A new brain implant stands to transform human-computer interaction and expand treatment possibilities for neurological conditions such as epilepsy, spinal cord injury, ALS, stroke, and blindness – helping to manage seizures and restore motor, speech, and visual function. This is done by providing a minimally invasive, high-throughput information link directly to and from the brain.
The transformational potential of this new system lies in its small size and ability to transfer data at high rates. Developed by researchers at Columbia University, NewYork-Presbyterian Hospital, Stanford University, and the University of Pennsylvania, this brain-computer interface (BCI) relies on a single silicon chip to establish a wireless, high-bandwidth connection between the brain and any external computer. The platform is called the Biological Interface System to Cortex (BISC).
Described in a study published Dec. 8 in Nature Electronics, BISC includes a single-chip implant, a wearable “relay station,” and the custom software required to operate the system. “Most implantable systems are built around a canister of electronics that occupies enormous volumes of space inside the body,” says Ken Shepard, Lau Family Professor of Electrical Engineering, professor of biomedical engineering, and professor of neurological sciences at Columbia University, who is one of the senior authors on the work and guided the engineering efforts. “Our implant is a single integrated circuit chip that is so thin that it can slide into the space between the brain and the skull, resting on the brain like a piece of wet tissue paper.”
Shepard was joined in the BISC effort by senior and co-corresponding author Andreas S. Tolias, PhD, professor of Ophthalmology and co-founding director of the Enigma Project at Stanford University. Tolias’s pioneering work training AI models on large-scale neural datasets — including datasets recorded in the Tolias laboratory using BISC — enabled the team to evaluate the device’s neural decoding performance. “BISC turns the cortical surface into an effective portal, delivering high-bandwidth, minimally invasive read–write communication with AI and external devices,” Tolias says. “Its single-chip scalability paves the way for adaptive neuroprosthetics and brain-AI interfaces to treat many neuropsychiatric disorders, such as epilepsy.”
Dr. Brett Youngerman, assistant professor of neurological surgery at Columbia University and a neurosurgeon at NewYork-Presbyterian/Columbia University Irving Medical Center, served as the chief clinical collaborator on the project. “This high-resolution, high-data-throughput device has the potential to revolutionize the management of neurological conditions from epilepsy to paralysis,” he says. Youngerman, Shepard, and NewYork-Presbyterian/Columbia epilepsy neurologist Dr. Catherine Schevon were recently awarded a grant from the National Institutes of Health to implement BISC in the management of drug-resistant epilepsy. “The key to effective brain-computer interface devices is to maximize the information flow to and from the brain, while making the device as minimally invasive in its surgical implantation as possible. BISC surpasses previous technology on both fronts,” continues Dr. Youngerman.
“Semiconductor technology has made this possible, allowing the computing power of room-sized computers to now fit in your pocket,” Shepard says. “We are now doing the same for medical implantables, allowing complex electronics to exist in the body while taking up almost no space.”
Smaller, Safer, and Faster
BCIs work by interfacing with the electrical signals that neurons use to transfer information throughout the brain. Today’s state-of-the-art BCIs, used in medical contexts, are constructed from individual microelectronic components, including amplifiers, data converters, radio transmitters, and power management circuits. To accommodate all these devices, a large canister of electronics must be surgically implanted in the body, either by removing a portion of the skull or by placing the device in another location, such as the chest, and running wires to the brain.
BISC works differently. The entire implant, which occupies less than 1/1000th the size of a conventional device, is a single complementary metal-oxide-semiconductor (CMOS) integrated circuit chip thinned to just 50 μm. With a total volume of approximately 3 mm³, the flexible chip conforms to the surface of the brain. This micro-electrocorticography (µECoG) device integrates 65,536 electrodes, 1,024 simultaneous recording channels, and 16,384 stimulation channels. By leveraging the large-scale manufacturing techniques developed in the semiconductor industry, these implants can be easily manufactured at scale.
The single-chip implant includes a radio transceiver, wireless powering circuit, digital control, power management, data conversion, and the analog circuits required to support the recording and stimulation interfaces. The battery-powered relay station powers and communicates with the implant, transferring data via a custom ultrawideband radio link that achieves 100 Mbps data bandwidths — a connection with at least 100 times higher throughput than any competing wireless BCI device. The relay station is itself an 802.11 WiFi device, in effect forming a relayed wireless network connection from any computer to the brain.
BISC has its own instruction set, supported by an extensive software stack, which together constitute a computing architecture designed for BCIs. As demonstrated in this study, these high-bandwidth recording capabilities allow brain-signal patterns to be submitted to advanced machine-learning or deep-learning frameworks for decoding complex intentions, perceptions, or states.
“By integrating everything on one piece of silicon, we’ve shown how brain interfaces can become smaller, safer, and dramatically more powerful,” Shepard says.
From Lab to Clinic
To make this technology available to doctors and patients, Shepard’s group partnered closely with Youngerman at NewYork-Presbyterian/Columbia University Irving Medical Center. Together, they refined surgical methods to safely implant the paper-thin device in a preclinical model and demonstrated its recording quality and stability, as described in the current study. Studies in human patients for short-term intraoperative recordings are underway.
“These initial studies give us invaluable data about how the device performs in a real surgical setting,” Youngerman says. “The implants can be inserted through a minimally invasive incision in the skull and slid directly onto the surface of the brain in the subdural space. The paper-thin form factor and lack of brain-penetrating electrodes or wires tethering the implant to the skull minimize tissue reactivity and signal degradation over time.”
Extensive pre-clinical testing of BISC in the motor and visual cortices drew on collaborations with both Dr. Tolias and Bijan Pesaran, professor of neurosurgery at the University of Pennsylvania, both of whom are leaders in computational and systems neuroscience.
“The extreme miniaturization by BISC is very exciting as a platform for new generations of implantable technologies that also interface with the brain with other modalities such as light and sound,” Pesaran says.
Developed under the Neural Engineering Systems Design program of the Defense Advanced Research Projects Agency (DARPA), BISC combines Columbia’s strengths in microelectronics, Stanford’s and Penn’s cutting-edge neuroscience, and NewYork-Presbyterian/Columbia University Irving Medical Center’s surgical innovation.
Toward Real-World Applications
To accelerate translation, the Columbia and Stanford teams launched Kampto Neurotech, a spin-off company founded by Columbia electrical engineering alumnus Dr. Nanyu Zeng, one of the project’s lead engineers. Kampto Neurotech is developing commercial versions of the chip for preclinical research applications and raising funds to advance the system toward human use.
“This is a fundamentally different way of building BCI devices,” Zeng says. “In this way, BISC has technological capabilities that exceed those of competing devices by many orders of magnitude.”
In a technological landscape driven by advances in artificial intelligence, BCI technologies have drawn considerable recent interest in both restoring function to those affected by neurological conditions and in potentially augmenting human capabilities by providing direct interfaces to the brain.
“By combining ultra-high resolution neural recording with fully wireless operation, and pairing that with advanced decoding and stimulation algorithms, we are moving toward a future where the brain and AI systems can interact seamlessly — not just for research, but for human benefit,” says Shepard. “This could change how we treat brain disorders, how we interface with machines, and ultimately how humans engage with AI.”
