[cubetime]

Agreed that it's unfeasible for now, of course, but I'm a little amazed people aren't seeing the uses of this.

We can edit, directly observe, and record/playback simulated brains. We can test ten million different models on top of a recorded simulation and see which one fits best. Eero doesn't think we could learn about how the brain works by simulating a trillion slightly different permutations on a brain, or (maybe more ethically) small subsystems of a brain, and observing how each behaves?

Sweet god, the economic implications! http://mason.gmu.edu/~rhanson/uploads.html

Horrifying, maybe, but I don't see how people can get away with suggesting this will never be valuable to anyone.

[Udo]

I think you might be misunderstanding the intent of my argument a bit.

> I'm a little amazed people aren't seeing the uses of this.

That's not the issue - I imagine everyone here would like to see these goals reached. Nobody has to sell anyone on the rewards of neuro research. The question is merely whether this specific project can deliver them.

> We can edit, directly observe, and record/playback simulated brains.

The idea itself is a good one. However, the key issue becomes choosing an appropriate level of detail for the simulation. I believe a blanket choice of "let's just do the entire brain" is computationally infeasible right now, plus we don't have good enough models to actually program the thing - but most importantly even in a future where these problems are solved the device seems like a blunt and unwieldy instrument that won't give up its data easily.

> or (maybe more ethically) small subsystems of a brain

That's what's already happening all over the world right now, in thousands of independently scoped simulations and experiments.

[cubetime]

If you're just saying that this specific project is a poor use of resources at the moment, then yeah, agreed. I don't really feel justified in suggesting that any particular level of abstraction will have so little to tell us that it'll never be a good use of resources.

>That [simulating small subsystems of a brain] is what's already happening all over the world right now, in thousands of independently scoped simulations and experiments.

Woah! Links? The searches I can come up with aren't turning up anything besides that simulation of a rat cortical column and the various attempts at nematode uploading.

[Udo]

> that it'll never be a good use of resources.

Never is a long time ;)

> Woah! Links?

Any university with a neuroscience department does this. Go to your local university's website and browse what they're doing in that area: more likely than not you'll find something interesting. Basic research on neurons has become very common, and computer-based modeling is a fundamental part of it. The perception problem here is that, say, modeling the signaling behavior of locust neurons seems like a very inconsequential piece of the puzzle - but in reality it's what we need to do to figure this stuff out.

The fundamental problem in neuroscience research is not a lack of complexity, for now we need to move away from complexity in order to observe the behavior of basic building blocks. It may seem embarrassing how we're still at that stage, but it's where we stand.

[simonster]

This is not my subfield of neuroscience, but here are some people I know who do spiking neural network simulation to understand how brains work:

http://www.math.pitt.edu/~bdoiron/

http://neurotheory.columbia.edu/~larry/

http://www.cns.nyu.edu/wanglab/

http://alleninstitute.org/our-research/modeling-analysis-the... (modeling group)

http://www.nada.kth.se/~ala/

There are also some companies that are led by people with academic experience doing spiking neural network simulation and seem to be trying to commercialize it:

http://www.braincorporation.com/

http://www.evolvedmachines.com/

[cubetime]

Ah, yes, "a single neuron" is indeed a small subsystem of a brain, and it is indeed common nowadays.

[erikpukinskis]

Here's where I would start: https://www.google.com/search?q=computational+modeling+cogni...