Mouse Brain Simulated Via Computer 268
Mordok-DestroyerOfWo writes "Researchers from the IBM Almaden research lab and the University of Nevada have created a simulation of half a mouse brain on the BlueGene L supercomputer. 'Half a real mouse brain is thought to have about eight million neurons each one of which can have up to 8,000 synapses, or connections, with other nerve fibres. Modelling such a system, the trio wrote, puts "tremendous constraints on computation, communication and memory capacity of any computing platform."' Although there's more to creating a mind than setting up the infrastructure, does this mean that we may see a system for human mental storage within our lifetimes?"
Human Brain Simulation in our life time? (Score:1, Insightful)
Do we even want to, wouldn't that take away some of the mystery behind humans. Afterall if we can figure ourselves out then doesn't that mean that we aren't really all that complex?
wouldn't that also give us perfect explanations of people's actions making situations predictable violating free will?
afterall if society is ultimately chaotic in terms of our understanding, then wouldn't this be the ultimate control?
Does it run ...? (Score:3, Insightful)
Re:Human Brain Simulation in our life time? (Score:2, Insightful)
Re:Human Brain Simulation in our life time? (Score:4, Insightful)
Do we even want to, wouldn't that take away some of the mystery behind humans. Afterall if we can figure ourselves out then doesn't that mean that we aren't really all that complex?
wouldn't that also give us perfect explanations of people's actions making situations predictable violating free will?
afterall if society is ultimately chaotic in terms of our understanding, then wouldn't this be the ultimate control?
Don't be afraid to know more. It's coming if you want it or not. It doesn't mean a thing about free will: did you ever believe that your free will belong to your "ghost" or something? You are the sum of your parts and the interaction between them. Nothing scary about this.
As for the "mental storage" - simulating a brain doesn't mean much about mental storage. Knowing and simulating an Intel chip in a program doesn't mean you can crack open an already produced Intel chip unit and hack few more cores in it.
Plus, we already make very good use of tools to expand our mental storage: starting with notes, diaries, databases, computer knowledge systems, customer relationship programs, photos albums etc. etc.
All these act as peripheral devices to our brain, and we should expect tighter integration between the brain and those (for example a wire projecting video directly in your cortex), but nothing that "expands" the brain structure at such a low level as is hinted in the summary.
very short article (Score:3, Insightful)
What did the author mean by that? If they are not simulating any of the actual neural structures in the mouse brain, does it mean they are just simulating a more or less random neural network with eight million neurons? I have seen reports of simulations of actual brain structures in more primitive animals years ago.
Until they can, as they say, "add structures seen in real mouse brains" there's nothing to see here, move along...
Why the BS conclusion? (Score:3, Insightful)
Re:Human Brain Simulation in our life time? (Score:3, Insightful)
You think that making something that can figure itself out is simple?
Re:Human Brain Simulation in our life time? (Score:3, Insightful)
We have a fairly good understanding of the way a rainbow is made, but I can still appreciate it's beauty. Same goes for a wide variety of phenomena.
We understand the physiological make-up of boobs, but they're still pretty interesting and appreciated by a large % of the population. Just because we understand something, doesn't make them less wonderful and amazing. Besides, most people in the near future wont bother/be able to learn about the exact way a mouse brain works, let alone a human one. So those people can still have that ignorant bliss you promote.
While it's a bit of a tangent, regarding your free will comment... Psychology does allow us to make probabilistic predictions about how populations of people will behave in a given situation. That seems to rob us of free will? But at the same time, some sort of regular predictable nature has to exist in order for us to make choices. If I can't use some sort of rudimentary psychology to predict how a girlfriend will react to my gift of a pair of tickets to the superbowl, versus tickets to the theater, then how can I be said to be choosing anything? I need to be able to predict how people will behave, or else I can't make informed choices with my own "free will"
Simulations are cheap. Validated ones are gold. (Score:3, Insightful)
I've seen far too many papers where people make a "simulator" for a system, without demonstrating that the simulator has any real connection to reality, and then make grandiose claims about the real system that they're simulating, based on simulation results.
Call me a cranky old computer scientist, but someone simulating a brain isn't particularly noteworthy. Showing that the simulator is accurate enough to shed light on the ways that brains work, or that the simulated mouse brain can achieve things that we have difficulty achieving with traditional computer software, and I'll be excited.
Re:Mouse simulation (Score:3, Insightful)
Re:Umm (Score:3, Insightful)
If you model it as a black box that sums up inputs and fires if you're over a threshold you can simulate a whole whack of them. If you model it in excruciating detail you might need a supercomputer for each one. If you believe Penrose that quantum mechanical effects are important in neurons then you can't even properly model one with a current supercomputer.
And then there are the connections. Different types of neurons have different numbers of connections. And the connections themselves are quite complex, if you want to get into the gory details.
So the 8000 might be a typo, but they might be doing a simulation of a very different type than Blue Brain.
Re:Human Brain Simulation in our life time? (Score:3, Insightful)
Would it bother you to wake up one day and realize you don't have free will?
Or perhaps the soul is nothing more than chemical reactions that only came about through random chance?
Truth be told, the brain exists in a semi-logical universe where rules are applied and must adhere to the laws of physics.
The question of having free will or a soul makes no difference to how the human mind works on a chemical level. It would work regardless of how we thought on the matter (maybe just different regions) but it would still function.
So if we find tomorrow exactly how the human brain functions on an atomic level or forget the whole matter entirely, it will change nothing of how it is made and how it actually works.
And we might as well try to figure it out, because leaving well enough alone would have left us in caves thinking that fire was a bad idea.
Re:No randomness? (Score:4, Insightful)
Re:IBM's Big Assumption: Newtonian Physics (Score:4, Insightful)
I think the biggest argument against this is that synapses do not work on the atomic level. They are made of atoms, but quantum states do not seem to overtly affect organic matter at cellular level.
Of course I could be wrong about this, but since decisions are usually the next best move [wikipedia.org] it could simply be a matter of weighting what the "intelligence" applies to his rules as next best move.
The problem with General Artificial Intelligence is that "the next best move" is often open ended and too many possible choices often give our current computation a run for its money unless its put into some form of predefined rules.
The reason humans do so well is because we have certain criteria encouraging us to do things (hunger, pain, altruism, fear, etc etc)
Hence, our general intelligence goals aren't that complex (usually... to feel good about oneself and one's life) and that our true intelligence is being able to recognize things that improve upon that given a set amount of rules we know.
Which makes us very deterministic.
Even rebelling against the crowd can often be very predictable in humans.
Re:IBM's Big Assumption: Newtonian Physics (Score:1, Insightful)
Re:No randomness? (Score:3, Insightful)
What makes you think this machine is not affected by cosmic rays?
Re:No randomness? (Score:3, Insightful)
How does it remove the possibility of predicting human behavior? Many macroscopic processes (e.g., motions of the celestial bodies) can be predicted very well, despite quantum uncertainty. You would have to argue that human behavior is determined at the quantum level, as Penrose does, not very convincingly, in my view.
You may also consider the fact that uncertainty does not just arise at the quantum level. for example, it is very difficult to predict weather, despite the fact that quantum effects probably have little role in it. It has to do with the fact, that certain systems are very sensitive to the initial conditions and our ability to measure is limited.
Re:No randomness? (Score:3, Insightful)
Given the difficulty of distinguishing between pseudo-random and truly random numbers, I don't think that would even be necessary. I would be very surprised if we made a brain simulator with a real entropy source, which was creative, and then replaced that with a pseudo-random number generator, and the creativity evaporated.
Re:Not a big assumption. (Score:2, Insightful)
I am forced to assume that it is important for his notion of identity, to have a free will that is capable at least of thinking whatever it is possible to think. He likely refines this formally as the ability to 'prove what is provable' - since if we *couldn't* prove certain things that are actually provable, then we clearly wouldn't have the ability to think whatever was thinkable, or possibly to think whatever we want preventing free will. Can't be certain which beef he has that drives his assumption - there are likely several more possible motivations, though Penrose claims at least not to be motivated by spirituality in this argument.
Any discussion of AI and computability must acknowledge the wonderful Godel Escher and Bach: An eternal Golden Braid by Douglas Hofstadter. ISBN-10: 0465026567 ISBN-13: 978-0465026562
Hofstadter is less rigorous, and is mostly just trying to show how neat these areas of math are - and how they relate to consciousness, intelligence, identity, knowledge etc... If you haven't read it already I think you'd really, really, enjoy it. He also assumes things more along the lines of how I think - so I can claim his arguments are more 'sound' than Penrose. Penrose does a commendable job of logically carrying his position, but his assumptions are crazy - I accuse him of an 'unsound' analysis.
Thanks for taking the time to read my post - there's no way I'm getting modded up on something that long.
I had mod points too (or at least I did earlier today), could have just hit him with the trusty 'overrated'.
Sigh.
Re:IBM's Big Assumption: Newtonian Physics (Score:2, Insightful)
Nothing exciting for now (Score:2, Insightful)
Re:IBM's Big Assumption: Newtonian Physics (Score:2, Insightful)
A massively parallel cortical simulator with (a) phenomenological spiking neuron models; (b) spike-timing dependent plasticity; and (c) axonal delays.
(see the actual research description here: http://www.modha.org/papers/rj10404.pdf [modha.org])
Secondly, it is not necessary for a cortex to have left-right brain functionality in order for it to function. This has been demonstrated in live humans.
And third, the speed, relative to real-time, is irrelevant. It is comparatively a minor task to increase the speed of the simulation by increasing parallelization.
Now, to respond to your somewhat antiquated understanding of the current state of AI:
In addition, everything I have seen in tech press on AI since the rules based AI reasoning failures of the 80's has been neural net simulations looking for patterns, such as the mentioned synchronized firings.
Sounds like you're a couple of years behind (as would be expected on slashdot, which primarily focuses on IT and science, and not neuroscience). Let me bring you up to date a little. Spiking neural networks began to grow in popularity in the mid to late 90's. They are much more biologically realistic then most of the models used in the 80's and early 90's. Also, a lot of research has been done which points to the significance of chaotic attractors, which arising from phase-locked loops in the neuronal structure. The fact that synchronous firing is observed tends to imply similar dynamics are occurring.
Furthermore, you make the assumption that biological brains are somehow superior to simulated brains, just because they are more chemically complex. That assumption has absolutely no research to back it up. For all we know at this point all of that chemical complexity may be superfluous for evolutionary benefits (and this is direction which evidence suggests).
Aren't the neural net rules just tweaked until they get interesting behavior like that?
That's the way it used to be done, so I can understand your confusion here. I think the problem lies in the fact that people are very interested in neuroscience these days. But a remarkable amount of progress has been made. Phenomenological spiking neural networks are quite a bit biologically accurate than the "neural nets" of the 80's and early 90's.
Don't tell me you think they actually have any idea how they would simulate brain functionality.
The cortex is arranged into mircocolumns of neurons, which have a very definite structure repeating structure over the surface of the cortex. Jeff Hawkins has recently presented a very convincing argument for structure of the mind, in relation to the structure of the cortex.
Training neural nets is just something easy to do. Beats actually writing complex code, doesn't it?
If you're implying that the simulation was not complex, consider that each neuron had its own dedicated computer. And, once again, this is much more complicated than a simple neural network.
I've never seen any explanation for how either short term or long term memory works, much less reasoning or any other functionality. And that at least is something that would seem able to be modeled and explained. How does man know anything about something they have never encountered before, for example, to acquire language as a child?
Explanations for both short and long term memory have been out there for quite some time. But neuroscience is not a popular topic of discussion, partly because it can get quite complex. People would much rather be talking about the step in the evolution of Intel processors, or life
Re:Unproven assumptions (Score:3, Insightful)