Brain-Spine Interface Shows Promise for Restoring Movement After Spinal Cord Injury
Researchers at Washington University in St. Louis have developed a non-invasive “decoder” that can predict a person’s intention to move their leg, even when they aren’t physically moving it. This breakthrough offers a potential pathway to restoring movement in individuals with spinal cord injuries.
the research, published April 25, 2025, in the Journal of Neuro Engineering and Rehabilitation, focuses on re-establishing interaction between the brain and spinal cord after injury. Spinal cord injuries disrupt this communication, leading to paralysis, despite the brain and spinal cord below the injury remaining functional.
Led by Ismael Seáñez, assistant professor of biomedical engineering and neurosurgery at WashU, the team used electroencephalography (EEG) – a non-invasive technique using a cap with electrodes to measure brain activity – to study 17 volunteers without spinal cord injuries. Participants were asked to physically extend their leg and then to imagine extending their leg while keeping it still.
The researchers then fed this brain activity data into an algorithm, or decoder, allowing it to learn the neural patterns associated with both actual and imagined movement. Surprisingly, the brain activity for both was remarkably similar.
“After we give the decoder this data, it learns to predict based on neural activity whenever there is movement or no movement,” explained Seáñez. “We show that we can predict whenever someone is thinking about moving their leg, even if their leg does not actually move.”
Crucially, the team implemented controls to ensure the signals detected were truly from imagined movement, and not residual muscle activity. This is especially crucial for future applications with patients who cannot physically move their legs.the ability to use imagined movement to “train” the decoder is a significant step forward.
This proof-of-concept study demonstrates the potential for a non-invasive brain-spine interface. The decoder’s predictions could be used to trigger transcutaneous spinal cord stimulation - non-invasive electrical pulses – to reinforce voluntary movement and aid in rehabilitation.
The team is now investigating whether a single, “universal” decoder trained on data from multiple participants can perform as effectively as a personalized decoder, which would simplify clinical request.
This research was funded by the McDonnell Center for systems Neuroscience at Washington University in St. Louis; the National Institutes of Health (K12-HD073945, K01-NS127936; R01-EB026439; P41-EB018783); the Department of Biomedical Engineering in McKelvey Engineering at washu; and the Department of Neurosurgery at washu Medicine.