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Why we're building a €1 billion model of a human brain
11 February 2013 by Jessica Griggs

The Human Brain Project has just won a €1 billion research prize. Its director Henry Markram says the initiative will unify our understanding of the brain

Your project aims to recreate the human brain in a supercomputer. Why?
We want to reach a unified understanding of the brain and the simulation on a supercomputer is the tool. Today you have neuroscientists working on a genetic, behavioural or cognitive level, and then you have informaticians, chemists and mathematicians. They all have their own understanding of how the brain functions and is structured. How do you get them all around the same table? We think of the project as like a CERN for the brain. The model is our way of bringing everyone, and our understanding, together.

What do you hope will come of the project?
There are three goals. As the model becomes more accurate and behaves more like a brain, we could couple it to a robot and see the robot learning. Then we'll be able to trace the chain of events from molecules to cognition.

Second, we plan to collect data from hospitals around the world to search for biological signatures of disease. We believe this will give us a new classification of brain disease, which can be used to diagnose people objectively - not solely based on their symptoms.

And finally, we want to build neuromorphic computers, which would have processors that can learn, mimicking the way the brain does.


"Once we've modelled a rat brain, then we update the rules and gradually move towards a human model"

How close are you to recreating a brain?
We've developed an algorithm to work out some of the rules for how to reconstruct the brain. We can now make thousands of predictions that when tested are accurate, and we can reconstruct small brain circuits of up to about 1 million rat neurons. Now we've got to connect those groups of neurons to make brain regions, then connect the regions to make a computer model of a whole brain. Once we've modelled a rat brain, then we update the rules and gradually move towards a human model.

Could the model be too detailed?
People are afraid of detail and complexity. But a drug is a molecule. It doesn't hit a cell, or the brain, it hits other molecules. There's no reason why we shouldn't try to explain how all the molecules are interacting with one another. Sheer numbers do not equal complexity. One hundred billion neurons is numbers, not complexity.

What about criticisms that it drains funds from more readily achievable neuroscience?
That is an incredibly short-sighted view of how a big science project impacts the rest of the field. Take the Human Genome Project - you can criticise them for all the promises they made at the time, but we would be in the dark ages now if we hadn't done that project. It has benefitted every biologist and geneticist on the planet today.

Once completed, could the simulated brain ever become conscious?
When we couple the model to a robot, the robot will behave, and we'll see this in the way its neurons are firing. Does that mean it's conscious? That's a philosophical question - and an unresolved one.

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Discussion Starter · #2 ·
On the same topic;


Will We Ever… Simulate the Brain?
by Ed Yong, National Geographic

For years, Henry Markram has claimed that he can simulate the human brain in a computer within a decade. On 23 January 2013, the European Commission told him to prove it. His ambitious Human Brain Project (HBP) won one of two ceiling-shattering grants from the EC to the tune of a billion euros, ending a two-year contest against several other grandiose projects. Can he now deliver? Is it even possible to build a computer simulation of the most powerful computer in the world-the 1.4-kg cluster of 86 billion neurons that sits inside our skulls?

The very idea has many neuroscientists in an uproar, and the HBP's substantial budget, awarded at a tumultuous time for research funding, is not helping. The common refrain is that the brain is just too complicated to simulate, and our understanding of it is at too primordial a stage.

Then, there's Markram's strategy. Neuroscientists have built computer simulations of neurons since the 1950s, but the vast majority treat these cells as single abstract points. Markram says he wants to build the cells as they are-gloriously detailed branching networks, full of active genes and electrical activity. He wants to simulate them down to their ion channels-the molecular gates that allow neurons to build up a voltage by shuttling charged particles in and out of their membrane borders. He wants to represent the genes that switch on and off inside them. He wants to simulate the 3,000 or so synapses that allow neurons to communicate with their neighbours.

Erin McKiernan, who builds computer models of single neurons, is a fan of this bottom-up approach. "Really understanding what's happening at a fundamental level and building up-I generally agree with that," she says. "But I tend to disagree with the time frame. [Markram] said that in 10 years, we could have a fully simulated brain I don't think that'll happen."
Even building McKiernan's single-neuron models is a fiendishly complicated task. "For many neurons, we don't understand well the complement of ion channels within them, how they work together to produce electrical activity, how they change over development or injury," she says. "At the next level, we have even less knowledge about how these cells connect, or how they're constantly reaching out, retracting or changing their strength." It's ignorance all the way down.

"For sure, what we have is a tiny, tiny fraction of what we need," Markram says. Worse still, experimentally mapping out every molecule, cell and connection is completely unfeasible in terms of cost, technical requirements and motivation. But he argues that building a unified model is the only way to unite our knowledge, and to start filling in the gaps in a focused way. By putting it all together, we can use what we know to predict what we don't, and also refine everything on the fly as new insights come in.

The crucial piece of information, and the one Markram's team is devoting the most time towards, is a complete inventory of which genes are active in which neurons. Neurons aren't all the same - they come in a variety of types that perform different roles and deploy different genes. Once Markram has the full list-the so-called "single-cell transcriptome"-he is confident that he can use it to deduce the blend of different neurons in various parts of the brain, recreate the electrical behaviour of each type of cell, or even simulate how a neuron's branches would grow from scratch. "We're discovering biological principles that are putting the brain together," he says.

For over two decades, his team have teased out the basic details of a rat's neurons, and produced a virtual set of cylindrical brain slices called cortical columns. The current simulation has 100 of these columns, and each has around 10,000 neurons-less than 2 percent of a rat's brain and just over 0.001 percent of ours. "You have to practice this first with rodents so you're confident that the rules apply, and do spot checks to show that these rules can transfer to humans," he says.

Eugene Izhikevich from the Brain Corporation, who helped to build a model with 100 billion neurons, is convinced that we should be able to build a network with all the anatomy and connectivity of a real brain. An expert could slice through it and not tell the difference. "It'd be like a Turing test for how close the model would be to the human brain," he says.

But that would be a fantastic simulation of a dead brain in an empty vat. A living one pulses with electrical activity-small-scale currents that travel along neurons, and large waves that pass across entire lobes. Real brains live inside bodies and interact with environments. If we could simulate this dynamism, what would emerge? Learning? Intelligence? Consciousness?
"People think I want to build this magical model that will eventually speak or do something interesting," says Markram. "I know I'm partially to blame for it-in a TED lecture, you have to speak in a very general way. But what it will do is secondary. We're not trying to make a machine behave like a human. We're trying to organise the data."

That worries neuroscientist Chris Eliasmith from the University of Waterloo in Ontario, Canada. "The project is impressive but might leave people baffled that someone would spend a lot of time and effort building something that doesn't do anything," he says. Markram's isn't the only project to do this. Last November, IBM presented a brain simulation called SyNAPSE, which includes 530 billion neurons with 100 trillion synapses connecting them, and does… not very much. It's basically a big computer. It still needs to be programmed. "Markram would complain that those neurons aren't realistic enough, but throwing a ton of neurons together and approximately wiring them according to biology isn't going to bridge this gap," says Eliasmith.

Eliasmith has taken a completely different approach. He is putting function first. Last November, he unveiled a model called Spaun, which simulates a paltry 2.5 million neurons but shows behaviour. It still simulates the physiology and wiring of the individual neurons, but organises them according to what we know about the brain's architecture. It's a top-down model, as well as a bottom-up one, and sets the benchmark for brain simulations that actually do something. It can recognise and copy lists of numbers, carry out simple arithmetic, and solve basic reasoning problems. It even makes errors in the same way we do-for example, it's more likely to remember items at the start and end of a list.

But the point of Spaun is not to build an artificial brain either. It's a test-bed for neuroscience-a platform that we can use to understand how the brain works. Does Region X control Function Y? Build it and see if that's true. If you knock out Region X, will Spaun's mental abilities suffer in a predictable way? Try it.

This kind of experiment will be hard to do with the HBP's bottom-up architecture. Even if that simulation shows properties like intelligence, it will be difficult to understand where those came from. It won't be a simple matter of tweaking one part of the simulation and seeing what happens.If you are trying to understand the brain and you do a really good simulation, the problem is that you end up with… the brain. And the brain is very complicated.

Besides, Izhikevich points out that technology is quickly outpacing many of the abilities that our brains are good at. "I can do arithmetic better on a calculator. A computer can play chess better than you," he says. By the time a brain simulation is sophisticated enough to reproduce brain's full repertoire of behaviour, other technologies will be able to do the same things faster and better, and "the problem won't be interesting anymore," says Izhikevich.

So, simulating a brain isn't a goal in itself. It's an end to some means. It's a way of organising tools, experts, and data. "Walking the path is the most important part," says Izhikevich.
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I think this is a great thing to do. It's very exciting to think what this might accomplish and discover.
 

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Could this possibly lead to immortality?
We can already replace every single organ...limbs are not a problem...they can even replicate blood by using nano particles that transport oxygen just like blood would! The only thing that stops us from immortality is our brain (dementia etc.)

It's very interesting, but to me immortality would be the only benefit. I'm not overly hyped on robots running the world, smartphones already dumbed society enough
 

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Discussion Starter · #5 ·
Could this possibly lead to immortality?
Possibly.

We can already replace every single organ...limbs are not a problem...they can even replicate blood by using nano particles that transport oxygen just like blood would! The only thing that stops us from immortality is our brain (dementia etc.)
That's a ahead of the current truth. We are doing work on being able to replace all parts of the body but we are a long way off completion yet.

However we will probably see it happen this century.

It's very interesting, but to me immortality would be the only benefit. I'm not overly hyped on robots running the world, smartphones already dumbed society enough
What about all the treatments for mental disorders it could potentially help with long before that? Surely as someone who frequents a SA forum you have an interest in that?
 

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That's disgusting :puke
 

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What about all the treatments for mental disorders it could potentially help with long before that? Surely as someone who frequents a SA forum you have an interest in that?
This is an interesting debate, replacing our brains seems a bit weird for the sake of our consciousness, would we still be that same person? would they replace the entire brain and let us be nothing like we were before.
I don't believe in a thing like the soul and I am sure that our personality (and all of its disorders are caused by the brain)

I prefer to be who I am, with my bad sides, than to replace my entire...being
 

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Discussion Starter · #9 ·
This is an interesting debate, replacing our brains seems a bit weird for the sake of our consciousness, would we still be that same person? would they replace the entire brain and let us be nothing like we were before.
I don't believe in a thing like the soul and I am sure that our personality (and all of its disorders are caused by the brain)

I prefer to be who I am, with my bad sides, than to replace my entire...being
Nobody is talking about replacing people's brains. Not yet anyway. :)

Have a perfect software model of a brain will allow us to better understand it which in turn will help with the treatment of people with mental issues.

In the far future if it was made possible to install a different brain I don't think anyone would choose to have one installed that made them a totally different person, as that would be akin to them dying.

However, being able to replace parts of a brain which are damaged/faulty would be invaluable to many people who currently suffer.
 
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