To Build a Supercomputer Replica of a Human Brain


Markram’s grand vision to simulate an entire brain’s worth of neurons will require epic computing power. The project’s first Blue Gene supercomputer was robust enough to simulate a single neocortical column in a rat (its whole brain has the equivalent of 100,000 columns). The Human Brain Project will eventually need an astronomical amount of memory and computational speed—at least 100 petabytes of RAM and an exaflop—to make its sims possible. —Katie M. Palmer

Illustration: Brown Bird Design

Through it all, Markram continues to battle a chorus of serious-minded naysayers. The eminent neuroscientist Moshe Abeles of Bar-Ilan University in Israel points out that the brain “differs from one individual to another, and in some respect it also differs in each of us from day to day. Our ability to understand all the details of even one brain is practically zero. Therefore, the claim that accumulating more and more data will lead to understanding how the brain works is hopeless.”

Abeles didn’t keep his opinion to himself while Markram’s proposal was under review as one of six finalists (among about 120 entrants) for the billion-euro European Flagship Initiative grant. In the Israeli newspaper Haaretz last year, he proclaimed, “the Human Brain Project is irresponsible in terms of public interest. It’s obvious the researchers won’t be able to keep their promise. So it’s robbing the public purse on one hand and sabotaging the future of science on the other.”

Around the same time, harsh criticism also came from Rodney Douglas, who moved to Lausanne’s archrival, ETH Zurich, in 1995. “We need variance in neuroscience,” he declared at a session of the Swiss Academy of Sciences in January 2012, spreading the alarm that with a billion euros Markram could achieve a monopoly on the field.

“Rodney Douglas’ resistance is a farce,” Markram responds, sounding less angry than sad. “It’s envy, it’s ego. He’s at the end of his career, measuring a piece of a circuit, and he still doesn’t know what it’s doing.” As if to prove Markram’s point, Douglas—who declined to be interviewed—will retire in July.

Christof Koch believes envy is responsible for most criticism of Markram. “This is not a zero-sum game,” he says. “It isn’t that Henry is going to get a billion euros or neuroscience is going to get it. The money comes out of the European infrastructure. If it doesn’t go to his modeling facility, it might bail out another Greek or Italian bank.” Though Koch remains skeptical of Markram’s 10-year time frame, that didn’t keep him from spending three days this spring in Lausanne, coordinating their respective research programs. “I like his vision,” Koch says. “The guy has cojones.” The distinguished University of Manchester computer engineer Steve Furber, inventor of the ARM processor, is even more fully won over. “There aren’t any aspects of Henry’s vision I find problematic,” he asserts. “Except perhaps his ambition, which is at the same time both terrifying and necessary.”

Markram thinks that the greatest potential achievement of his sim would be to determine the causes of the approximately 600 known brain disorders. “It’s not about understanding one disease,” he says. “It’s about understanding a complex system that can go wrong in 600 different ways. It’s about finding the weak points.” Rather than uncovering treatments for individual symptoms, he wants to induce diseases in silico by building explicitly damaged models, then find workarounds for the damage. Researchers have done the same with lab animals for decades, observing their behavior after giving them lesions. The power of Markram’s approach is that the lesioning could be carried out endlessly in a supercomputer model and studied at any scale, from molecules to the brain as a whole.

A researcher could see the world as a schizophrenic while watching what is going on in the patient’s mind.

And the view wouldn’t just be from the outside. Neuroscientists could not only see the flow of neurotransmitters and ions but could also experience the delusions. “You want to step inside the brain,” Markram says. He’ll achieve this by connecting his model brain to sensor-laden robotics and simultaneously recording what the robot is sensing and “thinking” as it explores physical environments, correlating audiovisual signals with simulated brain activity as the machine learns about the world. A neuroscientist could then play back those perceptions as distorted by a damaged brain simulation. In an immersive 3-D environment, a researcher could see the world as a schizophrenic while watching what is going on in the schizophrenic’s mind.

In hype-driven contexts (such as his 2009 TED talk), Markram has hinted at the possibility that a sim embodied in a robot might become conscious. Hardwired with Markram’s model and given sufficient experience of the world, the machine could actually start thinking (à la Skynet and HAL 9000). While that has gained him a following among sci-fi enthusiasts, he separates such speculations from the hard work of doing real science. When pressed, he shows a rare touch of modesty. “A simulation is not the real thing,” he says. “I mean, it’s a set of mathematical equations that are being executed to re-create a particular phenomenon.” Markram’s job, simply put, is to get those equations right.

He plans to give the EU an early working prototype of this system within just 18 months—and vows to “open up this new telescope to the scientific community” within two and a half years—though he estimates that he’ll need a supercomputer 100,000 times faster than the one he’s got to build the premium version. Ever the optimist, he believes that Moore’s law (and the European Union) will deliver him that raw power in about a decade. However, he’ll also need far more data than even his industrial-strength Blue Brain lab can collect. Shortly after arriving at Lausanne, Markram developed workflows that extracted experimental results from journals, strip-mining thousands of neuroscience papers only to find that the data was too inconsistent to use in a model. For a while, that looked like one of his biggest hurdles. But he has since been building standardized protocols for many of the labs participating in the Human Brain Project. His timing may be just right, with the data glut expected from the Allen Brain Atlas, the Human Connectome Project, and the Brain Activity Map. According to Brown University neuroscientist John Donoghue, one of the key figures in the Obama-sanctioned initiative, “the two projects are perfect complements. The Human Brain Project provides a means to test ideas that would emerge from Brain Activity Map data, and Brain Activity Map data would inform the models simulated in the Human Brain Project.”

One of the few people with experience simulating the entire human brain (albeit in much less detail than Markram), University of Toronto psychologist Randy McIntosh is also tentatively optimistic about Markram’s project. “Technically speaking, I think it is possible to do this,” he says. “I tend to think of the Human Brain Project in the same way one should have considered the Human Genome Project, where the thought was that once the genome was sequenced, we would solve genetic-based disease and understand the genetic basis of behavior. We are nowhere near that, but in moving toward that goal, a huge number of insights and innovations came.”

Genomics has proven that biology, like astronomy and physics, thrives on big data. In the 21st century, going big is the way of all science. The brain is due for a billion-euro enlargement.

Contributor Jonathon Keats ( is the author of Forged: Why Fakes Are the Great Art of Our Age.