In September 2011, a group of neuroscientists and nanoscientists gathered at a picturesque estate in the English countryside for a symposium meant to bring their two fields together.
At the meeting, Columbia University neurobiologist Rafael Yuste and Harvard geneticist George Church made a not-so-modest proposal: to map the activity of the entire human brain at the level of individual neurons and detail how those cells form circuits. That knowledge could be harnessed to treat brain disorders like Alzheimer’s, autism, schizophrenia, depression, and traumatic brain injury. And it would help answer one of the great questions of science: How does the brain bring about consciousness?
Yuste, Church, and their colleagues drafted a proposal that would later be published in the journal Neuron. Their ambition was extreme: “a large-scale, international public effort, the Brain Activity Map Project, aimed at reconstructing the full record of neural activity across complete neural circuits.” Like the Human Genome Project a decade earlier, they wrote, the brain project would lead to “entirely new industries and commercial ventures.”
New technologies would be needed to achieve that goal, and that’s where the nanoscientists came in. At the time, researchers could record activity from just a few hundred neurons at once—but with around 86 billion neurons in the human brain, it was akin to “watching a TV one pixel at a time,” Yuste recalled in 2017. The researchers proposed tools to measure “every spike from every neuron” in an attempt to understand how the firing of these neurons produced complex thoughts.
The audacious proposal intrigued the Obama administration and laid the foundation for the multi-year Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, announced in April 2013. President Obama called it the “next great American project.”
But it wasn’t the first audacious brain venture. In fact, a few years earlier, Henry Markram, a neuroscientist at the École Polytechnique Fédérale de Lausanne in Switzerland, had set an even loftier goal: to make a computer simulation of a living human brain. Markram wanted to build a fully digital, three-dimensional model at the resolution of the individual cell, tracing all of those cells’ many connections. “We can do it within 10 years,” he boasted during a 2009 TED talk.
In January 2013, a few months before the American project was announced, the EU awarded Markram $1.3 billion to build his brain model. The US and EU projects sparked similar large-scale research efforts in countries including Japan, Australia, Canada, China, South Korea, and Israel. A new era of neuroscience had begun.
An impossible dream?
A decade later, the US project is winding down, and the EU project faces its deadline to build a digital brain. So how did it go? Have we begun to unwrap the secrets of the human brain? Or have we spent a decade and billions of dollars chasing a vision that remains as elusive as ever?
From the beginning, both projects had critics.
EU scientists worried about the costs of the Markram scheme and thought it would squeeze out other neuroscience research. And even at the original 2011 meeting in which Yuste and Church presented their ambitious vision, many of their colleagues argued it simply wasn’t possible to map the complex firings of billions of human neurons. Others said it was feasible but would cost too much money and generate more data than researchers would know what to do with.
In a blistering article appearing in Scientific American in 2013, Partha Mitra, a neuroscientist at the Cold Spring Harbor Laboratory, warned against the “irrational exuberance” behind the Brain Activity Map and questioned whether its overall goal was meaningful.
Even if it were possible to record all spikes from all neurons at once, he argued, a brain doesn’t exist in isolation: in order to properly connect the dots, you’d need to simultaneously record external stimuli that the brain is exposed to, as well as the behavior of the organism. And he reasoned that we need to understand the brain at a macroscopic level before trying to decode what the firings of individual neurons mean.
Others had concerns about the impact of centralizing control over these fields. Cornelia Bargmann, a neuroscientist at Rockefeller University, worried that it would crowd out research spearheaded by individual investigators. (Bargmann was soon tapped to co-lead the BRAIN Initiative’s working group.)
There isn’t a single, agreed-upon theory of how the brain works, and not everyone in the field agreed that building a simulated brain was the best way to study it.
While the US initiative sought input from scientists to guide its direction, the EU project was decidedly more top-down, with Markram at the helm. But as Noah Hutton documents in his 2020 film In Silico, Markram’s grand plans soon unraveled. As an undergraduate studying neuroscience, Hutton had been assigned to read Markram’s papers and was impressed by his proposal to simulate the human brain; when he started making documentary films, he decided to chronicle the effort. He soon realized, however, that the billion-dollar enterprise was characterized more by infighting and shifting goals than by breakthrough science.
In Silico shows Markram as a charismatic leader who needed to make bold claims about the future of neuroscience to attract the funding to carry out his particular vision. But the project was troubled from the outset by a major issue: there isn’t a single, agreed-upon theory of how the brain works, and not everyone in the field agreed that building a simulated brain was the best way to study it. It didn’t take long for those differences to arise in the EU project.
In 2014, hundreds of experts across Europe penned a letter citing concerns about oversight, funding mechanisms, and transparency in the Human Brain Project. The scientists felt Markram’s aim was premature and too narrow and would exclude funding for researchers who sought other ways to study the brain.
“What struck me was, if he was successful and turned it on and the simulated brain worked, what have you learned?” Terry Sejnowski, a computational neuroscientist at the Salk Institute who served on the advisory committee for the BRAIN Initiative, told me. “The simulation is just as complicated as the brain.”
The Human Brain Project’s board of directors voted to change its organization and leadership in early 2015, replacing a three-member executive committee led by Markram with a 22-member governing board. Christoph Ebell, a Swiss entrepreneur with a background in science diplomacy, was appointed executive director. “When I took over, the project was at a crisis point,” he says. “People were openly wondering if the project was going to go forward.”
But a few years later he was out too, after a “strategic disagreement” with the project’s host institution. The project is now focused on providing a new computational research infrastructure to help neuroscientists store, process, and analyze large amounts of data—unsystematic data collection has been an issue for the field—and develop 3D brain atlases and software for creating simulations.
The US BRAIN Initiative, meanwhile, underwent its own changes. Early on, in 2014, responding to the concerns of scientists and acknowledging the limits of what was possible, it evolved into something more pragmatic, focusing on developing technologies to probe the brain.
Those changes have finally started to produce results—even if they weren’t the ones that the founders of each of the large brain projects had originally envisaged.
Last year, the Human Brain Project released a 3D digital map that integrates different aspects of human brain organization at the millimeter and micrometer level. It’s essentially a Google Earth for the brain.
And earlier this year Alipasha Vaziri, a neuroscientist funded by the BRAIN Initiative, and his team at Rockefeller University reported in a preprint paper that they’d simultaneously recorded the activity of more than a million neurons across the mouse cortex. It’s the largest recording of animal cortical activity yet made, if far from listening to all 86 billion neurons in the human brain as the original Brain Activity Map hoped.
The US effort has also shown some progress in its attempt to build new tools to study the brain. It has speeded the development of optogenetics, an approach that uses light to control neurons, and its funding has led to new high-density silicon electrodes capable of recording from hundreds of neurons simultaneously. And it has arguably accelerated the development of single-cell sequencing. In September, researchers using these advances will publish a detailed classification of cell types in the mouse and human motor cortexes—the biggest single output from the BRAIN Initiative to date.
While these are all important steps forward, though, they’re far from the initial grand ambitions.
We are now heading into the last phase of these projects—the EU effort will conclude in 2023, while the US initiative is expected to have funding through 2026. What happens in these next years will determine just how much impact they’ll have on the field of neuroscience.
When I asked Ebell what he sees as the biggest accomplishment of the Human Brain Project, he didn’t name any one scientific achievement. Instead, he pointed to EBRAINS, a platform launched in April of this year to help neuroscientists work with neurological data, perform modeling, and simulate brain function. It offers researchers a wide range of data and connects many of the most advanced European lab facilities, supercomputing centers, clinics, and technology hubs in one system.
“If you ask me ‘Are you happy with how it turned out?’ I would say yes,” Ebell said. “Has it led to the breakthroughs that some have expected in terms of gaining a completely new understanding of the brain? Perhaps not.”
Katrin Amunts, a neuroscientist at the University of Düsseldorf, who has been the Human Brain Project’s scientific research director since 2016, says that while Markram’s dream of simulating the human brain hasn’t been realized yet, it is getting closer. “We will use the last three years to make such simulations happen,” she says. But it won’t be a big, single model—instead, several simulation approaches will be needed to understand the brain in all its complexity.
Meanwhile, the BRAIN Initiative has provided more than 900 grants to researchers so far, totaling around $2 billion. The National Institutes of Health is projected to spend nearly $6 billion on the project by the time it concludes.
For the final phase of the BRAIN Initiative, scientists will attempt to understand how brain circuits work by diagramming connected neurons. But claims for what can be achieved are far more restrained than in the project’s early days. The researchers now realize that understanding the brain will be an ongoing task—it’s not something that can be finalized by a project’s deadline, even if that project meets its specific goals.
“With a brand-new tool or a fabulous new microscope, you know when you’ve got it. If you’re talking about understanding how a piece of the brain works or how the brain actually does a task, it’s much more difficult to know what success is,” says Eve Marder, a neuroscientist at Brandeis University. “And success for one person would be just the beginning of the story for another person.”
Yuste and his colleagues were right that new tools and techniques would be needed to study the brain in a more meaningful way. Now, scientists will have to figure out how to use them. But instead of answering the question of consciousness, developing these methods has, if anything, only opened up more questions about the brain—and shown just how complex it is.
“I have to be honest,” says Yuste. “We had higher hopes.”
Emily Mullin is a freelance journalist based in Pittsburgh who focuses on biotechnology.