Brain-Spinal Cord Stimulation Decoder
- A new brain-spine interface decoder developed at Washington University in St.
- Ismael Seáñez, assistant professor of biomedical engineering and neurosurgery at WashU, led the research team, including doctoral student Carolyn Atkinson.
- The findings, which focus on brain-spine interface, were published April 25, 2025, in the Journal of Neuro Engineering and Rehabilitation.
WashU researchers achieved a notable breakthrough, developing a brain-spine interface decoder, a potential game-changer for spinal cord injury rehabilitation. This cutting-edge technology leverages noninvasive stimulation to cue leg movement, offering a new avenue to restore communication between the brain and spinal cord. The primary_keyword “decoder” analyzes brain activity to predict movement intention, even when the leg doesn’t move, possibly aiding patients who cannot physically move. The secondary_keyword ”spinal cord injury” treatment could be revolutionized thanks to this innovative approach. Through the use of EEG, the decoder identifies neural strategies used in imagined movements, boosting the possibility of using the decoder when helping paralyzed patients. News Directory 3 is excited about the potential of this research. Discover what’s next in this groundbreaking research.
Brain-Spine Interface Decoder Shows Promise for Spinal Cord Injury Rehabilitation
Updated June 22, 2025
A new brain-spine interface decoder developed at Washington University in St. Louis offers a potential breakthrough for individuals with spinal cord injuries. The technology aims to re-establish communication between the brain and spinal circuits below the injury site, potentially restoring movement. Paralysis occurs when this communication is disrupted.
Ismael Seáñez, assistant professor of biomedical engineering and neurosurgery at WashU, led the research team, including doctoral student Carolyn Atkinson. They created a decoder that uses transcutaneous spinal cord stimulation – noninvasive, external electrical pulses - to cue lower leg movement. The study involved 17 participants without spinal cord injuries.
The findings, which focus on brain-spine interface, were published April 25, 2025, in the Journal of Neuro Engineering and Rehabilitation.
The researchers used a cap equipped with noninvasive electrodes to measure brain activity via electroencephalography (EEG).Volunteers were asked to extend their leg at the knee and then to imagine doing so while keeping the leg still. This allowed the team to record brain waves during both actual and imagined movements.
This neural activity data was fed into the decoder, an algorithm designed to learn how brain waves behave in each scenario. The team discovered that actual and imagined movements employed similar neural strategies, which is key to brain-spine interface progress.
“After we give the decoder this data, it learns to predict based on neural activity whenever there is movement or no movement,” Seáñez said. “We show that we can predict whenever someone is thinking about moving their leg, even if their leg does not actually move.”
Controls were implemented to confirm that volunteers were genuinely imagining movement and not subtly moving their leg, which could introduce signal noise.
“Whenever people move, this can introduce signal noise, and we want to make sure that the signal noise is not what we’re learning to predict,” Seáñez said. “It’s movement intention or brain activity that we want to predict, so we have people imagine that they’re extending their leg and use the same algorithm that has been trained on people moving to predict whether they were imagining or not.”
Seáñez emphasized the significance of this finding. First, it reinforces that the decoder is interpreting movement intention rather than artifacts or noise. Second, it suggests that the decoder can be trained using imagined movements in individuals with spinal cord injuries who cannot physically move their legs.
Seáñez described the study as a proof-of-concept, marking an initial step toward a noninvasive brain-spine interface.The goal is to use real-time predictions to deliver transcutaneous spinal cord stimulation, reinforcing voluntary movement in a single joint during rehabilitation for patients with spinal cord injuries. This could revolutionize spinal cord injury treatment.
What’s next
The team plans to test a generalized decoder trained on data from all participants to determine if a global decoder can perform as well as a personalized one, which would simplify its use in clinical settings.