Building a Functional Model of the Human Brain

In summary, building a functional model of the human brain involves creating a detailed representation of the brain's structure and its functions. This is achieved through the use of advanced technology, such as brain imaging techniques and computer simulations. The goal of this model is to better understand how the brain works and to potentially develop treatments for neurological disorders. It requires collaboration between various fields of study, including neuroscience, psychology, and computer science. Despite the complexity of the brain, significant progress has been made in creating functional models that can accurately simulate its behavior and provide valuable insights into its functioning.
  • #1
Guybrush Threepwood
Is it possible for us to make a functional model of the human brain?
I'm not interested in the phylosophical implications, but more in the resources, techonolgies we can use (that's why I posted here... )
Engineering news on
  • #2
Why not start small?

How about a honeybee? Or a simple worm?

If those could be modeled, wouldn't the human brain just be a matter of scaling up?
  • #3
hi Nereid :smile:

I don't think insects have a central nervous system (I could be wrong though...).
What animal has the simplest brain; is there a biologist here that can answer that?
just found this link here: for anybody interested
  • #4
Why not start small?

How about a honeybee? Or a simple worm?

If those could be modeled, wouldn't the human brain just be a matter of scaling up?

Not quite.

Mammalian brains are different from reptiles and birds, which are different from fish which are different from invertabrates.

I think a human brain can be modeled. It is a physical entity after all. However, not all of its functionality is understood, and what is understood is tremendously complex.

  • #5
Njorl said: Mammalian brains are different from reptiles and birds, which are different from fish which are different from invertabrates.
What are the key differences?

What is the simplest mammal, from the brain perspective?
  • #6
I'm no expert, and would screw up the details I'm sure. Try this link:

I'm not qualified to judge the info on the site. Hopefully, one of our biology experts will critique the ideas presented at this site, and maybe come up with a better one if they find it lacking.

  • #7
What if you wrote a physics engine in a computer language and programmed in every atom of a human brain? :)
  • #8
well I was hoping of something that could be done in my lifetime...
  • #9
Unless you're extremely old, it could! All we need is a very fast computer with a ton of memory, and we can program a program that sets up every atom, after detecting it in a machine with a dead human brain (or some such thing) in it.

Something like that, anyway. It's not as impossible as it sounds...
  • #10
(pay no attention to the man behind the curtain!) Guybrush,

It is most definitely not possible. There is, at this time, a worldwide effort underway to simply map the human brain. In other words they still haven't sorted out what functions different parts of the brain perform.

If you take vision, for example, they know this is primarily processed in the occipital lobes, but important aspects of vision, such as the perception of up and down motion, are processed in the parietal lobes. Other aspects are processed in the temporo-parietal area. What is one phenomenon to us: vision, is actually the perception of many different aspects of vision fused into the one we're conscious of.

No one even thinks to consider we need a system to process the perception of up and down motion till it gets damaged in someone.
We don't know how many things the brain does that we haven't even realized needed doing.

The functions performed by the brain are, therefore, probably still not all discovered, and it is taking imput from neurologists all over the world, to simply create this comprehensive map.

That being the case it is clear they don't know remotely enough to create a functioning model of the circuitry.

If you'll settle for a good plastic brain model go here:

Brain Mart's Brain Models

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  • #11
Ah yes, I raised this in the chat, didn't I?

I think the whole issue is that of acceptable approximation. It is not required that we model every atom etc, but rather just understand what each individual cell or group of cells does and translate this into an entire system. If there are parts of the brain we don't know about... then modelling them would be outside the scope of our model's criterias.

In using GR as a model of the universe, we do not claim that GR covers all things we do not even know. Rather, we judge the acceptability of the model on what we already know...
  • #12
IMO the great challenge is to make a system that can learn. No system made by man can do that yet. It may not be obvious but computers work on algorithms. Every algorithm in use today was made from scratch by men. There isn't a algorithm that was made by a computer. I think that if we want to make a model of the brain sooner or later we must design a system that can learn...

the human genome project lasted 13 years and al they did was mainly:
- identify all the approximately 30,000 genes in human DNA,
- determine the sequences of the 3 billion chemical base pairs that make up human DNA.
Tenths of institutes have joined resources to make this happen. ( )
And you want ot map every atom in the brain and believe it can be done in a lifetime? You're too optimistical :smile:

If you'll settle for a good plastic brain model go here:

that's a start as good as any other...
  • #13
Modelling the brain in isolation is not really a model of the brain as it works in humans. There is significant bio-feedback from chemicals produced in other parts of the body. For example, eyes detect tiger, tiger is referenced in brain, brain tells adrenal glands to produce adrenaline, adrenaline affects neurotransmission, brain works differently.

  • #14
Originally posted by FZ+ If there are parts of the brain we don't know about... then modelling them would be outside the scope of our model's criterias.
Guybrush wants a functioning model, a very tall order, and one which means a physical apparatus that does something, as opposed to a conceptual model, such as "Bohr's model of the atom".

If we were to make a functioning apparatus based on what we do know about the brain, leaving out the parts we don't know about, it really wouldn't be a model of a human brain at all. With luck it might amount to a functioning model of a very damaged human brain.

Njorl's post points out the that the functioning of the brain as we know it extends out and into the body. I hadn't thought of that. Guy's model would actually require
a functioning model of the body to be built as well, to support it.
  • #15
u can only create a probabilistic model using AI algorithms like genetic algo and neural networks, which themselves are derived from biological principles on which our brain and nervous system works. so, the fuzziness in our final model will definitely limit the efficiency, and we will end up with a brain that does not, or rather, can not ,THINK ...
  • #16
model atoms of brain?

Modelling the atoms may be too ambitious, but modelling the individual functions could be also. The power contained in the brain comes from the fact that all of these functions interact synergistically, so that the whole is more than the sum of the parts, and we may never be able to determine all of the unseen interactions that take place when several functions combine to produce a thought. Rather, let's consider the middle road. Just model the connections between neurons, and the conditions that cause each synapse to fire (kind of like the game of life). I picture an AI containing groups of synapses of various characteristics - in this group, two inputs (on average) cause a firing while in that group it may be that 5 inputs are required. As stated, chemical processes can change the characteristics of the neurons, but such chemical processes would be fairly easy to model as a possible output of certain groups having high activity at the same time, and this causing a global change throughout the AI, with various affects to each group. In summary, I believe the synergistic characteristics of the brain come mainly from the circular feedback of various neuron groups each having DIFFERENT firing rules on average. Also important would be if one group, for example, comes between a pair of groups in the normal communication scheme, i.e. the corpus colosum connects the hemispheres, but modifies the info going between them.
Just some random thoughts on the subject.
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  • #18

I'm picturing the brain as being multiple neural networks, having feedback between many pairs of such networks. In both the brain and in all other complex biological, chemical, and physical systems that exhibit synergistic effects and emergent phenomena, feedback is the key. Without feedback, things go in a linear fashion. With feedback, surprises can result! Picture a corporation running with information and direction going only from the top down - disaster! The management will be out of touch with what is going on below them, and even in parallel branches of the corporation. Those who implement policies will have no recourse when conditions change and the directions they were given no longer fit the situation they now find themselves in. Parallel branches may act against the goals of each other - a schizophrenic corporation. Now add upward and sideways feedback and voila, we now have an intelligently run corporation. It's the same way with the brain. In simplistic terms, at the very least we have feedback between memories, reasoning, input, planning, output, emotions (intuitions, hunches), feelings, imaginings, etc. How many different facets of thought are there - I'd like people to supply their own answers to this here, if they think it would help the thread. Now, how many of these facets are stand-alones, don't give or receive feedback from other facets during normal thinking?
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  • #19

From what I understand of the brain you are on the right track.
All the different parts of the brain are constantly in communication with other parts, back and forth.

I would only suggest that for the "multiple neural networks" of the first sentence of your last post you substitute "multitudinous neural networks." Earlier today I was looking through a book on the brain and became aware of yet more things the brain does that I hadn't ever considered needing doing.

You have also to take into account the all important, constant stream of new information coming in through the sences. The more I consider the brain/body/environment interaction the less I think it is possible to construct even the crudest of functioning models.
  • #20
Originally posted by Guybrush Threepwood
IMO the great challenge is to make a system that can learn. No system made by man can do that yet.
What do you mean by "learn?" In the simplest, zeroth order sense, is not any response to stimulus learned?
  • #21
Originally posted by turin
What do you mean by "learn?" In the simplest, zeroth order sense, is not any response to stimulus learned?

Yes what exactly is the defenition of learn? It is not just simply retaining information. ok looked it up. To gain knowledge, comprehension, or mastery of through experience or study.
To fix in the mind or memory; memorize: learned the speech in a few hours.

To acquire experience of or an ability or a skill in: learn tolerance; learned how to whistle.
To become aware: learned that it was best not to argue.
To become informed of; find out. See Synonyms at discover.
Nonstandard. To cause to acquire knowledge; teach.
Obsolete. To give information to.

So some of this stuff a computer can do, like memory and processing. but to cause a computer to become aware or to have a drive to discover its environment on its own, hmmmmmmmm. I am contemplating Is this different than processing, hmmmmmmmm let's see, I think in order to make a computer learn it would need to become aware of itself. hmmmmmmm I am computer therefor I am. We designed the algorithms for the computer to use so what do we use is the question? if not complex algorithms than what? We want to learn, why? If a computer did not know it exsisted than why would it want to learn? It wouldn't. I don't care how much memory or power you give it, it will still be a machine that can just simply crunch information and spit it back out at you. If the computer senses its exsistance though watch out. Even at a low computational level it will learn. After that sight, feel, eye movement becomes more than a sensor, it becomes its connection to its environment, It will want to move a sight sensor and will start to figure out how or if it can, in order to see something that seems interesting. Now you've got something!
  • #22
If you know how it's happening, it's not learning?


There are plenty of examples from the insect world where learning - in the sense you describe above - doesn't happen, yet I'm sure you'd agree that the critters do each have a brain.

In the world of complex computer systems, a good case could be made that some systems do 'learn', if you simply judge their behaviour in the same way as some behaviour in simple animals is called 'learning' (by the relevant biologists).

Perhaps you don't count what the autopilot of a modern fighter plane, or the management system of a telephone network, can do as being able to 'learn' because you know (in principle) how the code was built?

Sure, a wasp can't learn how to whistle or learn not to argue and neither can an autopilot. However, is there a fundamental difference between a wasp and, say, a chimp? Or is it just a matter of time before a meta-autopilot could behave like a chimp?
  • #23
Originally posted by Guybrush Threepwood
Is it possible for us to make a functional model of the human brain?
I'm not interested in the phylosophical implications, but more in the resources, techonolgies we can use (that's why I posted here... )
Engineering answer, imo, not in few hundred years.

There is still some uncertainty whether we could at all. Reason is complexity. There are limits to our human comprehension. In fact they are even measurable. For ex, it has been suggested to "just write a program", but its obvious difficulty of writing such program isn't even imagined. In past years some interesting revelations have came up. For eg, in 70ies they built a computer with 65536 cpus. It was disaster, not because it was slow (it was fastest supercomputer at a time), but because programmers of a time were simply unable to program it to utilise its potential. Occured that humans simply are unable to think parallel enough. Thats an important bummer. Technology was sitting there, and we couldn't make use of it.

Today, its said that roughly, human being is able to cooperatively comprehend around 1 million lines of code. Beyond that, number of errors introduced outnumbers fixes made. For every 1 fix you add >1 error. Another important bummer. It seems to set the limits as to how complex a program we can create. MS windows is around 1M lines of code. Not very intelligent. Fortunately, the limit is not hard one, we evolve on that front.

Then, there is interesting question whether a machine can at all comprehend its own design and functioning? Answer isn't trivial at all, because to comprehend its own functioning, it should be able to comprehend more than what it is designed for, in addition to that its designed for. We can dismantle brain into functional units and perhaps even understand how they work, but to put together coherent functional whole, we'd need to really make a monumental effort. We are far from even trying. We'll need to comprehend it as a whole. Would we have enough brain capacity for that?

As to techonolgies, quantum computing seems to come close enough for the job. When it matures, and we learn to program it, we'll be able to build equivalent to brain. Then, we'll have to solve our ability to program something as complex as that. And I believe that will be the main obstacle. I like to think its possible, but it would take leap in structured cooperative programming approaches. And that's unfortunately very slow process, could take generations of geniuses to get us ready.
It seems more probable that we'll create learning and evolutioning computers that would be better suited for such difficult tasks, and that they would then succeed in creating thinking machine. Thats beginning of a new species, homo roboticus
  • #24
wimms wrote: Today, its said that roughly, human being is able to cooperatively comprehend around 1 million lines of code. Beyond that, number of errors introduced outnumbers fixes made. For every 1 fix you add >1 error. Another important bummer. It seems to set the limits as to how complex a program we can create. MS windows is around 1M lines of code. Not very intelligent. Fortunately, the limit is not hard one, we evolve on that front.
Do you have a source with more data on this bug/program size conundrum?

IIRC, there were >1m lines-of-code programs running quite well long before Windows came along. Also, to what extent have the 'must-not-have-bugs' apps run into a size problem of the kind you describe? I'm thinking of things like the latest Airbus and Boeing autopilot software, nuclear reactor control systems, medical lasers, and so on.
  • #25
No, I don't have a source handy. It was few years back when I saw it.

Before windows, LOC were measured in tens of thousands.
There is always a difficulty to define exactly what is meant by lines of code and program. NT4.0 was said to have over 9M LOC, w2000 over 40M. But that's not a single program. There is some essential part of it that makes up the "core" of it, that's much smaller. Its no point in including Notepad as a part of the core, as its pretty irrelevant to it.

There is no need to look at whole system as one program. But there are interactions of a system that require good coordination of any changes in it, because parts depend on each other. Its those dependancies that grow into huge mess. By program is usually meant such conglomerate of tight interdependancies. By line of code is usually meant minimal conceptual unit of computer action that changes state of it. Not comments, not empty lines, not syntactic sugar.

1Million lines of code is impossible for single person to even read through, let alone understand, and forget about remembering beginning while reaching the end. And there are no two persons that think the same. Many people working on same code are bound to misunderstandings, hurting each others work while "fixing" bugs of other, etc. More complex programs have more and deeper dependancies on its own internal state, so there is a trend - the more complex the program becomes, the more difficult it is to change anything in it without braking loads in other areas, or even find where the error is.

There are a lot of ways to manage a teamwork, and main leap is expected exactly there. OO programming is one example that made things possible unthinkable in the past. New ideas are coming that would extend the raw LOC limit, but there remains something essential to it. Its not that we should know exact value of the limit, but just that there is one, and its not very huge nor complex.

As to autopilot, I don't think its very complex thing. Its difficult to invent and design, but the program code itself isn't very huge.
I recall, that NASA had rules that accounted that comprehension matter. IIRC, deep space probes and other space computers had under 60K lines of code, had to be developed by single person, had to be developed concurrently by 5-10 persons independantly and unrelatedly, then exchanged code and had to understand and find out all errors other programmers made. Repeated over few times. Then best design picked. There is no one out there to press ctrl-al-del, y'know..

I believe modern autopilots of planes also have 2-3 systems built by different coders, all computing same task, and then comparing with each other in realtime - trying to detect computing errors, too much is at stake. But given that airbus computers runs on windows, I don't know.. must be that it doesn't matter.
  • #26
Guybrush Threepwood wrote: Is it possible for us to make a functional model of the human brain?
This was the original question.

So, a few WAGs:

1) in terms of hardware, the human brain has ~100 billion neurons, and ~150 trillion synapses. At an OOM level - maybe 2 or 3 OOMs - this corresponds to ~100G of RAM, and ~150T of ROM ('hard drive') in a computer.
Well, I reckon we could easily construct a computer with that much hardware today.

2) for cycle time (or clock speed), the comparison isn't exact, but if the brain were a synchronous machine (it isn't), its clock would run at ~10Hz, which is ~9 orders of magnitude *slower* than today's computers. Of course, a more realistic comparison, involving relevant comparable domains for example, would reduce the gap, but not make it go away.
Again, human brains can be matched or bettered in this respect.

3) turning to resilience and robustness. This is certainly an area where the brain's capabilities are poorly understood. At a very high level ... brains suffer gradual decline in functional capability and performance, and can easily work continuously for 100 years. A significant percentage (1-5%?) do suffer systematic failures which can be compensated for to some extent. In contrast, today's computers are ~1 to 3 orders of magnitude less resilient. Methods and approaches to improve this are known (e.g. how the key Shuttle computers are designed).
However, it's likely to be a decade or two before we come close to matching the human brain's capability here.

4) architecture. At one level we know how the brain is wired; that's where the name 'neural network' came from. In other respects - as zoobyshoe pointed out - we are still likely very ignorant of all that the brain does, let alone how it's wired to enable and perform these activities. We can already build neural networks in silicon, or similate them with code; we can also handle the inherent parallelism, at least in principle.
For what we know today, an artificial brain could be built today, architectually. Say two decades before we discover ~80% of all the key brain architectures, and another decade to emulate these.

5) apps. Some of the brain's apps we know reasonably well (e.g. vision), some we're still likely decades away from even outlining (e.g. personality, social interactions), and some are in-between (e.g. language).
WAG: we might get to an '80%' brain in a couple of decades; this is perhaps similar to zooby's 'very damaged human brain'.

6) integration. IMHO, this is the area we know least about, and don't even know how important it is, in terms of the objective as Guybrush set.
Since we don't know what we don't know, this could take a mere five years to clarify, or over 100.

My conclusion: "Is it possible for us to make a functional model of the human brain?" Not today, but maybe in a limited sense by 2020-2030.
  • #27
I think that we will be able to model the brain as soon as we have perfected nanoTech. My reasoning behind this is that we would be able to inject nanites into the brain. From there that could each attach to a neuron and map its inputs and outputs. And as the brain is working, it would be able to determine how it responds to stimuli both artificially and from other neurons. Depending on the technique used, we could then both extract the nanites and have them reassemble themselves 3-dimentionally. Or, (taking a Borg like approach) they could assemble some sort of transmitter. If they made the transmitter, it might be possible to actually gather real time data from the brain.

Furthermore, I do not really care too much for true computer AI. I think it would be very nice to learn enough about the brain to build mind machine interfaces, or some sort of other augmentation.

I heard from someone that one on the applications of nanoTech was brain augmentation. The idea is to make nanites with very small transmitters and receivers. These would allow the brain to make connections between neurons at the speed of light, as well as many more connections. Currently the brain can only send a signal at about 200mi/hr and even then, the neuron must be reset. I do not know of any projections of how much better off the brain could be with these enhancements, but I believe that if everyone had them there would not be anyone without a 200 IQ (that is a bit optimistic, but oh well).

Going back to talking about windows, I think I heard that win XP has 3 billion lines of "C" code if you include all of the utilities that go with it. However, the important thing to note is what programming language those lines of code are. For example,... 3 lines of visual basic COULD translate to 9 lines of Visual C. 9 lines of Visual C COULD translate to something like 54+ lines of Assembly code (also called machine code).

In addition, some one stated that the operational speed of the brain is something like 10 Hz. Well I am not totally disagreeing, but you have to multiply that by the brain cells in use, as well as, all of the other brain waves. That is, I've done research into binaural waves and using sound waves you can stimulate your brain to change its frequency. Therefore, more accurately, the brain is like a computer where the processor speed readily fluxuates. You also have to take into account the individual processing power of a neuron. I heard some statistic placing a single neuron in the optic nerve as having the processing power greater than a Cray super computer. I heard another statistic that the brain, as a total, has an equivalent processing power of 5exo-hertz. In addition, if you think about it, it kind of makes sense. Right now computers find it very hard to recognize objects 3-dimentionally. An example of this would be asking a computer to use images from security cameras to identify a telephone. Now if it is a phone it is seen before it should be able to spot it right away, however, what about different models of phones?

.. Any way, I am just rambling now...
  • #28
Unless humans are artificial, I don't think you can ever model a "human" brain. The closest to come to it is to recreate a model of the whole universe to authentically recreate a human brain.
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  • #29
INX990, What source did you use for your facts on the brain's processing speed? In researching my next SF novel, I came across a statement that the brain thinks at 1.25 times the speed of light. As the entire premiss of the book hinges on that fact, I need to be absolutely sure of it's truth. Do computers think faster than us? Obviously I have a lot more research to do. Any help would be greatly appreciated.
  • #30
1.25 the speed of light? doesn't that violate the laws of physics?
  • #31
yeah, that should. I am not completely sure wot he meant by it thinks at that speed. If your referring to pure thought you cannot realisticaly put a measurment of speed on it. However, measuring the chemical signaling of the brain, it is much slower. um, I am going to brush up on my neuroBiology ang get back to youall on the exact processes required to make this happen.
  • #32
speed of light

From my master (research) notebook: "Scientists have found ways to break the speed limit. In one experiment, published in the May 22 issue of Physical Review Letters, scientists at the Italian National Research Council of Florence shone light beams at a curved mirror. The mirror then shot the beams back at the instrument that measured the ray's speed. The beam coming from the center of the mirror was measured at 5% to 7% faster than light speed. The authors said this effect only works over short distances, such as the one meter used the the Italian researchers."
  • #33
I seriously doubt it... could you provide a link?
  • #35
neuron mechanics

The diagram (attachment) is self-explanatory.

Nevertheless, essentially the nerve impulse is a sudden rush of sodium ions. The rush then triggers the next few proteins to let in more ions. This process continues in a relay fashion until the pulse reaches the presynaptic membrane. As soon as the pulse passes an indicated area of proteins, they will immediately stop allowing sodium into the pathway. Then active transport kicks in via the sodium potassium pump and resets the nerve. This entire process occurs at about 100m/sec. (much slower than the speed of light).
For those of you that are curious about claims that nerves are electric well, here is the explination. The axon has positive ions on the outside and negative ions on the inside. This creates an electric potential. So then, why doesn’t the pulse travel at the speed of electricity? Well, the protein gates that keep the ions out have different ways of being activated, chemically, and electrically. The main pulse is mostly controlled by electrically activated proteins. However, they have a high "Tolerance.” That is, while they can "feel" the pulse coming via the weakened electric current, they do not activate until the pulse is near to them. Ultimately, the signal sent across the synaptic cleft is chemical. Thus, it would seem to be inefficient to keep changing the signal medium. However, there are some organisms that do have nerve that rely solely on electricity.
This electric method is fast but it does not integrate information well. Electric transmission across synapsises is very fast and can proceed in either direction. However, they are less common in vertebrates and other organisms that have complex nervous systems. First, electrical continuity between neurons does not allow temporal summation of synaptic inputs (one way that signals are integrated). Second, an effective electrical synapsis requires a larger area of contact between the cells. This makes it impossible to have thousands of connections coming from one cell (witch is common in vertebrates). Third, electrical synapses cannot be inhibitory (not allowing for complex brain chemistry); and fourth, there is little plasity (modifiability) of connections (much harder to learn). Essentially, all there good for if speed, but not so good for complexity.

The statistic I got for brain speed came from a friend of mine, ill try to contact him about his source whenever he is back from the holidays.

The question "do computer think faster than us?"
Well, yes and no. They are capable of transferring information faster than we are, and are faster at processing in a linear fashion. However, they are much slower when it comes to nonlinear systems and processing also known as thought. Simply computers "think" what we program them to. So yes, computers process linear equations faster than we process, but could never understand their environment (at least with current tech).

As far as either building or emulating a brain, I think we should start small. We should try to create something called a ganglion. A Ganglion is simply a small cluster of nerve cells that carry out a specific task. These tasks could be something simple like detecting danger then relaying the signal, of cause the creature to disengage itself from prey. This simple basis of neuro-networking would not allow the subsequent computers to gain emotions or anything and would be reacting on instinct. Thus it wouldn’t decide one day that it no longer likes the scientists and lock them out side the space craft... “HAL. Let me in”...

Another interesting thing to put to the test would be what the DNA says about creating a brain. I mean, it eventually has to do it some way or the other.


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