DARPA Funds Ambitious Brain-Machine Interface Program

The N3 program aims to develop wearable devices that let soldiers to communicate directly with machines.

3 min read
Future soldier using a VR headset
Photo-illustration: iStockphoto

DARPA’s Next-Generation Nonsurgical Neurotechnology (N3) program has awarded funding to six groups attempting to build brain-machine interfaces that match the performance of implanted electrodes but with no surgery whatsoever.

By simply popping on a helmet or headset, soldiers could conceivably command control centers without touching a keyboard; fly drones intuitively with a thought; even feel intrusions into a secure network. While the tech sounds futuristic, DARPA wants to get it done in four years.

“It’s an aggressive timeline,” says Krishnan Thyagarajan, a research scientist at PARC and principal investigator of one of the N3-funded projects. “But I think the idea of any such program is to really challenge the community to push the limits and accelerate things which are already brewing. Yes, it’s challenging, but it’s not impossible.”

The N3 program fits right into DARPA’s high-risk, high-reward biomedical tech portfolio, including programs in electric medicine, brain implants and electrical brain training. And the U.S. defense R&D agency is throwing big money at the program: Though a DARPA spokesperson declined to comment on the amount of funding, two of the winning teams are reporting eye-popping grants of $19.48 million and $18 million.

Plenty of noninvasive neurotechnologies already exist, but not at the resolution necessary to yield high-performance wearable devices for national security applications, says N3 program manager Al Emondi of DARPA’s Biological Technologies Office.

Following a call for applications back in March, a review panel narrowed the pool to six teams across industry and academia, Emondi told IEEE Spectrum. The teams are experimenting with different combinations of magnetic fields, electric fields, acoustic fields (ultrasound) and light. “You can combine all these approaches in different, unique and novel ways,” says Emondi. What the program hopes to discover, he adds, is which combinations can record brain activity and communicate back to the brain with the greatest speed and resolution.

Specifically, the program is seeking technologies that can read and write to brain cells in just 50 milliseconds round-trip, and can interact with at least 16 locations in the brain at a resolution of 1 cubic millimeter (a space that encompasses thousands of neurons).

The four-year N3 program will consist of three phases, says Emondi. In the current phase 1, teams have one year to demonstrate the ability to read (record) and write to (stimulate) brain tissue through the skull. Teams that succeed will move to phase 2. Over the ensuing 18 months, those groups will have to develop working devices and test them on living animals. Any group left standing will proceed to phase 3—testing their device on humans.

Four of teams are developing totally noninvasive technologies. A team from Carnegie Mellon University, for example, is planning to use ultrasound waves to guide light into and out of the brain to detect neural activity. They plan to use  interfering electrical fields to write to specific neurons.

The three other teams proposing non-invasive techniques include Johns Hopkins University’s Applied Physics Laboratory, Thyagarajan’s team at PARC, and a team from Teledyne Technologies, a California-based industrial company.

The two remaining teams are developing what DARPA calls “minutely invasive” technologies which, as we described in September, require no incisions or surgery but may involve technology that is swallowed, sniffed, injected or absorbed into the human body in some way.

Rice University, for example, is developing a system that requires exposing neurons to a viral vector to deliver instructions for synthetic proteins that indicate when a neuron is active. Ohio-based technology company Battelle is developing a brain-machine interface that relies on magnetoelectric nanoparticles injected into the brain.

“This is uncharted territory for DARPA, and the next step in brain-machine interfaces,” says Emondi. “If we’re successful in some of these technologies…that’s a whole new ecosystem that doesn’t exist right now.”

A version of this post appears in the July 2019 print issue as “Wanted: Hi-Res, Surgery-Free Brain Interfaces.”

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This CAD Program Can Design New Organisms

Genetic engineers have a powerful new tool to write and edit DNA code

11 min read
A photo showing machinery in a lab

Foundries such as the Edinburgh Genome Foundry assemble fragments of synthetic DNA and send them to labs for testing in cells.

Edinburgh Genome Foundry, University of Edinburgh

In the next decade, medical science may finally advance cures for some of the most complex diseases that plague humanity. Many diseases are caused by mutations in the human genome, which can either be inherited from our parents (such as in cystic fibrosis), or acquired during life, such as most types of cancer. For some of these conditions, medical researchers have identified the exact mutations that lead to disease; but in many more, they're still seeking answers. And without understanding the cause of a problem, it's pretty tough to find a cure.

We believe that a key enabling technology in this quest is a computer-aided design (CAD) program for genome editing, which our organization is launching this week at the Genome Project-write (GP-write) conference.

With this CAD program, medical researchers will be able to quickly design hundreds of different genomes with any combination of mutations and send the genetic code to a company that manufactures strings of DNA. Those fragments of synthesized DNA can then be sent to a foundry for assembly, and finally to a lab where the designed genomes can be tested in cells. Based on how the cells grow, researchers can use the CAD program to iterate with a new batch of redesigned genomes, sharing data for collaborative efforts. Enabling fast redesign of thousands of variants can only be achieved through automation; at that scale, researchers just might identify the combinations of mutations that are causing genetic diseases. This is the first critical R&D step toward finding cures.

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