Who We Are
The NPNL at USC is an interdisciplinary lab situated between the Chan Division of Occupational Science and Occupational Therapy, the Division of Biokinesiology and Physical Therapy, the Keck School of Medicine Department of Neurology, and the Neuroscience Graduate Program and affiliated with the USC Mark and Mary Stevens Neuroimaging and Informatics Institute and the USC Brain and Creativity Institute. We are scientists and researchers with varied backgrounds across neuroscience, cognitive science, engineering, computer science, occupational therapy, and physical therapy.
Stroke is one of the leading causes of serious long-term adult disability around the world. Despite intensive physical and occupational therapy, many stroke survivors are unable to independently care for themselves due to persistent motor, cognitive and communicative difficulties. Large variations in lesion damage and individual characteristics (such as age, gender, physical fitness and genetic makeup) make stroke rehabilitation outcomes difficult to predict. Novel methods that predict and maximize each individual’s potential for recovery after stroke are thus desperately needed.
Under the direction of Dr. Sook-Lei Liew, the goals of the Neural Plasticity and Neurorehabilitation Laboratory are:
- to characterize and predict neural plasticity changes in healthy individuals and in individuals after stroke throughout the process of learning or recovery;
- to enhance neural plasticity or neural recovery in individuals using noninvasive brain stimulation, brain-computer interfaces, virtual reality, behavioral measures and novel learning paradigms; and
- to personalize the use of plasticity-inducing paradigms in order to capitalize on each individual’s unique learning or recovery potential.
These goals support the overall mission of the laboratory, which is to enhance neural plasticity in a wide population of individuals in order to improve their quality of life and engagement in meaningful activities.
Ongoing Research Projects
ENIGMA Stroke Recovery
ENIGMA Stroke Recovery: The ENIGMA Stroke Recovery working group is using a ‘big data’ neuroimaging approach to better understand how changes the brain relate to motor recovery after stroke. We are analyzing thousands of brain MRIs of individuals after stroke collected from around the world. Combining large amounts of data from sites worldwide gives us a better ability to find reliable patterns of brain changes that are related to recovery. The long-term goal is to use these patterns we uncover to predict and prescribe personalized treatments for individuals after stroke. Funded by the National Institutes of Health/National Center for Medical Rehabilitation Research K12 and K01. For more information or to participate, please contact NPNL or visit the ENIGMA Stroke Recovery Website.
Based on our work in ENIGMA Stroke Recovery, we believe that bringing together data from researchers worldwide will be much more effective if we are collecting similar measures of recovery and function. We developed SCORE (Stroke Comprehensive Outcomes for Rehabilitation Excellence) to provide short, medium, and long batteries of tests that we plan to use in prospective data collection, and invite other researchers to join us. More information can be found on our resources page.
Analyzing brain MRIs of people after stroke takes a lot of time and work, in part because we have to map out the brain damage (aka, lesions), which can be a different size, shape, and location for each person. Usually we do this by hand, but a single MRI lesion can take hours. We, along with other research groups, are working on developing computer algorithms to do this automatically, but the algorithms need a lot of examples of properly traced lesions to work. We developed ATLAS (Anatomical Tracings of Lesions After Stroke), which is a large database of about 315 manually traced lesions, to share with the research community. Researchers will be able to download and use ATLAS to test and train their own algorithms and build better, faster ways to analyze post-stroke brains. Funded by the NIH-funded Center for Large Data Research and Data Sharing in Rehabilitation. Link to ATLAS data archive forthcoming.
Motor Learning in Virtual Reality
Virtual reality technology, such as the Oculus Rift, has recently become commercially affordable and available, and could be an engaging, immersive tool for motor rehabilitation after stroke. Our lab is studying how people learn in virtual reality and how that compares to learning in the real world. We are also studying ways to use virtual reality to help people transfer skills they learn in the clinic to their home environments. Read one of our recently published studies: Anglin, J. M., Sugiyama, T., & Liew, S. L. (2017). Visuomotor adaptation in head-mounted virtual reality versus conventional training. Scientific Reports, 7. For more information or to participate in our ongoing studies, please contact NPNL.
Virtual reality also gives people an opportunity to have a virtual body that’s different from their real body. Studies have shown that if we’re given a body with extra long arms in virtual reality, we act as though we really have long arms in the real world, and if we’re given a child’s body in virtual reality, we show more child-like behaviors. In our project called REINVENT (Rehabilitation Environment using the Integration of Neuromuscular-based Virtual Enhancements for Neural Training), we are trying to give people who have difficulty moving their arm after stroke a healthy body in virtual reality. Their healthy body in VR is controlled using their own brain and muscle activity, so that when their brain tells their arm to move, we take that signal and make their virtual arm move. This project is funded by the American Heart Association, and partners with the Front Porch Center for Innovation and Well-Being, Rancho Los Amigos, and the USC Institute for Creative Technologies Mixed Reality Lab. Read more about REINVENT: Spicer, R., Anglin, J., Krum, D. M., & Liew, S. L. (2017, March). REINVENT: A low-cost, virtual reality brain-computer interface for severe stroke upper limb motor recovery. In Virtual Reality (VR), 2017 IEEE (pp. 385-386). IEEE.
Transcranial direct current stimulation (tDCS) is a promising way to modulate someone’s brain activity and make regions of the brain more or less excited. tDCS has shown promise in helping people recover motor function after stroke by increasing activity in the damaged brain. However, the stimulation seems to have effects not just in the part of the brain we’re stimulating, but across the whole brain, which produces a lot of variable results for patients. The goal of TICNET (tDCS-Induced Changes in the Motor Network) is to map out the effects of regional tDCS on the whole brain by measuring whole brain activity during tDCS (e.g., using fMRI with tDCS at the same time). The long-term goal of TICNET is to better understand brain network changes after local tDCS so we can make better and more specific tDCS treatments for patients after stroke. Read our recent review paper about tDCS for motor recovery: Lefebvre, S., & Liew, S. L. (2017). Anatomical Parameters of tDCS to Modulate the Motor System after Stroke: A Review. Frontiers in Neurology, 8.