from the getting-plugged-in-to-new-technology dept.
Since they came into use by physicians and researchers, Brain-Computer Interfaces (BCIs) or Brain-Machine Interfaces (BMIs) have provided ways to treat neurological disorders and shed light on how the brain functions. As beneficial as they've been, BCIs have potential to go far beyond the technology's current capabilities. In a collaboration between the Yale School of Engineering & Applied Science (SEAS) and Yale School of Medicine, a team of researchers are looking to break through these limitations.
"The goal is to build a class of ultra-low-power devices that are safe for chronic implantation in humans," said Abhishek Bhattacharjee, associate professor of computer science. "Chronic implantation opens the door to a number of clinical uses, ranging from implants to treat epilepsy and movement disorders to designing assistive devices for patients with paralysis, as well as many research uses."
[...] The tricky part about this goal is that these implantable BCIs are limited by how much power they use. Federal and international guidelines state that BCIs must not use more than 15 to 40 milliwatts of power, depending on the depth within the brain tissue that the BCI is implanted. Anything beyond that is unsafe for chronic implantation in humans. Excessive power dissipation causes the devices to overheat, which brings the risk of damaging the cellular tissue of the brain. The SEAS researchers' task, then, is broadening the potential of these devices while staying within a very constrained power limit. They're limiting the power of their own device to 15 milliwatts, which would allow it to be placed deeper into the brain, where power constraints are more stringent.
"So, it's power-constrained, but at the same time, there are some serious computation needs here—you need to be able to read and perform fairly sophisticated signal processing on more and more data from the brain for these devices to be more useful," Bhattacharjee said. "How you do all of this under really tight power budgets of 10 to 15 milliwatts is a wide-open question."
To that end, they've developed HALO (Hardware Architecture for Low-power BCIs), a general-purpose architecture for implantable BCIs. The technology allows for the treatment of various conditions, and records and processes data for studies to advance our understanding of the brain. The technology includes a chip and sensors and allows for a microelectrode array that reads roughly 50 megabits per second from 96 distinct parts of the brain. And unlike other BCIs, which are designed for one specific purpose — treating epilepsy, for example — the HALO technology can support numerous tasks. This is all achieved while operating within the team's strict power budget.
[...] "One of the things that I'm particularly excited about in our research is that it shows that if you build BCIs that can balance specialized hardware with general purpose hardware in a principled way, you can actually be under the power limit, while supporting a much broader class of computational functionalities than what existing devices support," Bhattacharjee said. He also believes that the results point to a broader question beyond BCIs, particularly because the waning of Dennard scaling (the principle that as transistors get smaller, their power stays constant) "poses questions about how best to determine what to build hardware accelerators for, how to integrate these hardware accelerators seamlessly, and how to enable a modular platform that can naturally slot in new accelerators. HALO is an exemplar of these research questions."
Shixian Wen, Allen Yin, Tommaso Furlanello, et al. Rapid adaptation of brain–computer interfaces to new neuronal ensembles or participants via generative modelling, Nature Biomedical Engineering (DOI: 10.1038/s41551-021-00811-z)