Brain-computer interfaces (BCIs) have made remarkable progress restoring movement and speech in people with paralysis. While brain-computer interface technology thus far has largely focused on decoding motor function, the disorders responsible for the greatest global burden of brain disease—including depression, anxiety, post-traumatic stress disorder, and obsessive-compulsive disorder—are fundamentally disorders of cognition: how we attend, remember, decide, and regulate emotion. As researchers seek to expand the clinical potential of BCIs, a new review argues that treating cognitive disorders will require fundamentally different approaches than the current BCI motor applications.
In a perspective published in Trends in Cognitive Sciences, Ignacio Saez, PhD, Director of the Laboratory for Human Neurophysiology at the Icahn School of Medicine at Mount Sinai, outlines a roadmap for developing next-generation "cognitive brain-computer interfaces." He explains that decoding thought is vastly different from decoding movement. While movement is represented in a compact, stable, well-mapped patch of brain, cognition is not. Brain activity underlying attention, memory, and emotion is spread across many regions, within networks that reorganize from moment to moment; thus the same brain signal can mean different things in different contexts. Recognizing these differences is what will allow scientists and engineers to borrow and adapt the right tools from motor BCI for this new cognitive application.
"Brain-computer interfaces have made extraordinary progress restoring movement and speech and I believe the field is at an inflection point where advances in intracranial recording, decoding, and clinical neuromodulation now make it plausible to build BCIs that target cognitive, rather than motor functions," said Dr. Saez, Associate Professor of Neuroscience, Neurosurgery and Neurology at the Icahn School of Medicine. "This review reframes the next frontier – cognition – as a distinct scientific and engineering challenge that will bring together two approaches that have historically worked more or less separately: BCI research, which has been focused on reading the brain; and clinical neuromodulation, which has focused on stimulating it. Cognitive BCIs will require merging both into a closed-loop system."
These systems must detect dysfunctional brain states as they emerge and respond with precisely timed, adaptive neurostimulation. Dr. Saez describes the scientific advances—and remaining challenges—needed to make this vision a reality. He explains that many of the necessary building blocks—including intracranial brain recording, adaptive neurostimulation, and high-resolution neurochemical sensing—already exist in clinical and research settings. Integrating these technologies into intelligent, closed-loop systems represents the next major challenge for the field and could ultimately enable more precise, personalized treatments for serious brain disorders.
The push toward cognition also comes as commercial interest in brain-computer interfaces intensifies. Companies that have driven much of the recent progress in motor and speech BCIs are increasingly looking to cognitive applications as the field's next frontier, where the addressable patient populations—spanning depression, anxiety, PTSD, and other common psychiatric and neurological conditions—are far larger than those for paralysis. Dr. Saez notes that translating these advances from the laboratory into approved therapies will depend not only on scientific progress but also on close collaboration among academic researchers, clinicians, and industry to build the hardware, algorithms, and regulatory pathways that clinical-grade cognitive BCIs will require.
To learn more about this review, please visit: https://www.sciencedirect.com/science/article/abs/pii/S1364661326001397
