Scientists unveil a groundbreaking brain chip that revolutionizes real-time thought transmission. This innovative brain implant holds the potential to transform how we interact with computers and offers new treatment avenues for various conditions, including epilepsy, spinal cord injuries, ALS, stroke, and blindness. By establishing a minimally invasive, high-throughput communication pathway to the brain, it promises to control seizures and restore motor, speech, and visual functions. The technology's promise lies in its compact size and ability to transmit data at lightning-fast speeds. Developed through a collaborative effort between Columbia University, NewYork-Presbyterian Hospital, Stanford University, and the University of Pennsylvania, the device is a brain-computer interface (BCI) built on a single silicon chip. This chip creates a wireless, high-bandwidth connection between the brain and external computers, forming the Biological Interface System to Cortex (BISC). A study published in Nature Electronics details BISC's architecture, which includes the chip-based implant, a wearable 'relay station,' and the software required to run the platform. The implant is remarkably thin, fitting between the brain and the skull, and is designed to rest on the brain like a piece of wet tissue paper. This approach significantly reduces the space occupied by the electronics within the body, making the implant more comfortable and less invasive. The BISC system is built on a single complementary metal-oxide-semiconductor (CMOS) integrated circuit, thinned to 50 μm and occupying a fraction of the volume of standard implants. With a total size of about 3 mm³, the flexible chip can curve to match the brain's surface. It features 65,536 electrodes, 1,024 recording channels, and 16,384 stimulation channels, enabling high-resolution data collection and processing. The chip integrates a radio transceiver, wireless power circuit, digital control electronics, power management, data converters, and analog components for both recording and stimulation. The external relay station, operating as an 802.11 WiFi device, bridges any computer to the implant, providing a throughput of 100 Mbps, at least 100 times higher than existing wireless BCIs. BISC incorporates its own instruction set and a comprehensive software environment, forming a specialized computing system for brain interfaces. This high-bandwidth recording capability allows brain signals to be processed by advanced machine-learning and deep-learning algorithms, enabling complex interpretation of intentions, perceptual experiences, and brain states. The BISC implant was fabricated using TSMC's 0.13-μm Bipolar-CMOS-DMOS (BCD) technology, combining digital logic, high-current and high-voltage analog functions, and power devices in a single chip. This technology enables efficient collaboration between these essential components, contributing to BISC's performance. To transition the system into real-world medical use, the research team partnered with a neurosurgeon at NewYork-Presbyterian/Columbia University Irving Medical Center. They developed surgical procedures to safely place the thin implant in a preclinical model and confirmed its ability to produce high-quality, stable recordings. Short-term intraoperative studies in human patients are already underway. The extensive preclinical work in the motor and visual cortices involved recognized leaders in computational and systems neuroscience, further validating the technology's potential. BISC was developed through the Neural Engineering System Design program of the Defense Advanced Research Projects Agency (DARPA) and leverages the expertise of Columbia University, Stanford University, and the University of Pennsylvania in microelectronics, advanced neuroscience, and surgical capabilities. To advance the technology towards practical use, researchers at Columbia and Stanford founded Kampto Neurotech, a startup producing research-ready versions of the chip and securing funding for human patient trials. This innovative BCI device has the potential to revolutionize how we treat brain disorders and interface with machines, marking a significant step towards seamless brain-AI interaction for human benefit.
