TDLC researchers present at the 2013 International Brain-Computer Interface (BCI) Conference
TDLC's Scott Makeig, Tim Mullen, Leanne Chukoskie, and Virginia de Sa (among others) recently attended the 2013 International Brain-Computer Interface (BCI) Conference, held on June 3-7, 2013, in Pacific Grove, CA. They were part of a group of scientists who convene annually to discuss scientific advances in the field of BCI. TDLC's Tim Mullen won Poster Prize for Technical Merit for his poster, "Real-Time Estimation and 3D Visualization of Source Dynamics and Connectivity Using Wearable EEG".
The Brain Computer Interface (BCI) is a technology that links thoughts, commands and emotions from the brain to computers, using EEG. With BCI, a computer reads brain activity and sends signals to an external device like a wheelchair or robot to execute an action. While researchers are using the BCI to create exciting gadgets like mind-dialed cell phones and a cap to alert nodding-off air traffic controllers, the new technology could also have a big effect on medicine. Several TDLC researchers shared their BCI research at the International BCI Conference.
BCI for Autism Spectrum Disorders (ASD)
Scott Makeig and Leanne Chukoskie were among the presenters in a special workshop on "BCI for Autism Spectrum Disorders (ASD)", organized by Disha Gupta from the Wadsworth Center in Albany, NY.
The first aim of the workshop was to familiarize the BCI community with ASD and especially the challenges those living with ASD face on a daily basis. Jonathan Tarbox of the Center for Autism and Related Disorders (CARD) kicked off the workshop by presenting the basics of ASD, including current therapeutic options and the incredible heterogeneity of the ASD community in terms of needs and outcomes. The second goal of the workshop was to discuss how, given the current state of BCI research, the tools and methods of this community could be directed toward addressing the challenges of those living with autism.
Scott Makeig presented a big picture view of EEG research and the need for creating tools to permit the analysis and comparison of data from large numbers of people. Archiving and sharing presents a great challenge for EEG data that are collected by different systems using different tasks in individuals with quite different skills and abilities. Yet, this is exactly what is needed in order to study the diversity of presentations of neurodevelopmental disorders that include ASD. The National Database for Autism Research (NDAR) demands that all federally funded autism research results are deposited in the database to make them available to other researchers, including EEG data. Together with colleagues at the Swartz Center for Computational Neuroscience, Dr. Makeig is leading the effort to create a standard format for sharing EEG data that is immune to differences in collection protocols.
Leanne Chukoskie, along with her INC colleague, Marissa Westerfield, discussed areas of autism research that could best benefit from BCI methods now and also areas where measuring and supporting behavioral methods might be currently more productive. Current estimates suggest that as many as 25% of individuals diagnosed with autism are minimally verbal. They cannot communicate their needs and wants vocally and so it is difficult to know what they are feeling or where to begin with interventions to best support their needs. EEG technology has allowed some researchers, including TDLC's April Benasich, to evaluate comprehension of words and phrases without the need for spoken language. These methods could help by telling us what someone understands, even if he cannot speak. That would be tremendously helpful for tailoring appropriate therapies that are neither too simple nor two complex for an individual's level of comprehension.
However, although EEG methods offer great promise and we must continue basic research to advance our learning, some interventions are currently best at the behavioral level. Eye and body movements, for example, are readily measurable and can be used in game-style interventions. The advantage goes beyond accessibility. By providing precise feedback through games on behaviors, like eye and body movements, that people engage in every day, there is a greater chance that the effects of the intervention will be lasting. Drs. Chukoskie and Westerfield along with Jeanne Townsend, the director of the Research in Autism and Development lab, are developing these sorts of interventions with the hope that they will be beneficial to many individuals on the autism spectrum.
This workshop offered a first step toward what will hopefully be a productive long-term relationship between the community that researches ASD and the community that researches BCI.
Using BCI to Help Parkinson's Disease Patients
TDLC investigators Priya Velu (graduate student, Medical Scientist Training Program), Virginia de Sa (Department of Cognitive Science) and Howard Poizner, at the Institute for Neural Computation (INC), hope to use BCI technology to help Parkinson's disease patients walk. Parkinson's patients are known to heavily rely on external visual or auditory cues in order to guide their movement. They may be unable to initiate a movement, but if they are given chalk marks on the floor, they can see where to place their feet and they can begin to move. Visual cues can also be presented with virtual and augmented reality apparatus. With collaborator Yoram Baram, the team is using a system that projects moving visual targets as a person walks. With Cognitive Science graduate student Tim Mullen, they are looking at the real-time effect of visual cues on brain activity. TDLC trainees Eunho Noh and Matthew Valdivia (former REU trainee) are helping with data analysis and collection.
The team hopes to use the BCI to read Parkinson's patients' motor cortex thoughts, to determine how they want to move and in what direction, detect whether patients are about to have a gait freezing episode, and then present visual and/or auditory cues that would help them overcome that freezing of gait. Using EEG, they also hope to learn more about how visual cues decrease the number of freezing episodes. The ultimate goal is to develop a portable EEG device that would help prevent their legs from freezing in the first place. Sensors could be embedded in a baseball cap or a headband, and virtual reality glasses would display visual images to guide the patient. Emerging technology could help retrain the brain.
BCI Research at SCCN and INC
Three teams of researchers at UC San Diego -- Scott Makeig and Tzyy-Ping Jung at the Swartz Center for Computational Neuroscience (SCCN), Howard Poizner and Virginia deSa, at INC -- were highlighted in a UCSD TV Series video that describes how they are pioneering this new field. Click here to view the video of this research.