Recent advancements in brain-computer interface (BCI) technology are poised to revolutionize the fields of neurotechnology, spatial computing, and mixed/virtual reality. Synchron, a leading BCI company, recently showcased a groundbreaking achievement by integrating its BCI solution with Apple Vision Pro, a mixed-reality headset. This milestone was demonstrated by an amyotrophic lateral sclerosis (ALS) patient, underscoring the technology’s potential to enhance the lives of those with severe neurological impairments.
Tom Oxley, CEO and founder of Synchron, anticipated this transformative moment four years ago. He remarked, “We’re building something that we think is going to be transformative technology capable of streaming direct thought for people who, through injury or disease, have lost the capacity to move or speak.” Synchron’s achievement highlights the significant progress being made in leveraging artificial intelligence (AI) and machine learning to decode and interpret complex brain data, especially for individuals with locked-in syndrome, neuromuscular disorders, and paralysis.
The concept of a brain-computer interface was first introduced by Jacques Vidal, Ph.D., a computer science professor emeritus at the University of California, Los Angeles, in his 1973 paper, “Toward Direct Brain-Computer Communication.” According to Grand View Research, the BCI industry is expected to reach $6.2 billion in revenue by 2030, growing at a compound annual growth rate of 17.5% from 2023 to 2030. This projected growth underscores the burgeoning interest and investment in BCI technologies.
What sets Synchron’s BCI apart is its innovative, non-invasive implantation process. Unlike traditional BCIs that require brain surgery, Synchron’s solution employs a stent-based approach. Stents, small mesh tubes commonly used in medical procedures to prevent blood vessel narrowing or to deliver medication, are repurposed in this context to record brain activity. Synchron’s BCI uses a stent-electrode array equipped with 16 sensors to capture the brain’s motor signals. This neuroprosthesis, named the Stentrode, is implanted via a minimally invasive endovascular procedure. The stent is placed in a blood vessel on the surface of the brain’s motor cortex through the jugular vein in the neck, eliminating the need for invasive brain surgery.
The stent, made of a super-elastic nickel and titanium alloy called nitinol, expands up to eight millimeters within the blood vessel. This allows it to remain securely in place, capturing brain signals that are then transmitted via a lead to an implanted device below the collarbones. The BCI utilizes AI and machine learning to translate these signals into user commands, which can be sent to an external digital device, such as the Apple Vision Pro headset. This innovative approach offers a safer and more accessible alternative to traditional BCIs, making it possible to assist a broader range of patients.
In a real-world application, a 64-year-old ALS patient named Mark successfully used his thoughts to control a computer cursor. This remarkable achievement enabled him to compose and send texts, select TV programs, and play an immersive virtual reality card game of Solitaire, all without the use of his hands. This integration of AI, BCI, spatial computing, and medical devices represents a significant advancement in neurotechnology, heralding a new era in digital health and promising more powerful assistive technologies in the future.
In another development, a brain-computer interface surgically implanted on the brain of an ALS patient has shown promising results in translating brain signals into computer commands. This new study, led by Johns Hopkins Medicine researchers in collaboration with the Johns Hopkins University Applied Physics Laboratory, highlights significant advancements in BCI technology. The results, published in Advanced Science, demonstrated that computer commands could be accurately translated from brain activity over a three-month period without the need for retraining or recalibration of the BCI algorithm.
The BCI, known as CortiCom, was surgically implanted on the surface of brain areas responsible for speech and upper limb function in a patient with ALS. Tim Evans, a 62-year-old diagnosed with ALS in 2014, participated in the study. Despite severe speech and swallowing problems, Evans was able to reliably use six basic commands (up, down, left, right, enter, and back) to navigate a communication board and control smart devices like room lights and streaming TV applications. The BCI’s deep-learning algorithm allowed Evans to issue verbal commands to control a communication board in real-time, enabling him to navigate and select items despite his speech being difficult for human listeners to understand.
Unlike many other BCI studies, this approach used non-penetrative electrodes, allowing the team to record large populations of neurons from the brain’s surface. The accuracy of the BCI remained consistent over the three months of the study, indicating the potential for independent home use of speech BCIs by people with severe paralysis. This success suggests that participants could use the BCI without ongoing researcher intervention, offering the freedom to control household devices independently.
The integration of BCI technology into clinical practice holds the promise of significantly improving the quality of life for ALS patients. By restoring their ability to control home devices, BCIs offer a new level of independence and communication for individuals with severe paralysis. As research progresses, the potential for BCIs to transform the lives of those with neurological impairments becomes increasingly tangible. The continued development of procedures and standards of care for the clinical application of BCIs, including addressing medical and ethical considerations, will be crucial in bringing this transformative technology to those who need it most.
