Summary: New advances in brain computer interface technology allows three people with movement impairments to control a cursor by imagining their hand movements.
In a Stanford-led research report, three participants with movement impairment controlled an onscreen cursor simply by imagining their own hand movements.
A clinical research publication led by Stanford University investigators has demonstrated that a brain-to-computer hookup can enable people with paralysis to type via direct brain control at the highest speeds and accuracy levels reported to date.
The report involved three study participants with severe limb weakness — two from amyotrophic lateral sclerosis, also called Lou Gehrig’s disease, and one from a spinal cord injury. They each had one or two baby-aspirin-sized electrode arrays placed in their brains to record signals from the motor cortex, a region controlling muscle movement. These signals were transmitted to a computer via a cable and translated by algorithms into point-and-click commands guiding a cursor to characters on an onscreen keyboard.
Each participant, after minimal training, mastered the technique sufficiently to outperform the results of any previous test of brain-computer interfaces, or BCIs, for enhancing communication by people with similarly impaired movement. Notably, the study participants achieved these typing rates without the use of automatic word-completion assistance common in electronic keyboarding applications nowadays, which likely would have boosted their performance.
One participant, Dennis Degray of Menlo Park, California, was able to type 39 correct characters per minute, equivalent to about eight words per minute.
‘A major milestone’
This point-and-click approach could be applied to a variety of computing devices, including smartphones and tablets, without substantial modifications, the Stanford researchers said.
“Our study’s success marks a major milestone on the road to improving quality of life for people with paralysis,” said Jaimie Henderson, MD, professor of neurosurgery, who performed two of the three device-implantation procedures at Stanford Hospital. The third took place at Massachusetts General Hospital.
Henderson and Krishna Shenoy, PhD, professor of electrical engineering, are co-senior authors of the study, which was published online Feb. 21 in eLife. The lead authors are former postdoctoral scholar Chethan Pandarinath, PhD, and postdoctoral scholar Paul Nuyujukian, MD, PhD, both of whom spent well over two years working full time on the project at Stanford.
“This study reports the highest speed and accuracy, by a factor of three, over what’s been shown before,” said Shenoy, a Howard Hughes Medical Institute investigator who’s been pursuing BCI development for 15 years and working with Henderson since 2009. “We’re approaching the speed at which you can type text on your cellphone.”
“The performance is really exciting,” said Pandarinath, who now has a joint appointment at Emory University and the Georgia Institute of Technology as an assistant professor of biomedical engineering. “We’re achieving communication rates that many people with arm and hand paralysis would find useful. That’s a critical step for making devices that could be suitable for real-world use.”
Shenoy’s lab pioneered the algorithms used to decode the complex volleys of electrical signals fired by nerve cells in the motor cortex, the brain’s command center for movement, and convert them in real time into actions ordinarily executed by spinal cord and muscles.
“These high-performing BCI algorithms’ use in human clinical trials demonstrates the potential for this class of technology to restore communication to people with paralysis,” said Nuyujukian.
Millions of people with paralysis reside in the United States. Sometimes their paralysis comes gradually, as occurs in ALS. Sometimes it arrives suddenly, as in Degray’s case.
Now 64, Degray became quadriplegic on Oct. 10, 2007, when he fell and sustained a life-changing spinal-cord injury. “I was taking out the trash in the rain,” he said. Holding the garbage in one hand and the recycling in the other, he slipped on the grass and landed on his chin. The impact spared his brain but severely injured his spine, cutting off all communication between his brain and musculature from the head down.
“I’ve got nothing going on below the collarbones,” he said.
Degray received two device implants at Henderson’s hands in August 2016. In several ensuing research sessions, he and the other two study participants, who underwent similar surgeries, were encouraged to attempt or visualize patterns of desired arm, hand and finger movements. Resulting neural signals from the motor cortex were electronically extracted by the embedded recording devices, transmitted to a computer and translated by Shenoy’s algorithms into commands directing a cursor on an onscreen keyboard to participant-specified characters.
The researchers gauged the speeds at which the patients were able to correctly copy phrases and sentences — for example, “The quick brown fox jumped over the lazy dog.” Average rates were 7.8 words per minute for Degray and 6.3 and 2.7 words per minute, respectively, for the other two participants.
A tiny silicon chip
The investigational system used in the study, an intracortical brain-computer interface called the BrainGate Neural Interface System*, represents the newest generation of BCIs. Previous generations picked up signals first via electrical leads placed on the scalp, then by being surgically positioned at the brain’s surface beneath the skull.
An intracortical BCI uses a tiny silicon chip, just over one-sixth of an inch square, from which protrude 100 electrodes that penetrate the brain to about the thickness of a quarter and tap into the electrical activity of individual nerve cells in the motor cortex.
Henderson likened the resulting improved resolution of neural sensing, compared with that of older-generation BCIs, to that of handing out applause meters to individual members of a studio audience rather than just stationing them on the ceiling, “so you can tell just how hard and how fast each person in the audience is clapping.”
Shenoy said the day will come — closer to five than 10 years from now, he predicted —when a self-calibrating, fully implanted wireless system can be used without caregiver assistance, has no cosmetic impact and can be used around the clock.
“I don’t see any insurmountable challenges.” he said. “We know the steps we have to take to get there.”
Degray, who continues to participate actively in the research, knew how to type before his accident but was no expert at it. He described his newly revealed prowess in the language of a video game aficionado.
“This is like one of the coolest video games I’ve ever gotten to play with,” he said. “And I don’t even have to put a quarter in it.”
The study’s results are the culmination of a long-running collaboration between Henderson and Shenoy and a multi-institutional consortium called BrainGate. Leigh Hochberg, MD, PhD, a neurologist and neuroscientist at Massachusetts General Hospital, Brown University and the VA Rehabilitation Research and Development Center for Neurorestoration and Neurotechnology in Providence, Rhode Island, directs the pilot clinical trial of the BrainGate system and is a study co-author.
“This incredible collaboration continues to break new ground in developing powerful, intuitive, flexible neural interfaces that we all hope will one day restore communication, mobility and independence for people with neurologic disease or injury,” said Hochberg.
Stanford research assistant Christine Blabe was also a study co-author, as were BrainGate researchers from Massachusetts General Hospital and Case Western University.
Funding: The study was funded by the National Institutes of Health (grants R01DC014034, R011NS066311, R01DC009899, N01HD53404 and N01HD10018), the Stanford Office of Postdoctoral Affairs, the Craig H. Neilsen Foundation, the Stanford Medical Scientist Training Program, Stanford BioX-NeuroVentures, the Stanford Institute for Neuro-Innovation and Translational Neuroscience, the Stanford Neuroscience Institute, Larry and Pamela Garlick, Samuel and Betsy Reeves, the Howard Hughes Medical Institute, the U.S. Department of Veterans Affairs, the MGH-Dean Institute for Integrated Research on Atrial Fibrillation and Stroke and Massachusetts General Hospital.
Stanford’s Office of Technology Licensing holds intellectual property on the intercortical BCI-related engineering advances made in Shenoy’s lab.
Stanford’s departments of Neurosurgery and of Electrical Engineering also supported the work. Shenoy and Henderson are members of Bio-X and the Stanford Neuroscience Institute.
*CAUTION: Investigational Device. Limited by Federal Law to Investigational Use.
Source: Bruce Goldman – Stanford
Image Source: NeuroscienceNews.com image is adapted from the Stanford video.
Video Source: Video credited to Stanford.
Original Research: Full open access research for “High performance communication by people with paralysis using an intracortical brain-computer interface” by Chethan Pandarinath, Paul Nuyujukian, Christine H Blabe, Brittany L Sorice, Jad Saab, Francis R Willett, Leigh R Hochberg, Krishna V Shenoy, and Jaimie M Henderson in eLife. Published online February 21 2017 doi:10.7554/eLife.18554
High performance communication by people with paralysis using an intracortical brain-computer interface
Brain-computer interfaces (BCIs) have the potential to restore communication for people with tetraplegia and anarthria by translating neural activity into control signals for assistive communication devices. While previous pre-clinical and clinical studies have demonstrated promising proofs-of-concept (Serruya et al., 2002; Simeral et al., 2011; Bacher et al., 2015; Nuyujukian et al., 2015; Aflalo et al., 2015; Gilja et al., 2015; Jarosiewicz et al., 2015; Wolpaw et al., 1998; Hwang et al., 2012; Spüler et al., 2012; Leuthardt et al., 2004; Taylor et al., 2002; Schalk et al., 2008; Moran, 2010; Brunner et al., 2011; Wang et al., 2013; Townsend and Platsko, 2016; Vansteensel et al., 2016; Nuyujukian et al., 2016; Carmena et al., 2003; Musallam et al., 2004; Santhanam et al., 2006; Hochberg et al., 2006; Ganguly et al., 2011; O’Doherty et al., 2011; Gilja et al., 2012), the performance of human clinical BCI systems is not yet high enough to support widespread adoption by people with physical limitations of speech. Here we report a high-performance intracortical BCI (iBCI) for communication, which was tested by three clinical trial participants with paralysis. The system leveraged advances in decoder design developed in prior pre-clinical and clinical studies (Gilja et al., 2015; Kao et al., 2016; Gilja et al., 2012). For all three participants, performance exceeded previous iBCIs (Bacher et al., 2015; Jarosiewicz et al., 2015) as measured by typing rate (by a factor of 1.4–4.2) and information throughput (by a factor of 2.2–4.0). This high level of performance demonstrates the potential utility of iBCIs as powerful assistive communication devices for people with limited motor function.
“High performance communication by people with paralysis using an intracortical brain-computer interface” by Chethan Pandarinath, Paul Nuyujukian, Christine H Blabe, Brittany L Sorice, Jad Saab, Francis R Willett, Leigh R Hochberg, Krishna V Shenoy, and Jaimie M Henderson in eLife. Published online February 21 2017 doi:10.7554/eLife.18554