gradations of T and F, but an actual N-dimensionality of veracity. Like, I'm telling the truth, I'm telling a lie, or I'm telling an arrow.

      --
      For all intensive purposes, "whom" is no longer a word. That begs the question, "who cares"?
    5. Re:Not sure by vlad30 · · Score: 1

      Of course the world is full of two bit people hen decreasing in number 4bit , 8 bit 16,32,64 all the way out to 512 bit and beyond of in color terms those that see in black and white to those that can see shades of grey and and the whole color spectrum but like color beyond 32 bit it gets hard to tell the difference

      --
      Your'e all thinking it, I just said it for you
    6. Re: Not sure by Anonymous Coward · · Score: 0

      seems like you didnt check development in PHP in last few years :) Do not get me wrong, I do not like it either but it went zanzilions miles from lame language it used to be in last few years ;)

    7. Re: Not sure by WarJolt · · Score: 1

      The world is analog. Digital is just a high gain approximation. In nueral networks we spend huge computational resources to approximate digitally the stochastic processes at work a single nueron. The brain isn't even close to being digital.

    8. Re:Not sure by istartedi · · Score: 1

      Simply having a larger word size isn't what I'm talking about though. Larger word sizes are just a composition of binary bits. I'm thinking more like the Flatland analogy. We know what true and false are, but we don't know what "arrow" is.

      In Flatland, a sphere projects onto the plane and is perceived as a circle. In our world, an "arrow" veracity might project as a paradox. For example, "everything I'm telling you is a lie" is a classic statement that defies analysis as "true" or "false". Perhaps it's an "arrow" statement projected onto our world.

      --
      For all intensive purposes, "whom" is no longer a word. That begs the question, "who cares"?
    9. Re: Not sure by lucien86 · · Score: 1

      (Puts dark glasses on.) The brain is digital. The brain is made of atoms and atoms are digital, look closely enough and everything is digital. Of course that is pedantic nonsense but that is how I'm feeling today. :) (because the number of atoms in the brain changes constantly and atoms are below our point of consideration - ie in most circumstances they effectively don't exist as individual objects.)

      (More sensibly) Anyone who reads even the basics of neural signalling will tell you that brains use hybrid digital analog logic. Neurons use pcm coding which transmits both digital and analogue signals using variable timing in trains of pulses.. It is pretty bizarre if they use binary arithmetic as well, it sounds like the article is not talking about arithmetic directly though but communications logic - which is something totally different.

      --
      Below the speed of light Special Relativity is one of the most accurate theories in physics - above the speed of light..
    10. Re:Not sure by Anonymous Coward · · Score: 0

      The universe is binary, so no surprise.

  3. Yup by pubwvj · · Score: 1

    2^11

  4. New! Brains! Digital Ready! by Anonymous Coward · · Score: 0

    Member digital ready? Member?

  5. Neurons either fire or don't fire. by Pezbian · · Score: 1

    It's pretty much obvious at first glance.

    --
    In a world of the blind, the one-eyed man is king--and the two-eyed man is a heretic.
    1. Re:Neurons either fire or don't fire. by Anonymous Coward · · Score: 2, Insightful

      except that patterns of firing matter.

      look up eg. P3a and P3b (components of P300s) for some of the simplest examples.

    2. Re:Neurons either fire or don't fire. by JoeMerchant · · Score: 5, Interesting

      It starts out obvious, but then factors like conduction speed, receptor sensitivity, calcium channel recharge rates, etc. etc. all factor in to make a "wet" neural network quite a bit more complex and nuanced than an electronic network of NAND gates.

      One of the open questions in "brain replication" is: can you get the same end result without the delays, varying sensitivity, numbing from multiple firing, etc.?

      OP seems to be saying that they think the hierarchy is using binary structures, but not that the firing/not firing is a simple 0 or 1 condition.

    3. Re:Neurons either fire or don't fire. by K.+S.+Kyosuke · · Score: 1

      Yes, but there's so many of them that filtering the incoming intermediate signals can yield fuzzy logic.

      --
      Ezekiel 23:20
    4. Re:Neurons either fire or don't fire. by mapkinase · · Score: 1

      >OP seems to be saying that they think the hierarchy is using binary structures, but not that the firing/not firing is a simple 0 or 1 condition

      How could they tell?

      --
      I do not believe in karma. "Funny"=-6. Do good and forbid evil. Yours, Oft-Offtopic Flamebaiting Troll.
    5. Re:Neurons either fire or don't fire. by Anonymous Coward · · Score: 2, Interesting

      factors like conduction speed, receptor sensitivity, calcium channel recharge rates, etc. etc. all factor in to make a "wet" neural network quite a bit more complex and nuanced than an electronic network of NAND gates.

      Clocks, wire delay, V-F curves and other things are all issues in electronic networks. It's all analog down there. And then it's all quantum under that.

      One of the open questions in "brain replication" is: can you get the same end result without the delays, varying sensitivity, numbing from multiple firing, etc.?

      I would suspect that the processes in brain are as robust as necessary for the survival of the biological organism and to minimize energy consumption, and as non-robust as necessary for the same reasons. Digital electronics common today is also sufficiently robust when operating under the specification as to allow it to do useful work over the whole manufacturing batch. As near-threshold computing ideas spread into the digital domain, perhaps brain-style of robustness comes a theme in some areas of digital electronics as well.

    6. Re:Neurons either fire or don't fire. by Anonymous Coward · · Score: 0

      Prayer.

    7. Re: Neurons either fire or don't fire. by Jfetjunky · · Score: 3, Insightful

      The difference is we actively attempt to overcome those non-idealities in electronics to get a deterministic result. They same cannot necessarily be said for neural networks. At times their core functionality works with the non-ideal features ofor the system.

    8. Re:Neurons either fire or don't fire. by Anonymous Coward · · Score: 0

      That transition from two-valued to infinite valued logic confuses the toughest of us.

    9. Re:Neurons either fire or don't fire. by JoeMerchant · · Score: 4, Interesting

      There's an interesting theory running around Neuroscience (and, let me tell you what a Harvard educated neuroscientist said about virtually all neuroscience and brain studies: "they're great theories, they've got tiny experimental observations to back them up, they're basically pulling all of this out of their asses.") so, anyway, the theory goes that "thoughts" are encoded as repeating firing patterns. As far as I understand the theory and what little I read of OP, the patterns themselves are more nuanced than binary, but one "idea" might be encoded as firing pattern like ..-..- ..-..- while a competing idea might be encoded as a different firing pattern: ...---... ...---... so, there can be thousands of distinct firing patterns (continuing the morse code analogy, even a simple 3 letter code holds over 17000 unique patterns, make those inter-firing intervals analog and a virtual infinity of patterns can be encoded with 8 to 10 intervals) so, groups of neurons start "singing" their songs based on inputs from other areas of the brain/body, usually several different patterns based on competing inputs from different "source" areas. The neurons in a "processing node" sort of fight it out, each repeating their idea of the "right" firing pattern until they reach some form of consensus, then that coherent pattern becomes a "valid" input to the next level of processing, which itself may be getting inputs from a bunch of different areas that it has to hash out until it can reach a coherent pattern to pass along. Eventually, these "ideas" fire off motor control routines and actuate the body to move, speak, etc.

      The thing that's most intriguing to me about this theory is that it's somewhat repeated in human society. We get together, repeat ideas among small groups, pass them along to "higher levels" and eventually act as societies to do things. Now, with the internet, we have billions of people acting in some ways like neurons in a brain, reaching consensus about some things and chanting in chaotic disagreement about others.

    10. Re:Neurons either fire or don't fire. by Anonymous Coward · · Score: 0

      There are differences between duration of excitation. Ask your girlfriend, if any :D

    11. Re:Neurons either fire or don't fire. by Vasheron · · Score: 2

      The thing that's most intriguing to me about this theory is that it's somewhat repeated in human society. We get together, repeat ideas among small groups, pass them along to "higher levels" and eventually act as societies to do things. Now, with the internet, we have billions of people acting in some ways like neurons in a brain, reaching consensus about some things and chanting in chaotic disagreement about others.

      What you have just described is Marvin Minsky's Society of Mind, which was the subject of his 1986 book. You stand in good company.

    12. Re:Neurons either fire or don't fire. by Darinbob · · Score: 1

      That's no how neurons work. They fire with different amounts. More like transistors than switches.

  6. Obligatory by Anonymous Coward · · Score: 0

    There are 10 types of people.

    Those who understand binary, and those who don't.

    1. Re:Obligatory by K.+S.+Kyosuke · · Score: 2

      There are 10 types of people: those who understand number systems, and 10-1 of those who don't realize that every base is base 10 in base 10.

      --
      Ezekiel 23:20
    2. Re:Obligatory by rhodium_mir · · Score: 1

      *golf clap*

      --
      You can't spell "oneiromancy" without "roman".
    3. Re:Obligatory by Anonymous Coward · · Score: 0

      All your base are belong to us.

    4. Re:Obligatory by Lotus456 · · Score: 1
      --
      "It's a good computer... for I to BM on!" - apologies to Triumph, the insult comic dog
    5. Re: Obligatory by Anonymous Coward · · Score: 0

      Did you just assume my gender?

    6. Re: Obligatory by Anonymous Coward · · Score: 0

      If you want to have some fun, replace 10 with x. Just base X. Then think about all those polynomials you learned about in high school. They were all in base X.

    7. Re:Obligatory by Zeroko · · Score: 1

      & those who think ternary jokes are better.

  7. This representation does not seem compact by presidenteloco · · Score: 2

    I only glanced at the news article summary of the research, but it seems like they're saying you need an exponential number of neuron groups compared to the amount of information in bits that is coming in or being classified. It's hard to see how ONLY this organizing principle could be efficient in terms of amount of matter and energy needed to store the info.

    There must be another organizing principles going along with this, to make it representationally and physically efficient.
    Principles such as perhaps:
    1) The cliques are organized in an efficient representation abstraction hierarchy
    2) Only create neuron cliques for those combinations of things which DO occur, rather than the exponential number of possible combinations which do not occur in the world. i.e a sparse distributed representation, as has been suggested in other neuroscience and computational neuroscience research.

    --

    Where are we going and why are we in a handbasket?
  8. Smells bullshitty by Anonymous Coward · · Score: 2, Interesting

    I mean, maybe it's just bad reporting, but seriously:

    At the heart of the Theory of Connectivity is the algorithm, N=2i–1, which defines how many cliques are needed for an FCM and which enabled the authors to predict the number of cliques needed to recognize food options, for example, in their testing of the theory.

    “N is the number of neural cliques connected in different possible ways; 2 means the neurons in those cliques are receiving the input or not; i is the information they are receiving; and -1 is just part of the math that enables you to account for all possibilities,” Dr. Tsien said.

    First off, that's not an algorithm but an equation. i is the information they're receiving? But in context, i is a number. Finally, "the part of the math that enables you to account for all possibilities"? what does that even mean?

    1. Re:Smells bullshitty by narcc · · Score: 2

      While I have no doubt the reporting is bad, I doubt the "science" is much better.

    2. Re:Smells bullshitty by Serge_Tomiko · · Score: 1

      Neuroscience is entirely bullshit. It's amazing it still exists now 13 years after the human genome was decoded.

    3. Re:Smells bullshitty by tgv · · Score: 1

      First: the humane genome has not been decoded. We've got a string of [AGCT]*, that's it. What it means, we don't know.

      Second: neuroscience is the modern name for a combination of cognitive psychology and neurobiology. It is a serious, complex and worthy subject of research, but there are a lot of bad researchers. It's unfortunately easier to get into neuroscience than into physics.

    4. Re:Smells bullshitty by Anonymous Coward · · Score: 0

      You mean brain shouldn't be studied using available methods because of genomics? It would be like a zoologist giving up studying animal behaviour after finding a piece of dung or a hair.

    5. Re:Smells bullshitty by peawormsworth · · Score: 1

      2^i is just the total number of combinations that a binary number of i digits can contain. They subtract 1 for the number "0" because that would represent no input food presented. What they found is that the number of "cliques" (N) required to identify between a number of "inputs" (i) is the same as if that brain had classified those items into a binary number.

      Maybe soon discover that colour is processed in 24bit RGB

    6. Re:Smells bullshitty by Anonymous Coward · · Score: 0

      Surely more variability than that.

      It doesn't explain tetrachromats, for example.

  9. Imagine a spherical cow... by Anonymous Coward · · Score: 0

    Neurons only work on binary if you ignore all the ways they don't and summarize things down to the point of being wrong.

  10. Neural modeling made easy by Dread_ed · · Score: 2

    This seems to say that by interlinking subsets of binary decision modules you can simulate (or create?) a silicon based system that will approximate the decision tree of a biological entity. Toss in an additive memory system that enhances pattern recognition based on past experience (machine learning compatible?) and you have a system that will grow in discernment the way biological systems do. The trick would seem to be in modeling the appropriate type and number of these underlying modules, designing them to revise their output based on the relevant memory experience, and then assigning priority to the outputs from those modules, giving self preservation and threat detection precedence for instance.

    (Half cocked speculation) I can see custom cores designed to evaluate input based on their own narrow realm of specialization (food, friend/foe, threat/non-threat, shelter, etc. could be analogous to other machine relevant inputs) and with their own memory stores of experiential reference material. These feeder cores would process input with regard to their own specialization and then hand off their individual result to another coordinating core designed to integrate results from the feeder cores. The coordinating core would have a prioritization system to weight the inputs and handle conflicts. The coordinating core would also build an experiential database comprised of inputs from the other core modules and the results of the decisions made from those inputs and the viability of the decisions.

    Emergent phenomena and complexity would seem to be a logical result of the combination of a large array of interacting modules provided the output space is varied and robust.

    --
    When the only tool you have is a claw hammer every problem starts to look like the back of someone's skull.
    1. Re:Neural modeling made easy by ShooterNeo · · Score: 1

      Yeah I think that is also what it is saying. We should be able to upgrade our neural network models to use this method of organization and get more performance. We should also be able to mimic any single subsystem of the human brain in the relatively near future*. Mimicking a full brain - what we think of as a general purpose artificial intelligence - is still immensely harder because of all the complex relationships between subsystems and the vast amount of memory and hardware we'll need. Even the massive GPU/ASIC clusters Google is using are nowhere close to the scale of a full human brain. It really partially is just a matter of hardware.

      * I mean in terms of utility, not in terms of being an exact copy of neural hardware.

  11. Matrix by Anonymous Coward · · Score: 0

    So it's true. We are living in a computer program.

    1. Re:Matrix by Anonymous Coward · · Score: 0

      So it's true. We are living in a computer program.

      And it's full of GOTOs.

  12. use the Semantic Scholar, Luke by epine · · Score: 3, Interesting

    I've been waiting for a good opportunity to take this new toy out for a spin. Semantic Scholar claims to have brain science almost completely covered.

    * author search

    Not bad.

    * topic search

    Not blindingly great. But the third link down is a primary hit.

    Theory of Connectivity: Nature and Nurture of Cell Assemblies and Cognitive Computation

    There's not a lot of related material here that I'd have gone chasing after the hard way. Apparently, either this research result or this search engine is still too new.

    Nevertheless, I retain high hopes.

  13. Whose science? by Anonymous Coward · · Score: 0

    Maybe for the most rudimentary mental processes, but I can tell you with certainty that true creative thinking, real critical thinking, abstract thinking most certsinly does not rely on binary logic. In fact, it relies greatly on the ability of the thinker to question their own thoughts. More bullshit science from the department of meh.

  14. Seven different brain regions? by by+(1706743) · · Score: 1

    They must mean eight (numbered 0-7, of course).

    1. Re:Seven different brain regions? by Tough+Love · · Score: 2

      No, 7, because 0 is the broadcast address

      --
      When all you have is a hammer, every problem starts to look like a thumb.
  15. The understanding of intelligence by Anonymous Coward · · Score: 0

    In Silicon Valley is apalling. I know you think you are smarter, but the tendency is to seriously miss the forest for the trees, which I suspect is largely a symptom of youth. Based on a binary system, which all computing is, simply out of necessity, the best anyone can hope for is essentially a glorified calculator. Can we move on, please? The world has legitimate problems.

  16. Groups ... cluster into functional by Anonymous Coward · · Score: 0

    sounds a lot like hermann hesse's theater of the mind;-)

  17. Re:the delays, varying sensitivity, numbing by Anonymous Coward · · Score: 0

    not to mention the effects of various drugs/meditation/etc;-)

  18. Misleading title on TFA by ShooterNeo · · Score: 3, Informative

    Summary of the TFA : the actual method of brain signaling is primarily all or nothing electrical impulses. The timing is analog - THEORETICALLY a difference in an electrical impulse arriving down to the planck-second could have an effect.

    This research does not change any of this. The brain is still analog at the individual synapse level, it just follows certain patterns that are related to binary math for setting up arrays of neural circuitry.

    In practice, like any analog system, true resolution is finite because there is noise. So the system merely needs to be quantized down to the level of resolution of noise and you can replicate it's behavior exactly in a digital equivalent. Remember analog PIDs and other simple analog computers, the ones that used vacuum tubes and were used from ww2 and a few decades after? Those systems also had finite effective resolution even though analog systems theoretically have infinite resolution. That was because of all the various forms of noise in the actual physical equipment. In practice if you replace an analog system with a digital system you can get BETTER resolution because all the intermediate processing steps do not introduce additional noise. (while each vacuum tube op amp you solder in picks up extra noise that is added to the signal)

    1. Re:Misleading title on TFA by Anonymous Coward · · Score: 0

      The brain is still analog at the individual synapse level...

      Forgive my ignorance: what, exactly, is the brain at the individual synapse level an analog of? Or is the assumption that the brain is NOT digital, therefore it can only be analog?

  19. Yeah right. by backslashdot · · Score: 1

    The most shocking part of this study is that the human brain uses logic. The authors thought they could slip that through? Who's going to believe it?

    1. Re:Yeah right. by Tablizer · · Score: 1

      The most shocking part of this study is that the human brain uses logic.

      It is shocking for those of us shocked over the election results.

    2. Re:Yeah right. by Anonymous Coward · · Score: 0

      Given the two frontrunners for this past presidential campaign, I find it shocking that anybody would be shocked over the elections results regardless of who won!!!

  20. Sounds like a logical capacity estimate... by BlueCoder · · Score: 1

    Neural network can produce logic or lossy yet meaningful metrics and then you can yet combine multiple levels and have precognitive assumptions and or forceful cognitive assumptions. Result: deterministic complexity vs statefull and relevant guesses.

    Static logic is best left to assembly code and extrapolated guesses to trained neural matrices. Repeat after me... left, right.. left, right... left, right...

  21. Think Minions chasing bananas by John+Allsup · · Score: 1

    Being saying this for years. If our braun behaviour is a consequence of neurin behaviour, this is inevitable. Think of a horde of Minions, each with a different idea of what a banana looks like, and a single button each to press if they see what they think is banana.

    --
    John_Chalisque
  22. Given exactly the same information, twice by Anonymous Coward · · Score: 0

    Can you build a computer which gives a different answer? I know several rather simple minded people who have mastered this.

  23. So its NOT binary logic? by Anonymous Coward · · Score: 0

    How did these guys become scientists? Is it a lottery now?

  24. Well, sort of, maybe by JimSadler · · Score: 1

    Sure we have binary circuits in the brain but logic is another issue completely. Humans will have all kinds of things going on that do not relate to the task or subject at hand. For example, looking good, retaining a posture of self, or showing that you can act up at times, may take precedence over accomplishing the goal at hand. Logic is not really a human characteristic.

  25. Welcome to the new Slashdot... by MikeDataLink · · Score: 1

    It's just Buzzfeed with a different web design and the same old trolls.

    --
    Mike @ The Geek Pub. Let's Make Stuff!
  26. In Related News by Anonymous Coward · · Score: 0

    Different parts of the brain talk to eachother and some pot-smoking hippy described it in a very idiot way.