The U.S. BRAIN Initiative Boldly Begins

Big science takes on the human brain

7 min read
The U.S. BRAIN Initiative Boldly Begins
Illustration: Eddie Guy

Sometimes when I think of the human brain, the theme from “Star Trek” starts playing in my own head. It’s the music of great unknowns—and in certain ways the human brain, with more connections between its cells than there are galaxies in the observable universe, is as vast and uncharted as that final frontier.

Despite decades of research, no detailed explanation yet exists of how the interplay of electrical and chemical activity between cells becomes the music I hear in my mind’s ear. No scientific model describes how a few simple notes elicit such emotion, nor how I might protect those feelings from dementia’s ravages decades hence.

human os icon

Beginning to answer such questions is the grand, daunting ambition of the Brain Research Through Advancing Innovative Neurotechnologies program, better known as the BRAIN Initiative. U.S. president Barack Obama formally announced the federal project in April 2013 with a US $110 million first-year budget that will be parceled out to the National Institutes of Health (NIH), the National Science Foundation (NSF), and the Defense Advanced Research Projects Agency (DARPA). Four private institutions—the Kavli Foundation, Allen Institute for Brain Science, Howard Hughes Medical Institute, and Salk Institute for Biological Studies—have also committed a total of $122 million of their own money to BRAIN work in 2014. Over the next year, the BRAIN Initiative should coalesce into one of the century’s defining scientific projects.

“In my mind, it’s the greatest challenge of our time,” says Miyoung Chun, the Kavli Foundation’s vice president of science programs. It was Chun who, in late 2012, played matchmaker between the White House and a small group of neuroscientists who had big plans for charting neurological activity. From those meetings grew the BRAIN Initiative, which at its inception focused narrowly on developing new tools to record electrical activity in unprecedented numbers of neurons, with the plan to eventually turn those recordings into maps of human brain function.

Fun Facts

neurons icon - 150 trillion

150 trillion

Estimated number of connections that link the neurons in the human brain

blood icon - 750 milliliters

750 milliliters per minute

Typical blood flow through the human brain (15 percent of cardiac output)

conscious icon - 8-10 seconds

8–10 seconds

Time until unconsciousness after loss of blood supply to the brain

ear icon - 160 mili-seconds

160 milli-seconds

Human response time to an auditory stimulus

womb icon - 250 000 neurons

250 000 neurons per minute

Approximate rate of neuron creation during early pregnancy

brain icon - 1.5 kilograms

1.5 kilograms (3 pounds)

Average weight of an adult brain (about 2 percent of the body’s weight)

With those maps, scientists might come to know far more than they do now about the brain’s biology, what happens as people think and feel, or when malfunction becomes disease. They’re not the first researchers to seek this knowledge, of course, but the project’s proponents say we’re at a unique historical moment: Our technological and computational power may finally be commensurate with our questions.

“The human brain is a miracle. It gives rise to infinitely many thoughts, emotions, memories, actions. How can one biological organ, a collection of cells, do all that?” says Rockefeller University neuroscientist Cori Bargmann, cochair of the NIH’s advisory committee. “No matter how long you’ve been a neuroscientist, it is still amazing that this complexity emerges from such mundane biological components.”

When President Obama first announced the BRAIN Initiative, however, many researchers were skeptical. The current tools of human brain analysis are indeed coarse, they agreed, incapable of recording neurological activity at the detail and scope they’d like. But was large-scale, fine-grained mapping realistic? For instance, current state-of-the-art neurological recording of zebra fish involves some 80 000 neurons, and that requires subjecting the creatures to techniques that would never be used on humans. That’s quite a few orders of magnitude less challenging than recording activity from the 75 million neurons of a mouse, to say nothing of a human’s roughly 86 billion neurons.

Even if technologies could be developed to record all that information, what could you do with the results? It would be an informational deluge that would make genomic big data look puny. “Many people were concerned that the project was overambitious and impractical,” says Donald Stein, a neurophysiologist at Emory University, in Atlanta.

Following the scientific outcry, the NIH, NSF, and DARPA held a series of workshops and meetings with scores of scientists to discuss what BRAIN should be. While the project will continue to evolve, the research priorities described in recent NSF and NIH reports emphasize basic science and tool development that can lead to grander map-making projects as the years go on.

The report from the NIH advisory committee doesn’t put the recording of cell activity at the top of the list. Rather, it starts with a back-to-basics mandate. The report calls for a census of the brain’s cell types, which encompass not only many varieties of neurons but also glia, a long-underappreciated family of cells that may actually outnumber neurons. The physical forms of these cells in mice and other animals will be characterized, along with their molecular and genetic properties, their locations, and ultimately how they connect to other cells, both individually and in groups.

These network-spanning wiring diagrams are called connectomes, and they’re considered crucial. Researchers now understand that an act of perception or cognition doesn’t rely on the neurons in just one area of the brain; instead, it involves complicated neural circuits that can weave through multiple regions. Although similar connection-mapping projects already exist—the first roundworm connectome was published in 1986, and the NIH’s Human Connectome Project launched in 2009—they don’t approach the comprehensiveness or detail envisioned in the NIH report.

To study cells and their networks in new detail, investigators will need to rely on a whole new toolbox, possibly including microscopes that can look at larger sections of a brain than is now practical, and “optical needles” that can penetrate a brain’s deep tissues, rather than just the outermost layers where most imaging now occurs. Going beyond passive imaging, some new methods enable researchers to activate cells or whole networks inside a living animal, helping them understand cell roles and network dynamics and eventually linking them to behavior. Optogenetic techniques, for example, deliver light-sensitive molecules to target cells, then stimulate them with light pulsed through a fiber-optic implant.

The BRAIN Initiative hasn’t given up on its original goal of recording neuronal activity, which will also require new tools. One proposed method would make use of flexible sheets fashioned from hundreds of thousands of nanowire electrodes, which would conform to a brain’s topography while noninvasively recording its activity. Researchers continue to debate how much to record: Eavesdropping on every single cell in a nervous system isn’t feasible, but how many are representative?

As of now, activity can be directly recorded from perhaps 100 neurons at a time, their electrical spikes measured by tiny implanted electrodes. At the other end of the spectrum is functional magnetic resonance imaging, or fMRI, which measures blood flow as a proxy for activity in regions containing millions of cells. “There’s a lot of information in the middle scale that we don’t have,” says Jack Gallant, a neuroscientist at the University of California, Berkeley. “And it’s not just that you need to record from every neuron. You need to record for a long period of time.”

Measuring that activity over time is the only way to study the extraordinary dynamism of brains. There’s no such thing as a static map of a brain. Its connections are ever-fluctuating, reconfiguring themselves on the fly. We now know that the connectome is capable of extreme transformation, as seen in the brains of stroke victims who recover functions typically linked to now-damaged regions.

Dealing with the resulting data will require still more tools, of the mathematical and conceptual varieties. Researchers will need algorithms and processing techniques that allow them to make sense of raw data and to understand how neurological activity encodes information, just as computer codes are so much more than strings of ones and zeros. “There are certain kinds of data that we get from the brain and don’t know how to analyze,” says Gallant. “Nonlinear systems with feedback”—weather, for example, or brains—“are mathematically hard systems to deal with. There just aren’t good tools for dealing with them.”

When the NIH issues its firstBRAIN grants in 2014, it will likely concentrate on projects that match the agency’s strengths, such as direct work on animals. Once the NIH’s concentrations are clear, the NSF will start doling out its funds, perhaps focusing on its own strengths, such as biophysics and computer science. The NSF’s reports echo many of the NIH report’s priorities, calling for the development of technologies to map brain structure and activity; they also emphasize the need for sophisticated new methods to store and analyze the massive amounts of data that will result from large-scale mapping efforts.

DARPA’s role is more mysterious. The defense agency will likely look at promising near-term applications for soldiers, such as improvements on existing brain-imaging technologies that can aid soldiers with brain injuries, but it may also take a chance on seemingly improbable ventures. Its existing neuroscience programs offer some hints that DARPA is interested in neurally enhanced soldiers: One project seeks interventions that can reduce the negative impact of stress. Other DARPA projects focus on cyborg-style fixes for injured soldiers, such as neurally linked prosthetic limbs and neural prosthetics that could replace lost cognitive or memory function.

“The feeling is that whatever path we go down, it will usher in a new era,” says Herbert Levine, a Rice University professor of bioengineering who coauthored one of the NSF’s BRAIN reports. A concern of Levine and others, though, is whether Congress will continue to fund the project, which doesn’t yet have a federal budget beyond 2014. Continued funding is expected but hardly assured, and will be decided in the next year.

As BRAIN proponents push for funding, they’ll have to walk a fine line of self-promotion. The project’s potential applications for self-understanding, the treatment of disease, and prosthetics are clear, but it’s unrealistic to expect breakthroughs, much less cures or answers to existential questions, in the next few years. At the same time, Congress and the public may have little patience for theoretical insights and the slow pace of basic research. Scientists may be tempted to overpromise, setting the stage for eventual disappointment and backlash. As difficult a sell as it may be, the BRAIN Initiative should be embraced for what it is: a grand, ambitious voyage into the unknown.

This article originally appeared in print as “Big Science Takes on the Brain.”

About the Author

Brandon Keim, a correspondent for Wired Science and a freelance science journalist, was skeptical about the U.S. government’s massive initiative to map the human brain. “I had some existential issues with it,” he says, adding that he initially found the project overambitious and ill-defined. But in the course of his reporting, he spoke to neuroscientists who were dividing that daunting task into more achievable goals. “It’s great that it’s going forward,” he says now.

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