Brain-Computer Interface
Researchers have designed a better decoder to make sense of electric signals from the brain. Their crucial development has the software compensate for the irregular nature of those neural signals. The innovation has led to the creation of a new high-speed typing system for ALS patients.
A new study describes three software innovations that substantially improved the user experience and performance of the BrainGate brain computer interface (BCI). Researchers said the gains are a significant advance in their ongoing work to develop and test a practical BCI assistive technology that people with paralysis could use easily, reliably, independently, and on demand to regain control over external devices.
The work has been published in the journal Science Translational Medicine.
Intracortical BCIs such as BrainGate use a tiny array of implanted electrodes to pick up the electrical activity of neurons in the motor cortex of the brain. Computers then translate those signals into digital commands that have allowed users to control electronic devicessuch as computers and robotic arms by simply intending to move their own arm or hand. The translation relies on a decoder, an algorithm that infers the movement intentions of the user from the patterns of their neural activity.
A challenge of decoding movement intention from intracortical electrodes is that the signals change over time — thus, intracortical BCIs have required frequent interruptions for decoder recalibration. Neural signal patterns can change when the electrodes move even slightly; a neuron whose signal was not previously detected can end up joining the recorded ensemble while another might become excluded. As the neural signals shift and drift, the performance of the BCI — the ability of users to move a cursor or robot by thinking about the move — will decline until the decoder can be recalibrated. This recalibration is typically performed using a special task in which the participant tries to move the cursor to prescribed targets so that movement intentions can be mapped to the new neural activity patterns.
The essential advance in the new study is a set of decoder upgrades that allow the algorithm to recalibrate itself during practical BCI use without making the user stop for calibration task every time the signals change. Results of the research reported in the paper show that the new decoder preserved BCI performance much longer than before and even contributed to improving users’ accurate typing speed on an on-screen keyboard. Rather than frequent pauses for recalibration, users could type for hours, pausing only when they wanted to and without the need for technicians to intervene.
"Eliminating the need to run a calibration task whenever the recorded signals change will make a clinical BCI more user-friendly and easy to use."
“Eliminating the need to run a calibration task whenever the recorded signals change will make a clinical BCI more user-friendly and easy to use,” said lead author Beata Jarosiewicz, assistant professor (research) of neuroscience at Brown University and the Brown Institute for Brain Science, and investigator at the Providence Veterans Affairs Medical Center (PVAMC).The BrainGate team includes scientists, engineers, and clinicians from Brown, Massachusetts General Hospital (MGH), PVAMC, Stanford University, and Case Western Reserve University.
A dramatic demonstration at the Stanford site of the clinical trial, a woman who is diagnosed with amyotrophic lateral sclerosis (ALS), was able to use BrainGate for six sessions of a few hours each over the course of 42 days without any interruptions for explicit recalibration after the decoder was initialized on the first day. She was able to type paragraphs, pausing and unpausing the BCI on her own, while the decoder calibrated itself.
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“Watching our participants use this more robust system to type on a computer screen highlights the progress being made toward a clinically useful system,” said Dr. Leigh Hochberg, professor of engineering at Brown, director of the Center for Neurorestoration and Neurotechnology at PVAMC, director of the Neurotechnology Trials Unit at MGH Neurology, and senior author of the paper.
“There is still a lot of research to do,” Hochberg said. “With continued clinical research, we will learn how our findings extend to more participants. We want to make the system faster, easier, smaller, fully implanted, more portable, less requiring of an expert researcher or caregiver, and more nimble in its ability to provide control of external devices.
“In these studies, we are making steps toward robust and flexible communication systems for people with severely limited movement, including limited or no speech. We are also dedicated not only to enabling control over computers or robotic assistive devices, but — for people with spinal cord injury or stroke — working toward the goal of reconnecting brain to limb, allowing the powerful intracortical signals to activate fully implanted functional electrical stimulation devices, and re-enabling intuitive movement of one’s own arm and hand.”
Hochberg emphasized, “Our extraordinary research participants are true pioneers. They are participating in the trial not because they hope to gain any personal benefit, but because they want to help us to develop and test a system that will help other people with paralysis in the future.”
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