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gib65

What do scientists not yet understand about the brain?

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Computers and Brains work essentially the same way. A neuron is fired on, or it remains off. Computers use binary code in much the same way. According to the singularity theorem, the technology will exsist so that we can upload our conciousness onto a computer. Hence "Singularity" - humans and computers becoming one.

 

For more info see http://www.kurzweilai.net

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This has to be the worst thread that has ever been posted.We have had the sublime to the ridiculus,but never has so much claptrap been spoken in one thread.The human brain is so complex we are only now just starting out on the road to understanding the electrical impulses that take place.But by some posts here,you would think that its all common knowledge....honestly im very angry at peoples idiotic comments.Im usually the poster of controversial subjects but this is just stupid.

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Artorius,

 

Calling this thread "stupid" is a blatant oxymoron with the statement you made just a few sentences ago: "The human brain is so complex we are only now just starting out on the road to understanding the electrical impulses that take place." If it's so complex and beyond our comprehension, how could a thread discussing the topic be "stupid"? The fact that we have people posting opinions on both sides of the fences shows that we can't all be as ignorant about it as you seem to think. I don't think there's anyone here who thinks the workings of the brain in its entirety are "common knowledge" but there are some of us who think there is some common knowledge that explains some of the workings of the brain. If not, then all our neuroscientific progress (albeit, very little with respect to how much there is to gleen from the brain) has been made in vain. But if you get so "very angry" at some of the comments that are bound to be posted on such a hot topic, then, rather than making your problem our problem, maybe it would be best for all of us if you just made a good example of your own preaching and didn't post here.

 

Quixix,

 

I will be replying to your posts soon. Good reads, BTW.

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Very interesting reads. And now for my rebuke.

 

First of all, with respect to Stefan Lovgren's article, there's a few quotes that seem to touch on the differences between computers and brains. A couple of the most relavant are...

 

"Silicon-based computers are very accurate and fast at processing some kinds of information, but they have none of the flexibility of the human brain."

 

and

 

"Brains can easily make certain kinds of computations that computers are unable to do, such as answering open-ended questions about what happened sometime in the past."

 

These, to me, point out some of the differences between computers and brains, but that should be expected. The comparison between brains and computers should not be confused with equating the two. At best, the brain is like a computer, and a computer is like a brain. Surely there will be differences. More specifically, this article points out how our current technology has yet to emulate some of the abilities the brain can accomplish, but this does not mean it never will, and if it does, there is no reason to assume it will have to apply principle above and beyond those of computational mathematics. Our lack of understanding how the brain accomplishes some of the amizing feats it does is no reason to throw the computer model out the window. It may still just come down to algorithms that we have not had the ingenuity to conjure up. Moreover, after reading this article, what with brains being connected to computers, being fed inputs and emitting outputs, controlling a flight simulator, etc., it seems the computer model is probably the most appropriate.

 

With respect to Peter Dayan's article, I should humble myself as this writer seems a lot more eloquent than I can handle. He has a heavy vocabulary, and I admit I had to look up a few of the words, but if I understand the overall position he takes (and Hawking's), I'll just say that I don't quite understand how his article merits disposing of the computer model of the brain. I can see how the "unsupervised learning" model would make the "home PC" unfit as an analogy, but there are many different types of computers out there, and I can easily conceive of one whose main function is to extract statistical structures from inputs (it wouldn't even have to have a central processor). Furthermore, it's suprising how you selected this article since Dayan doesn't seem that keen on Hawking's ideas to begin with.

 

If there are differences between brains and computers to be gleened from these articles, they are ones of specific algorithms. It is in how the brain computes the information it receives, and not that it computes information point blank.

 

Overall, I'm not convinced. That's not to say I can't be. When I started this thread, what I was generally trying to ask was if there are any studies or evidence out there to support the idea that it requires more than just the phenomena of electric impulses traveling down the axons of neurons and chemicals crossing the synaptic gaps in order to explain the activity of the brain. Obviously, it would require more than this to explain consciousness, so never mind that for now. Let me restate the question: "Is the human brain a deterministically closed system? Any unassailable evidence for or against this?" And, honestly, I am open to good points on either side.

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Computers and Brains work essentially the same way. A neuron is fired on, or it remains off. Computers use binary code in much the same way.

I'm not sure this is strictly true. For example, a neuron may fire, but it's effect is not always exitatory. It may be inhibitory (increasing the AP threshold in the next neuron). We also have neurones that signal when they're 'off' (e.g. the 'dark' current in retinal cells). We also have temporal and spacial summation and long term potentiation. We also have retrograde messaging where information is sent chemically back up an axon. I'm no expert on computers, but I doubt very much that computer circuits display many/any of these properties.

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Not only that, but the signal patterns in the brain are not handled in anything approaching the same fashion, neither is instruction processing.

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I'm no expert on computers, but I doubt very much that computer circuits display many/any of these properties.

During my studies of Neural Cybernetics, most all of these functions can be replicated with Logic Gates without any real difficulty.

so at THAT level, there`s no problem at all :)

 

the problem arises when trying to merge these into some sort of usable system of any complexity. Emergent "Bahavior" isn`t uncommon on even the most simple of structures, but to get anything even close to a Mosquitoes "brain" would be a challenge for the best, and actualy getting it WORK is another story too!

 

the basics we can replicate, complete systems are a different kettle of fish.

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Very interesting reads. And now for my rebuke.

 

First of all' date=' with respect to Stefan Lovgren's article, there's a few quotes that seem to touch on the differences between computers and brains. A couple of the most relavant are...

 

"Silicon-based computers are very accurate and fast at processing some kinds of information, but they have none of the flexibility of the human brain."

 

and

 

"Brains can easily make certain kinds of computations that computers are unable to do, such as answering open-ended questions about what happened sometime in the past."

...

Overall, I'm not convinced. That's not to say I can't be. When I started this thread, what I was generally trying to ask was if there are any studies or evidence out there to support the idea that it requires more than just the phenomena of electric impulses traveling down the axons of neurons and chemicals crossing the synaptic gaps in order to explain the activity of the brain. Obviously, it would require more than this to explain consciousness, so never mind that for now. Let me restate the question: "Is the human brain a deterministically closed system? Any unassailable evidence for or against this?" And, honestly, I am open to good points on either side.[/quote']

 

I am no trying to convince anyone, just trying to help along with different thoughts an ideas. I refer back to your first post:

"So I was just wondering: is this all there is to it? I mean, I'd expect that the exact nature of a neuron is a little bit more complicated than being a conductor, and there might be mysteries to them that to date stump the neuroscientific community, but from what I understand these mysteries (if they exist) shouldn't change how we currently understand the brain to work (i.e. as an organic computer)"

As far as I know, computers do not have (yet) plasticity in their connections. I am an expert at neither computers or brain. But I do know that the role of neurons is much more complex than that of a simple conductor. They have mechanisms by which they recognize from which synapse the inputs come and "remembering" it, they can generate new synapses, reinforce them or weaken them. These mechanisms are quite well known. But to me they don't explain quite well how knowledge is stored, if it is not by forming networks that are continuosly being modified and activated by inputs, be they endogenous or exogenous, reliving the original experience.

Handling information is one thing, storing it is another. I can not visualize any simil of the function of the hard disk (or any other memory gadget) with the function of any particular part of the brain. Perhaps there is one, but I have not been able to find it in the literature.

I do not know if computers can progress from specific to abstract concepts, which the brain does.

And there us also the "mistery" of consciousness. Although it has had some strong crticism, for me the best explanation comes from A. Damasio.

Best wishes

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what I was generally trying to ask was if there are any studies or evidence out there to support the idea that it requires more than just the phenomena of electric impulses traveling down the axons of neurons and chemicals crossing the synaptic gaps in order to explain the activity of the brain.

 

According to the liturature this would be basically what appears to be happening between individual neurons, but tells us little about how information processing actually takes place or what coding scheme(s) the brain uses to represent, store and manipulate information. To answer a previous question, this could sum up what is stumping the scientific community at this very moment.

 

Ok, so what could this coding scheme be ? Is it the so called rate code ? is it a timing code ? is it binary ? some other base ? is it even remotely digital at all ?

 

Reading about how a action potential ( spike) is believed to occur, i.e. when the dendrito-synaptic inputs to a neuron is sufficient enough to overcome some membrane threshold, a stereo-typical spike is propogated down its output axon to other neurons. This does appear to be somewhat digital but there is evidense that the timing between individual spikes (called the inter-spike interval or ISI) is significant as an analog type coding scheme.

 

If time is indeed a factor this would rule out binary in the digital sense of the word. As an analogy;recently ive bin reading about a proposed idea called rank order coding in which the firing order of an "array" of neurons can encode an enormously large input set. We are familiar with the on-off, 1's and O's binary nature of conventional computers in which information is represented by combinations of these but time has no meaning.

 

Heres a simple illustration comparing the representation capabilities of a rank order coding scheme and binary gates.

 

# of neurons: possible combinations: vs # of gates: possible combinations:

------------------------------------ --------------------------------

2----------- 2 __________________________2------------- 4

3----------- 6___________________________3------------- 8

4----------- 24__________________________4------------- 16

5----------- 120_________________________5------------- 32

6----------- 720_________________________6------------- 64

7----------- 5040________________________7------------- 128

8----------- 40,320______________________8------------- 256

9-----------362,880______________________9--------------512

10----------3,628,800____________________10-------------1024

 

Obviously as can be seen, has the number of neurons increase the number of possible non-repeating combinations quickly increase compared to their binary counterpart.

This just illustates that there are possibly other more powerful coding schemes foreign to conventional digital computing.

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I agree that using conventianal `puters won`t do this easily if at all.

 

we worked from the ground up, gate networks simulating basic functions performed by a group of cells, the results were quite astonishing in actualy terms, the problem arose from "making" these things actualy perform anything usefull (we Failed).

to get anything usefull we had to Emulate KNOWN behaviour, that worked great too! but was function limited and predictable (obviously).

 

it`ll take a REAL re-think of design to make something even barely passable I recon.

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My first post on these forums, since I've done some thinking around this topic before, and was interested. I have a small background in computer topics, none in medical, but I HAVE spent some time contemplating my own thought processes.

 

I wanted to start with better defining the diferences between computers and natural neural networks. Why were computers developed in the first place? To process large amounts of numerical calculations. More to topic, to perform a function that the human brain found boring and difficult, and to do it faster and more accurately than the human brain ever could. Why were "brains" developed? Dunno, but my best guess is, to recognize patterns in the flood of information comming from the newly evolved "eyes" of primitive organisms. This is something our current computers are barely beginning to be able to do.

 

Of course, both systems have evolved considerably since their beginnings. Still, this was lead by their initial purposes, and evolution went in completely different ways. "Brains", needing to process hugh amounts of data quickly, but without the initial need for much accuracy, evolved a network of individule processors all working simultaneously. Computers, needing to process set amounts of data accurately in as much time as it takes, and requiring a human engineer capable of understanding at once it's entire workings, evolved a single, rule based processor and other specialized components with simple, well defined connections.

 

We understand computers because they've been engineered to be easily managed by humans with limited intelligence. We don't yet understant the brain because nature has no need to evolve systems that require management (by anything less than supreme intellegence), being mostly self-regulating.

 

Does this mean that we can't understand the brain? Not at all. In fact, I believe (to directly answer your opening post) that we DO have enough information to understand the brain. We understand it the same way we do the weather. It'd be an exact science if it weren't for the fact that every breath you take influences how much rain we'll get 10 years from now! In other words, it's a relatively simple system that happens to depend on more variables than humanity is capable of collecting or processing in any reasonable amount of time.

 

As for developing a "brain"-based AI on computers, it would have to be done either a) completely emulate a neural network, or b) discover the "thought" function and engineer a software program to make use of it. a) takes only time to accomplish. It could be done right now if someone would take the time to find a simple brain, disect it, and reconstruct it in a digital form within a software package that, again, only takes time to accomplish. I believe that this would take too long and the results would be almost as difficult to study as the initial brain itself.

 

b) is far more interesting. How do you think? What does it take to develop a thought? I talk to myself in my head, in english, mentally pronouncing every word I type to you. Would this be a needed function in a created intellect? Sight, sound, motion, can they all be eliminated from the initial creation? How much of intellect is "pure thought" and how much is required for the human life we lead?

 

 

 

Wow not much opinion in here except my opinion about what the facts are. I'll leave that for later as this is getting long. Side feedback about my length and writing style would be appreciated. I hope I helped open some new avenues of discussion for you all!

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I wanted to start with better defining the diferences between computers and natural neural networks. Why were computers developed in the first place? To process large amounts of numerical calculations. More to topic' date=' to perform a function that the human brain found boring and difficult, and to do it faster and more accurately than the human brain ever could. Why were "brains" developed? Dunno, but my best guess is, to recognize patterns in the flood of information comming from the newly evolved "eyes" of primitive organisms. This is something our current computers are barely beginning to be able to do.

 

Of course, both systems have evolved considerably since their beginnings. Still, this was lead by their initial purposes, and evolution went in completely different ways. "Brains", needing to process huge amounts of data quickly, but without the initial need for much accuracy, evolved a network of individule processors all working simultaneously. Computers, needing to process set amounts of data accurately in as much time as it takes, and requiring a human engineer capable of understanding at once it's entire workings, evolved a single, rule based processor and other specialized components with simple, well defined connections.[/quote']

Very interesting comments. I fully agree. This remider me a paper I read yesterday. It is called "Memory Process and the Function of Sleep" from Journal of Theoretics, Vol6-6. I think that the temporary memory and sleep process should also be considered when design a future AI.

 

Here is the link about that article

http://www.journaloftheoretics.com/second-index.htm

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