Controlling computers with just the power of thought has shifted from science fiction to scientific reality, thanks to the development of brain-computer interface (BCI) technology. These systems have made remarkable progress in allowing humans to manipulate complex devices using only their neural activity. However, a major challenge remains: finding a novel, reliable signal that can be detected noninvasively, through the scalp and skull, without the need for surgical implants.
Researchers from the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, in collaboration with the Johns Hopkins School of Medicine in Baltimore, have made significant strides toward this goal. They have identified a new potential signal for noninvasive BCI devices by focusing on deformations in neural tissue. This breakthrough could lead to new methods for recording brain activity with high resolution without requiring invasive surgical procedures. Their findings were published in the journal Scientific Reports as part of research funded by the Defense Advanced Research Projects Agency’s (DARPA) Next-Generation Nonsurgical Neurotechnology program.
Currently, the most effective BCI systems depend on surgically implanted devices to capture and decode neural signals. These invasive procedures have limited the use of BCI technology to specific clinical cases, involving only about 50 patients worldwide who have had BCIs surgically implanted. Noninvasive methods do exist, but they are often hindered by limitations in resolution, signal quality, and the practicality of the device itself. According to Mike Wolmetz, APL’s program manager for Human and Machine Intelligence, the team’s research could lay the groundwork for a noninvasive alternative that maintains high spatial and temporal resolution, an improvement that could expand BCI applications to a broader population.
BCI systems work by detecting brain activity linked to specific functions such as movement, attention, or speech and then decoding that information to control an external device. The challenge of developing a noninvasive BCI involves two main obstacles: discovering a brain signal that accurately indicates when and where neural activity occurs, and creating a method to capture that signal through the layers of the scalp and skull. The APL team aimed to solve the first problem by developing a specialized system capable of detecting incredibly subtle changes in the brain’s neural tissue.
The researchers introduced a digital holographic imaging (DHI) system to identify and validate a novel signal related to tissue deformation during neural activity. Neural tissue deformation involves minute changes, measured in nanometers, that occur when neurons are activated. This deformation is incredibly subtle—only tens of nanometers in height—requiring a highly sensitive detection system. The DHI system they developed uses a laser to illuminate neural tissue, capturing the scattered light on a high-resolution camera. This process generates a detailed, phase-sensitive image of the tissue, allowing researchers to detect precise changes in tissue movement.
Through years of rigorous testing, the team confirmed that the signal detected by the DHI system correlated with actual neural firing. However, the process of isolating this neural signal was complicated by interference from other physiological factors, such as blood flow, heart rate, and respiratory movement. These sources of noise added complexity to the detection process, making the neural signal harder to distinguish.
David Blodgett, the principal investigator of the study and a chief scientist at APL, described the situation as akin to a remote sensing problem: the team had to detect a faint neural signal amidst the “clutter” of physiological noise. To address this challenge, the research brought together a wide range of technical expertise, including biomedical imaging, acoustic processing, neuroscience, and software development, in a multidisciplinary effort. Collaborating closely with Johns Hopkins Medicine, the team refined their techniques to minimize noise interference, eventually succeeding in identifying the neural signal.
Interestingly, while striving to suppress the physiological “clutter,” the researchers discovered that this data could also provide valuable insights into a person’s health. For instance, they realized that the DHI system was capable of noninvasively measuring intracranial pressure—a vital health metric that traditionally requires drilling into the skull. This capability opens up new applications for the technology, including monitoring brain health in critical care situations, such as assessing the effectiveness of treatment for traumatic brain injuries without the need for invasive procedures.
Austen Lefebvre, an assistant professor of neurology at Johns Hopkins University and co-author of the study, emphasized the clinical potential of noninvasive monitoring of brain health. The ability to observe brain function and detect health indicators through the skull could have significant implications for patient care, allowing doctors to assess neurological conditions in real-time without surgical risks.
The research team’s work has broader implications for neuroscience as well. According to Wolmetz, the findings demonstrate that digital holographic imaging could become a powerful noninvasive tool for recording brain function with high resolution. This method could enhance the study of brain dynamics, supporting both basic neuroscience research and clinical applications. The next step involves validating the technology’s use in human studies, which would mark a significant milestone in noninvasive BCI development.
Looking forward, the researchers are focused on refining the DHI system and exploring how it can be adapted for a wide range of applications. They are particularly interested in testing the technology’s ability to track more complex neural phenomena, including monitoring cognitive states, attention, and other brain activities in real-world environments. This capability could pave the way for noninvasive BCIs that are practical for everyday use, making it possible for individuals to control devices, communicate, and perform tasks through thought alone.
The potential applications of this research extend beyond assistive technologies for individuals with disabilities. The same techniques could eventually lead to more immersive virtual reality experiences, advanced human-machine interfaces, and even new tools for studying and treating neurological disorders. By advancing the understanding of how to capture and interpret neural signals noninvasively, the team’s work could accelerate the development of BCIs that are safe, effective, and accessible to a much larger audience.
The field of brain-computer interfacing is still in its infancy, but this research from Johns Hopkins suggests that significant progress is on the horizon. With continued exploration and technological refinement, noninvasive BCI systems may soon offer capabilities that rival their invasive counterparts, providing new ways to enhance human-machine interactions and improve quality of life for people with neurological conditions.
Source: Johns Hopkins University