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Topic: Do you know of sucessful insect brain simulation?

DanishMike
posted 5/2/2010  13:02Send e-mail to userReply with quote
I'm wondering if anyone has ever succeded in making a neuron-by-neuron computer model of a very simple brain like that of an insect with only a few tens of thousands neurons?

With the term "succeded" I mean having *really* duplicated an insect brain and made it react exactly like a real one, thus beeing able to control an insect-like robot or computer-simulated insect moving about in a similarly computer generated physical environment.

In my opinion this would be the right - or at least a very obvious - way to start when trying to reverse engineer real biological brains. I'm not as such interested in research trying to *understand* how they work, but simply in experiments that "mindlessly" copies them in software form and succedes in making them react just like their biological counterparts.

Strangely, I can't seem to find any information about this and hope you migth be able to drop a link to some webzine or portal dealing with this subject.

Cheers,
Mike


Last edited by DanishMike @ 5/2/2010 1:08:00 PM

lordjakian
posted 5/3/2010  07:40Send e-mail to userReply with quote
http://www.youtube.com/watch?v=RLCT3wU4fek

Blue Gene as a computer is pretty old news, and doesn't have to do with insects so much as rats, but it is the closest thing I've heard of in response with your first question. The video says ten thousand neurons.

Last edited by lordjakian @ 5/3/2010 7:43:00 AM

hunt
posted 5/3/2010  19:53Reply with quote
I think it's interesting that so many recent large collaborations are aimed at this goal: reproducing brains. I suppose because it seems a more tractable problem than "What is intelligence? Can we stick it in this computer?" he he he

I know there is a project aimed at simulating a cat brain: http://nextbigfuture.com/2009/11/ibm-has-achieved-cat-scale-brain.html

Then again, where there are high stakes, there is controversy: http://gizmodo.com/5411328/rat-brain-simulator-calls-ibms-cat-brain-simulation-bogus


DanishMike
posted 5/3/2010  20:45Send e-mail to userReply with quote
@Lordjakian

This wasn't quite what I was looking for, but thanks anyway.

@Hunt

Well, since after roughly *seventy* years of experiments and research (Turing onwards) we still don't have a clue how to build genuinely intelligent and sentient machines, reverse engineering real-world brains is beginning to seem like a pretty good idea :-)

The problem seems to be that researchers try to simulate too big brains which returns dubious results. Why even start with a cat's brain when there's more than enough of a challenge in simulating that of an ant or a spider?

I assume that someone by now has done a neuron-by-neuron map of an insect brain, like for instance the banana fly which if I remember correctly has about 50.000 brain cells. Simulating a brain of that size should be doable on a modern supercomputer, right?

In my opinion doing that would be the first real step towards developing truly intelligent and sentient machines.

cheers,
Mike

Last edited by DanishMike @ 5/3/2010 8:48:00 PM

hunt
posted 5/4/2010  00:23Send e-mail to userReply with quote
"Well, since after roughly *seventy* years of experiments and research (Turing onwards) we still don't have a clue how to build genuinely intelligent and sentient machines, reverse engineering real-world brains is beginning to seem like a pretty good idea :-)"

You might be right. :)

"The problem seems to be that researchers try to simulate too big brains which returns dubious results. Why even start with a cat's brain when there's more than enough of a challenge in simulating that of an ant or a spider?"

I wonder though if the results would be equally dubious for an insect or spider. What would this brain do that would make me say "Aha! It *is* behaving like an ant." Neuron activity matching? When we invoke neural responses from animals, we usually begin by applying stimuli. How do I stimulate the visual cortex of the ant brain? How do I know I'm doing it in the same way as would happen in an actual ant?

I'm not saying these questions don't have definite answers. But I wonder at the degree to which scientists understand their animal model itself, let alone a simulated copy of it. Especially if they are audacious enough to try a mammal. There are so many question marks when it comes to the mammalian brain, that I don't think modeling will elucidate. Especially if the test for it being a *good* model is mimicry of something that is poorly understood.

It all seems rather circular.

"I assume that someone by now has done a neuron-by-neuron map of an insect brain, like for instance the banana fly which if I remember correctly has about 50.000 brain cells. Simulating a brain of that size should be doable on a modern supercomputer, right?"

Hmm, somehow banana fly doesn't have the same cachet when applying for funding, I imagine.


DanishMike
posted 5/4/2010  10:01Send e-mail to userReply with quote
Hi there Hunt,

"What would this brain do that would make me say "Aha! It *is* behaving like an ant." Neuron activity matching? When we invoke neural responses from animals, we usually begin by applying stimuli. How do I stimulate the visual cortex of the ant brain? How do I know I'm doing it in the same way as would happen in an actual ant?"

I'd say by simulating the *whole* ant and it's environment, not just the brain. Construct a computer simulated ant, complete with legs, feelers, and eyes, and place it in a computer simulated environment, where everything moves and interacts according to the laws of classical mechanics. Then you'd know if the simulation was succesful by letting a specialized biologist observe the ant - or preferrably ant colony.

"I'm not saying these questions don't have definite answers. But I wonder at the degree to which scientists understand their animal model itself, let alone a simulated copy of it. Especially if they are audacious enough to try a mammal. There are so many question marks when it comes to the mammalian brain, that I don't think modeling will elucidate. Especially if the test for it being a *good* model is mimicry of something that is poorly understood."

That's what so wonderful about computer simulations. You don't have to *understand* it in order to simulate it. You just need to be able to copy it. And even only qualitatively so, not quantitatively. There doesn't exist a single quantitatively exact simulation of - say - our galaxy, but still scientists are greatly helped in their attempt to understand its mechanisms through qualitative simuations, where large-scale phenomena emerge from simple physical laws. I'd say this probably applies for brains aswell.

"Hmm, somehow banana fly doesn't have the same cachet when applying for funding, I imagine."

Ok, this got me laughing out loud :-) If you want lots of funding for research, the topic *needs* to have soft fur and big eyes!

Cheers,
Mike

Last edited by DanishMike @ 5/4/2010 10:03:00 AM

hunt
posted 5/5/2010  03:05Reply with quote
"I'd say by simulating the *whole* ant and it's environment, not just the brain. Construct a computer simulated ant, complete with legs, feelers, and eyes, and place it in a computer simulated environment, where everything moves and interacts according to the laws of classical mechanics. Then you'd know if the simulation was succesful by letting a specialized biologist observe the ant - or preferrably ant colony."

That would be an interesting endeavor. I wonder though how long such a simulation would take--of even just one ant. You'd have to break it down into some finite element model, I'd imagine. And carefully determine the number of nodes needed to successfully simulate each part: even something as simple as a feeler can be made ceaselessly more complicated. (Surely, not every seta needs its own node. And need we model at the level of the chemical receptors, or will phenomenological rules that guide feeler nervous system reactions to certain chemical stimuli be sufficient?)

It would be rather ridiculous if a microsecond of ant time took a week of computational time. But then, what are we building these giant supercomputers for, if not to dedicate to modeling more and more complex systems? I'd certainly be interested in the outcome of such a model.

"That's what so wonderful about computer simulations. You don't have to *understand* it in order to simulate it. You just need to be able to copy it."

I guess my skepticism is related to what rubric is used to determine that one has, indeed, successfully "copied" a system. Especially when the original system is so imprecisely understood.

"There doesn't exist a single quantitatively exact simulation of - say - our galaxy, but still scientists are greatly helped in their attempt to understand its mechanisms through qualitative simuations, where large-scale phenomena emerge from simple physical laws."

True--it is precisely such simulations that lead astrophysicists to smack themselves over the head and say, "This doesn't match reality at all. Matter must be missing!" And thus dark matter was born.

But while in galactic simulations the mechanism that guides the time evolution of the system is well-understood (minus that pesky dark matter), it is not so clear which mechanisms of neurological activity are necessary in a brain model and which are not. Though, I suppose, picking your favorite parameters and giving things a go is a nice "experimental" way of answering that question: either it will work, or it won't! (Or worst of all, it won't even be wrong...)

Last edited by hunt @ 5/5/2010 3:08:00 AM

DanishMike
posted 5/10/2010  03:59Send e-mail to userReply with quote
After having read a little up on IBM's blue gene computer and professor Modha's brain simulations, I'm starting to feel the same skepticism about the whole thing as you apparently do.

Here's Modha's blog describing his experiments on simulating mouse- and cat-scale brains - It's sounds very promising, as if cognitive computing is just around the corner.

http://p9.hostingprod.com/@modha.org/blog/2009/11/post_3.html

And then there are these responses. Here's Henry Markram's - a colleague at EPFL - email sent to many other colleagues as a response to Hodhas experiments.

http://spectrum.ieee.org/tech-talk/semiconductors/devices/blue-brain-project-leader-angry-about-cat-brain

And then there are these posts over at the Al Fin blog:

http://alfin2100.blogspot.com/2009/11/more-on-ibms-bluematter-brain.html

http://alfin2100.blogspot.com/2009/11/actually-no-ibm-did-not-simulate-cats.html

So now I really don't know what to think. These questions swirl in my mind:

We can build a physical model of a galaxy with millions of bodys, where every object interacts (gravitationally) with every other object all the time. Each interaction requires a call to the square root function, which is computationally expensive.
So, why can't we also simulate an insect's brain with only a few tens of thousands of cells, and where each neuron only interactis with some of the other neurons, and where no cpu expensive square root calls are necessary?

How come a small mammal with a brain requiring only a few watts of energy cannot be simulated by a supercomputer like blue gene, which requires tens of thousands of watts? What the hell is going on?!?

Cheers, at 03:00 in the morning,

Mike



tkorrovi
posted 5/10/2010  09:07Send e-mail to userReply with quote
 
DanishMike wrote @ 5/10/2010 3:59:00 AM:
How come a small mammal with a brain requiring only a few watts of energy cannot be simulated by a supercomputer like blue gene, which requires tens of thousands of watts? What the hell is going on?!?

 
Likely, moving molecules takes less energy than switching the electronic gates... Consider, molecules are the smallest entities which can stay in one place, that, and a network-like structure which enables to move them in an organized way. But when even this takes too much energy, then the only alternative are the quantum effects, or some combination of molecular movements and quantum effects.


hunt
posted 5/11/2010  02:42Reply with quote
"After having read a little up on IBM's blue gene computer and professor Modha's brain simulations, I'm starting to feel the same skepticism about the whole thing as you apparently do."

I think the problem really boils down to publicity vs. science. Science needs the publicity to spur both interest and funding. Unfortunately, outlandish claims of cat brains are more interesting to those outside the academic community, which is really a shame because what they're doing is quite impressive even without all the hyperbole.

"So, why can't we also simulate an insect's brain with only a few tens of thousands of cells, and where each neuron only interactis with some of the other neurons, and where no cpu expensive square root calls are necessary?"

Yeah, I agree. I'd like a clear answer on where current technology stands vs. the implementation of a model of this sort.

"How come a small mammal with a brain requiring only a few watts of energy cannot be simulated by a supercomputer like blue gene, which requires tens of thousands of watts? What the hell is going on?!?"

It boggles how truly inefficient modern computing is vs. the brain. And that's really what the answer is: computers are inefficient.

Think about this: you could simulate all the actions your computer does to make a calculation or display some text on its screen by running through the same algorithm using pen and paper manipulations. But you'd probably take all night to simulate the display of one post--that's a lot of coke and chips to get the job done! Many more calories than your battery is burning through, anyway. ;)


larae2156273o
posted 11/5/2011  10:44Send e-mail to userReply with quote
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tkorrovi
posted 11/5/2011  18:28Send e-mail to userReply with quote
 
hunt wrote @ 5/11/2010 2:42:00 AM:
I think the problem really boils down to publicity vs. science. Science needs the publicity to spur both interest and funding. Unfortunately, outlandish claims of cat brains are more interesting to those outside the academic community, which is really a shame because what they're doing is quite impressive even without all the hyperbole.

 
I see that for you science, and everything it does, is a holy cow. If science does something wrong, or stupid, or goes to wrong direction, then who is responsible for that is not academic community, but people outside the academic community. At the same time when whoever does or says something not accepted in the academic community, then this person would be labeled insane by the academic community. And when someone does something wrong outside the academic community, then certainly academic community is never responsible.

Even when they encourage absolutely unreasonable development in AI based on completely senseless arguments, poor people who believe them, put a lifetime of efforts in trying to implement their ideas and fail, are by themselves responsible for their failure at best, or labaled insane by the same academic community, in the worst case. Arthur T Murray here is a good example, someone who unfortunately went wrong because of what science made him to believe, and when failed then attacked by the same science. If one would compare the academic commnity to a person, then it would be an incredibly selfish and obstinate person, acting like a psychopath towards all others.

I am too in a way a victim. I was too encouraged to do great things in AI. But fortunately i found out how wrong these ideas all were, and thus didn't go insane by pursuing the goals which cannot be achieved. Instead, i found something else greater than i could imagine, always known by the smartest people on earth, but completely and perhaps deliberately omitted in science.

This is not a criticism of all scientists, and not a criticism of all science, i know that there are good scientists, it is just against considering academic community a holy cow, which it by far is not. And this is relevant to this topic, because of the criticism which appeared here about the nonsense ideas by the mainstream science. And threads, they can also go their own way, people should be free, that's the bottom line.

 Artificial Consciousness ADS-AC project
Last edited by tkorrovi @ 11/5/2011 6:53:00 PM

simnia
posted 8/25/2012  04:53Reply with quote
One such project starts next month, September 2012, which will attempt to completely simulate the brain of a bee, using biological data:

"Build a simulation of an insect brain to explain how bees perceive the world and learn about their
environment. Its more than just a bee flight simulator; you will design its auto-pilot brain capable
of learning to forage for food, learning to use landmarks for navigation, and explain phenomena
of complex cognition in bees. This is a rare opportunity to tightly couple software engineering
skills with real biological experiments in the same lab."

http://www.queensu.ca/psychology/news/Weekly-Memo/PhDStudentUK.pdf

Therefore it's likely such a simulation hasn't been accomplished yet.



DanishMike
posted 8/25/2012  09:42Send e-mail to userReply with quote
Hi there, thank you for the link. This is exactly what I've been looking for. Here's an excerpt from the application:

"In this ambitious joint Biology and
Computer Science PhD you will program a simulation of a bee in an environment to explain how
such behaviour could be mediated by a miniature brain in situated and embodied tasks. The
simulated bee will have a visual system and a motor system, and will fly in a 3D environment.
The simulation must be reconfigurable to various levels of abstraction allowing modelling of
functions such as concept learning, reinforcement learning, landmark learning etc, as well as
lower level visually based flight functions, and purely reactive obstacle avoidance functions. It
will allow testing of various controllers, e.g. spiking neuronal networks, continuous time
recurrent neural networks, computer vision algorithms, cognitive architectures, etc."

Though I must say it sounds very ambitious. For instance they're planning to make the software available on the web and for schools. It is beyond my comprehension how they intend to run a simulation with roughly 10^5 neurons and 10^9 synapses in real-time on an average desktop computer. I'm hoping for this project to return some interesting results, but I'm honestly having serious doubts wether it's going to work.

Cheers,
Mike


futcoinsboy
posted 8/21/2014  12:23Send e-mail to userReply with quote
I know there is a project aimed at simulating a cat

http://www.goldentok.com/

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