
Can The Human Brain Project be saved, and should it be? - Fede_V
http://chronicle.com/article/Can-the-Human-Brain-Project-Be/190031/?key=HWNxIQxsYHVGMS4wYG1KZz1dayFsMBl8Y35PPngjblFWFQ==
======
api
"A strong personality..."

I've seen a good number of boondoggles. At the center of each was a
personality of such magnetism that people simply fell in line behind them.
There are people who have the ability to spout utter nonsense, but to do so
with such alpha _authority_ that nearly everyone in the room just glazes over
and nods. Whatever it is that our brains take as a signal of alpha status,
these people know how to crank it to 11.

When are people going to learn that primate dominance gestures are not a
reliable proxy for much else?

I will say that when actual merit and this level of dominance actually align
in the same individual, amazing things can happen. But I see no sign that this
is more common than would be predicted by the random assortment of traits.

~~~
ploxiln
That sort of thing really doesn't affect nearly everybody. But those people
which it doesn't affect, leave the project, or are pushed out. So it's a self-
selecting/reinforcing thing, which is what makes it problematic, I think.

~~~
api
In the end you basically end up with a cult of personality around the
charismatic leader.

------
aheilbut
The marketing and salesmanship of the Human Brain Project may have been a
little too successful for its own good. On one hand, the idea that simply
building a giant brain simulation would be possible or scientifically useful
is not currently realistic.

However, I don't think they (Markram et al.) are that naive. In reality, the
project is composed of a lot of different subprojects, in simulation,
neuromorphic computing, mapping/characterizing mouse and human brains and
doing actual neuroscience, theory, applications to human disease, even
philosophy and ethics, etc. see:
[https://www.humanbrainproject.eu/discover/the-project/sub-
pr...](https://www.humanbrainproject.eu/discover/the-project/sub-projects) and
their list of publications so far
[https://www.humanbrainproject.eu/science/publications](https://www.humanbrainproject.eu/science/publications)

It's a huge umbrella for neuroscience funding that they marketed to the EU
under the grand vision of simulating the brain. Whether or not this kind of
marketing/funding mechanism is an optimal way to do the best science is a very
legitimate issue to debate. But the implication (which the HBP brought upon
themselves..) that a bunch of crackpots have been given a billion dollars to
buy supercomputers and run nonsensical simulations is an oversimplification.

------
crazypyro
[http://www.bioworld.com/content/computer-science-vs-
biology-...](http://www.bioworld.com/content/computer-science-vs-biology-
heart-human-brain-project-division)

I was curious why there was only neuroscientists and biologists quoted so I
went looking for another source. I think this link gives a different, broader
overview of the situation and doesn't only focus on personal attacks.

Specifically neuroscience subproject funding was removed... This seems like
angry academics that lost funding are trying to derail it through the media to
my uneducated observance...

~~~
orbifold
I think the overall problem is that traditional neuro scientists and
biologists bring virtually none of the required skills to the table.

Moreover while neuroscience is able to show pretty pictures of brain activity,
they have made insufficient progress in understanding it. On the other hand
the physicists/mathematicians that have invaded the field have a background in
computational methods, simulation and hardware development. So for example a
group at the University I studied had previous experience designing analog
chips for feature detection in High Energy Physics, a number of years ago they
re-branded themselves as a neurophysics group and recently landed a ~100
million euro+ grant in the context of the Human Brain Project.

It is also much easier to learn the jargon and read some of the softer
phenomenological articles than to develop a sound understanding of the
underlying mathematics and physics.

~~~
aheilbut
It is also much easier to conjure up some entertaining but biologically
meaningless mathematical model than to spend years doing real biological
experiments.

I think the overall problem is that the physicists and the biologists don't
have respect for each other's skills and knowledge.

~~~
orbifold
Obviously a biologist will have lots of knowledge and skills a physicist
doesn't have. Mathematical models can be very useful even if they don't model
the real world faithfully, as long as they capture part of the behavior to
some precision. Physicists spend an extraordinary amount of time studying toy
models to build up intuition, which together with an understanding how to
proceed in more complicated solutions can be very useful. For example even
though most real world EM problems won't have the symmetries required to come
up with a closed form solution, the intuition gained from studying toy
examples is still invaluable.

In the case of neurons you can model the membrane of the neuron and the
interior and exterior to various degrees of accuracy as an EM problem, if you
wish you can even add surface defects. Since the temperature is high, all
quantum effects are essentially washed out, as are the need to model
individual calcium ions etc., at least to first approximation. After the dust
settles you can come up with a few effective parameters that model one neuron
and an ODE that models its dynamics. As it turns out the ODE indeed exhibits
dynamics similar to real world neurons in response to electric stimuli.

If you then couple those ODEs into larger system and try different coupling
configurations (the coupling coefficients model the synapses between neurons),
you have come up with a simplified model for parts of a brain.

------
Simp
The entire point of the "Future and Emerging Technologies" FET Flagship
program (where the HBP got it's money) was to fund risky, daring and ambitious
technology projects.

Here's an article about the Human Genome Project from 1990:
[http://www.nytimes.com/1990/06/05/science/great-15-year-
proj...](http://www.nytimes.com/1990/06/05/science/great-15-year-project-to-
decipher-genes-stirs-opposition.html)

 _" The critics argue that the human genome project has been sold on hype and
glitter, rather than its scientific merits, and that it will drain talent,
money and life from smaller, worthier biomedical efforts."_

 _" They also doubt that the project can be completed in anything close to its
original deadline and budget."_

 _" it will have generated enormous reams of uninterpretable and often useless
data"_

 _" it's hyped science"_

 _" Everybody I talk to thinks this is an incredibly bad idea"_

 _" Some critics have begun aggressive letter-writing campaigns"_

The exact same arguments that were used 25 years ago to discredit the HGP are
now resurfacing to criticize the HBP. And with genome sequencing now below
1000$, that article has become almost laughable.

~~~
savanaly
Just because the HGP turned out to be worthwhile doesn't mean funding it in
the right place was the correct decision. If the expected value of the HGP was
below the opportunity cost it should not have been funded. That the actual
value turned out to be higher than the opportunity cost is irrelevant.

To say it another way, I think that playing the lotto with the goal of earning
money is a mistake. The fact that some people win it and in fact make money
doesn't change the fact that they were wrong to play it in the first place if
their goal was net gain of money.

That said I have no idea what the expected value of the HGP was so I have no
idea whether it was a good decision. I just want to chime in in support of
thinking about the probabilities involved in the right way.

~~~
geographomics
Expected value is a bit of a strange concept to apply to scientific research,
as no-one really knows for certain what the full, long-term impact will be.
The actual value of many scientific discoveries only becomes apparent years
later on.

~~~
philh
No one knows for certain, but... suppose you have two projects and can fund
one of them.

Project A wants to investigate in as much depth as possible (given their
budget) the effects of nail-biting on arthritis.

Project B wants to investigate in as much depth as possible (given their
budget) the effects of learning a programming language on Alzheimer's disease.

I know which of these seems like a better choice for funding, even though I
don't really know for certain what the long-term impact of either will be.

~~~
savanaly
Couldn't we say that you have formed an estimate of both projects in your
mind, and your estimate of the present value of all net benefits from project
B is higher than your estimate of project A?

~~~
philh
More or less. That sounds like it's giving me too much credit. I wouldn't say
I have two estimates so much as one intuition - but that's what my intuition
corresponds to, yes. If I made those estimates, I would expect to have a
higher estimate for project B than project A.

(But I should note that I deliberately chose projects where it seemed obvious
which one was better, so that I didn't need to do any calculations or even
think very hard about which one to prefer. In reality, sometimes it's not
obvious, and you should think hard and do calculations and it still might not
be obvious, and the specific project being discussed is probably one of those
cases.)

------
Udo
The Human Brain Project is a brute force attempt at solving AI (and
biological) research problems, and as such it's certainly not alone. I recall
supercomputers being put to use in simulating just one neuron at the molecular
level. The difference being of course that we do have enough modeling data to
make the single neuron simulation fly in principle, whereas the entire brain
is ridiculously out of scope.

The main problem with the project though is not the missing scientific data -
that just makes it unfeasible _for now_. What makes it unfeasible _in any
context_ is the detail level at which the simulation is supposed to be carried
out. This quote from the article expresses it better than I could have done:

 _Eero Simoncelli, a neuroscientist at New York University. "Would you try to
understand the universe by simulating every molecule? What would you have
achieved? It’s going to be just as complicated as the real thing and you won’t
understand it any better."_

~~~
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](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.

------
araes
Not a neuroscientist (never thought I'd use NANS), and this may well be the
boondoggle of a charismatic man who's using it to buy yachts and laugh at the
EU.

That said, the one benefit I could see is that it's a billion+ motivation for
folks to think about a hard problem. They likely won't accomplish a 100
billion neuron sim, but 100's to 1000's of people will hopefully be thinking
about that goal, trying to decompose it, and producing useful sub-advances.
Maybe like the HGP or the LHC or space flight, intense money will lead to
enabling technologies that accelerate what is possible.

The other problem is that humans are horrible at predicting scientific
progress, even in fields they are comfortable / experts in. Edge scientists
may actually suffer from this the worst. So much of life has been devoted to
becoming an expert in the field that it becomes more challenging to consider
large changes. Even while most major breakthroughs are built from analogies to
other fields, and more "simple" every day phenomena. Ex: Relativity, one of
the weirdest advances ever, came from thought about trains.

Maybe a billion+ could be spent more wisely, but at least they're spending it.
These are the same folks who decry our governments whenever they reduce
funding and malign the sciences. Stop complaining and find a way to write the
grant, or meet the right folks, or whatever's necessary so you can be a part
of the money train and get something useful done.

------
albertzeyer
Can someone explain a bit about the problems? I am not a Neuroscientist but a
Machine Learning researcher, and given the recent results in Deep Learning /
Artificial Neural Networks which reach Human performance in certain specific
tasks, it almost looks like if you would just put an ANN together which is
somewhat big enough and somewhat similar wired together as the Human brain,
you would yield something similar. And the point is, it doesn't really matter
at all whether that is exactly like in the Human brain, and also, you don't
really need to understand in detail how it will work, like you can even not
really explain the current simple ANNs. It just works anyway. So, under this
view, it's just a matter of scaling up, and to wait until we have enough
computing power. And then, you would add more details to make it more close to
the real Human brain.

~~~
sz4kerto
As an ML practitioner, you certainly know that the ANNs you use have not much
in common with biological (real) NNs. First, ANNs tend to be mostly
feedforward, while rNNs are highly recurrent. ANNs are therefore not very good
in tasks where memory is needed (I know about the developments involving LSTM
neurons, but they are not analogous to the implicit memory of recurrent neural
networks.) Second, ANNs usually don't have a time dimension, the firing is
essentially a floating point value instead of action potential. Third,
recurrent neural network structures do not scale: an
efficient/reliable/reduntant system of 100B neurons will probably have
extremely different structures than another one with 100M neurons -- because
of recurrency and other stuff a rNN is a chaotic process (in the sense of
sensitivity to parameters) that should be stabilized by the structure.

And there are many-many other differences. Note that our task is not to solve
problems but to figure out how the brain works.

Also, recurrent neural network simulation cannot really be scaled right now,
we don't have the hardware. It is not parallelizable with our current tools
because of the huge number of connections.

(Disclaimer: I was involved in a project trying to model real neural networks.
It wasn't a huge success, but we learned a lot.)

~~~
creamyhorror
This is a good informed summary, thank you. I asked the same question of my
Alzheimer researcher friend, and he gave a pretty similar response including
aspects like the huge computational requirements and the basic non-similarity
of rNNs and ANNs (albeit with a disclaimer that he wasn't in the field).

Nonetheless, I look forward to seeing more simple rNNs being created over time
(besides the C. elegans one that was modeled recently). Who knows what strange
organizational rules or structures we will discover from this strand of
research?

------
fiatmoney
For a vastly smaller-scale version of this, check out OpenWorm.

[http://www.openworm.org](http://www.openworm.org)

It defies understanding why one wouldn't start with a much simpler organism
rather than trying to go directly to the human brain. For one thing, you can
actually experiment on, e.g., a rat brain in a way that you can't on humans.

~~~
cr4zy
Hugely excited about OpenWorm!

More great stuff about the robotic embodiment of OpenWorm:

[http://www.i-programmer.info/news/105-artificial-
intelligenc...](http://www.i-programmer.info/news/105-artificial-
intelligence/7985-a-worms-mind-in-a-lego-body.html)

[https://news.ycombinator.com/item?id=8745639](https://news.ycombinator.com/item?id=8745639)

Eyewire.org is also _really_ cool -- for example, they have already made an
important discovery into how our eyes detect motion:
[http://www.scientificamerican.com/article/online-gamers-
help...](http://www.scientificamerican.com/article/online-gamers-help-crack-
mystery-of-how-eyes-sense-motion/)

------
Animats
A reasonable near-term goal is to get OpenWorm [1] to work well in simulation.
That's the simplest known organism with a system of neurons, and the
connections have been fully mapped out. Until that works, there's little point
in trying anything more complex.

The "the next step is the human brain" people have a poor track record. Rodney
Brooks tried that once. He'd done a good reactive-controller insect, and then
immediately tried to jump to human-brain level with Cog.[2] When he gave a
talk at Stanford proposing Cog some years ago, I asked him "Why not try for a
mouse next? That might be within reach." He said "I don't want to go down in
history as the man who created the world's best artificial mouse". Cog was an
embarrassing failure.

The Human Brain Project should be put on hold until OpenWorm works and that
technology has been advanced to at least the lizard level. The Human Brain
Project is likely to turn into an expensive supercomputer boondoggle.

[1] [http://www.openworm.org/](http://www.openworm.org/) [2]
[http://www.ai.mit.edu/projects/humanoid-robotics-
group/cog/c...](http://www.ai.mit.edu/projects/humanoid-robotics-
group/cog/cog.html)

~~~
oco101
Sure please take a look at this an tell me if you see any similarities (1990):
[http://www.nytimes.com/1990/06/05/science/great-15-year-
proj...](http://www.nytimes.com/1990/06/05/science/great-15-year-project-to-
decipher-genes-stirs-opposition.html)

~~~
Animats
That was about sequencing DNA. It was known how to sequence DNA before the
Human Genome Project started. It just cost too much and was too slow. That was
a production scaling problem.

If we ever get to a mouse brain, it's just scaling from there - all the
mammals have very similar DNA. We don't know how to make even a good lizard
brain yet. Or even a full insect nervous system.

------
streptomycin
I always figured it would make sense to try something like C. elegans first
before jumping right into simulating the human brain. Progress has been slow
on that front: [http://www.jefftk.com/p/whole-brain-emulation-and-
nematodes](http://www.jefftk.com/p/whole-brain-emulation-and-nematodes)

------
sambe
As others have pointed out there is a long anecdotal history of magnetic
personalities getting hype and funding based on their empty promises. However,
there are large counterexamples and this article clearly contains little
technical criticism (another commenter links to a more balanced view).

The Human Genome Project is cited as one such example: simultaneously not
meeting the hyped goals whilst also being more successful than imagined in
other ways. Perhaps what people are missing here is that the value may not be
in simulating the brain but rather having the infrastructure on which to run
simulations. This likely starts in parts and on a small scale but the
infrastructure alone could be incredibly useful for generating new ideas and
shortening feedback time.

------
grondilu
> "Would you try to understand the universe by simulating every molecule? What
> would you have achieved? It’s going to be just as complicated as the real
> thing and you won’t understand it any better."

I'm pretty sure cosmologists would love to make simulations to a molecular
precision. They currently simulate gas clouds with supercomputers in order to
study the formation of galaxies and the more precise the better.

~~~
TheEzEzz
Absolutely right, simulations are critical in physics, cosmology, and pretty
much every hard science. I think the nay-saying in the article is indicative
of a larger enmity some academics have towards simulation based science. The
harder sciences have mostly come to terms with the contributions simulations
can make, but I think it will be sometime before the softer disciplines come
around. In the meantime, politics and ad hominems as usual.

------
geographomics
This document detailing the overall vision of the project is worth a read:
[https://www.humanbrainproject.eu/documents/10180/17646/Visio...](https://www.humanbrainproject.eu/documents/10180/17646/Vision+Document/8bb75845-8b1d-41e0-bcb9-d4de69eb6603)

I'd be very surprised if they come anywhere near reaching their goal of a
comprehensive whole-brain simulation, but even if the overall project aim
falls short, many of the sub-projects are likely to provide worthwhile
outcomes.

For example, structural and functional data generation projects described in
there (SP1, SP2 and SP3) sound reasonable and reflect the kinds of topics and
techniques that are being researched already. The neuroinformatics (SP5) and
medical informatics platforms (SP8), while very ambitious, seem like they
could be a tremendously useful resource for linking disparate data sets
together into a single, more easily-accessible database.

I can see why many neuroscientists are scoffing at the rather over-hyped grand
aim of the project, but that doesn't mean the entire thing should be scrapped.
Personally I think that funding comparatively open-ended, long-term, risky
research is a good thing. Even if it 'fails', that failure is informative in
itself in helping to provide scope for future projects. And it increases the
opportunity for serendipitous discoveries.

------
Aqueous
The example given by the NYU neuroscientist seems to be betray some
misunderstanding/lack of vision:

"Would you try to understand the universe by simulating every molecule? What
would you have achieved? It’s going to be just as complicated as the real
thing and you won’t understand it any better."

At the very least you would have achieved the ability to rewind and play the
universe forward again, which is something that we most certainly can't do
with our real universe. You would also have achieved the ability to experiment
with and measure the universe with potentially greater precision than we can
in the physical world.

Simulation is a tool to help you understand, not understanding itself. I don't
think Markram ever said anything to the contrary.

------
koerding
Some more in depth comments about the HBP that go beyond the Chronicle
article: [http://www.quora.com/What-are-the-main-objections-to-the-
hum...](http://www.quora.com/What-are-the-main-objections-to-the-human-brain-
project/answer/Konrad-Koerding?__snids__=795167122%2C817538217&__nsrc__=2)

------
marmaduke
There are alternative approaches that attack the problem of simulating the
human brain with a smarter set of approximations, e.g.
[http://thevirtualbrain.org](http://thevirtualbrain.org)

------
TheHeasman
_" When a distinguished but elderly scientist says that something is possible,
(s)he is almost certainly right. When (s)he says it is impossible (s)he is
very probably wrong."_ \- Arthur C Clarke

~~~
SapphireSun
The reason these scientists are upset is because we are no where near being
able to do this. They're not saying we can't do it someday, just that it's a
crazy waste of money right now. We don't know enough about the brain to make
reasonable full scale models of it yet.

------
scottlocklin
I have a book from 1968 where this was proposed as an inevitability by the
1980s. The same author (it was sponsored by the foreign policy association)
assumed ray guns and antigravity were highly likely.

------
orblivion
This kind of research is walking head first into an ethical nightmare. I say
stay the hell away.

~~~
SapphireSun
Why do you think that?

~~~
Filligree
A simulation of a human brain is a human being, and human experiments are
generally considered unethical. To say nothing of the possibilities if they
_succeed_.

~~~
orblivion
Assuming it is, in fact, actually experiencing life, and not just appearing to
be.

But if it is, imagine what happens when, in 50 years, it becomes cheap to
reproduce. Any bozo can get a copy of it. The potential for mistreatment is
beyond anything seen yet on Earth, as bad as that's been so far. Check out the
Christmas special of Black Mirror, for just one example.

~~~
Udik
One point for citing Black Mirror's Christmas special. It gave me nightmares,
literally.

------
valevk
Why are such projects always coordinated as one big blob? Isn't it possible to
just fund startups that are active in this industry, and see which one
survives? Of course there should be regulation to a specific degree. VCs are
doing the same, and it seems to be working (for the VCs).

~~~
TeMPOraL
> _VCs are doing the same, and it seems to be working (for the VCs)._

Well, you don't want that in science. The point of startups (from VC's point
of view) is to make money for VC - startups themselves and their survival is
irrelevant. The point of research is to gain knowledge and not to make money.
That's two completely different kinds of thinking.

~~~
_almosnow
>The point of research is to gain knowledge and not to make money.

Hahahahahahaha.

Joke aside, I haven't seen "science just for the sake of science" ever.

~~~
TeMPOraL
Go to your local university then, talk to an older physics professor.

------
rokhayakebe
I am sensing Dan Brown just got some material for his next book.

------
_almosnow
Good to see that time puts everything in its place.

