A U.S. Department of Defense grant has allowed The University of Texas at San Antonio (UTSA) to acquire two high-performance electroencephalogram (EEG) systems in aid of advancing research and education in the area of brain-machine interaction (BMI) .
Understanding how the human brain functions and how this knowledge can benefit society is both a UTSA and a national research priority, the school says in a release. BMI, also known as brain-computer interface (BCI), is a field focused on assisting, augmenting, or repairing human cognitive or sensory-motor functions.
The new equipment, housed in the BMI Lab in the UTSA College of Engineering’s Applied Engineering and Technology Building, will enable several highly interdisciplinary research and educational projects in BMI and brain research led by six professors from five departments across UTSA.
Dr. Yufei Huang, UTSA professor of electrical and computer engineering and principal investigator of this grant, recognized the university-wide need for high-performance EEG systems, which are state-of-the-art, non-invasive devices for measuring brainwaves in real time in both laboratory and real-life environments. Very few universities across the country have equipment of this quality.
“UTSA already has a strong presence in neuroscience research and education,” says Dr. Huang n a UTSA release. “This new EEG technology will significantly enhance our scholarly contributions to advancing new knowledge in brain research. Our long-term vision is to develop a top-tier research and education center on brain-machine interaction at UTSA.”
The new EEG systems will support the following projects at UTSA:
Dr. Huang and computer science professor Dr. Kay A. Robbins will use the EEG equipment to develop and implement a computational system to monitor brain activities in realistic, event-rich environments. This research is part of the Cognitional and Neuroergonomics Collaborative Technology Alliance (CANCTA), a multi-institution collaboration funded by the U.S. Army Research Laboratory (ARL).
The ARL notes that collaboration between industry, academia and the government is a key element of the alliance concept as each member brings with it a distinctly different approach to research. Academia is known for its cutting-edge innovation; the industrial partners are able to leverage existing research results for transition and to deal with technology bottlenecks; the Army Research Laboratory’s researchers keep the program oriented toward solving complex Army technology problems.
Thus, multidisciplinary research teams are generating the complex technology needed to solve the Army’s complex problems. This approach enables an Alliance to bring together world class research and development talent and focus it on Army-specific technology objectives for application to Army needs.
ARL has a history of successful collaborations bringing together the triad of industry, academia, and government, dating back to the 1990s. There are currently four active CTAs: Micro Autonomous Systems and Technology (MAST) was awarded in 2008; Network Science (NS) CTA was awarded in 2009; and in 2010, the Robotics CTA and Cognition and Neuroergonomics (CAN) CTA were each awarded. In 2012, two Collaborative Research Alliances (CRA) were awarded: Electronic Materials, and Materials in Extreme Dynamic Environments. Soon to be announced will be the award of a Collaborative Research Alliance in the area of Cyber Security.
Dr. Robbins also will use the new EEG equipment at UTSA to capture data from the brain during attention and learning tasks in order to build a database that will help researchers see patterns in brain activity. This project also is part of CANCTA, funded by ARL.
Dr. Robbins’s research focuses on modeling, visualization, analysis, and management of multimedia data sets in three major application areas: neuroinformatics, bioinformatics, and medical informatics. Her group is currently developing algorithms and tools for automated annotation and retrieval of EEG and other signals based on content, as well as tools to detect enrichment of co-occurrences of events and signal patterns.
Electrical and computer engineering professor and chair Daniel Pack and Dr. Huang will use the equipment to design and implement a BMI system that uses brain signals generated by a soldier to navigate small unmanned aerial vehicles for military operations such as collecting intelligence, performing surveillance and conducting reconnaissance missions. This project is also funded by the ARL.
Kinesiology associate professor Wan Xiang Yao will use the equipment to examine the neuromechanisms underlying the transfer of learning from one side of the body to another and metal imagery practice, which will be helpful for patients relearning motor skills lost due to traumatic brain injury or disease, such as a stroke.
Biology assistant professor Nicole Wicha will use the equipment to determine the neurodevelopmental trajectory for arithmetic fact learning in bilingual children.
Dr. Wicha’s website says her research focuses on understanding how the brain processes language in real time using both behavioral and brain imaging techniques, in particular event-related brain potentials (ERPs), which is a non-invasive direct measure of electrical brain activity with excellent precision in the time domain. She has used these techniques to study the brain processes underlying language comprehension, such as the predictive nature of sentence comprehension in the monolingual and bilingual brains, and when and how different sources of linguistic information (e.g., grammar and word meaning) affect our ability to understand an utterance. Dr. Wicha’s findings indicate that the brain processes responsible for different linguistic operations interact over time. Moreover, the brain uses predictive processes to rapidly anticipate upcoming information and facilitate comprehension.
Currently a primary focus in Dr. Wicha’s lab is in understanding the unique processing capabilities of the bilingual brain. She is funded by the National Institute of Child Health and Human Development and the National Institute of General Medicine Sciences to pursue research on how the bilingual brain predicts and processes two languages simultaneously, such as when reading a sentence that contains language switches, or conversely how bilinguals manage to process one language without interference from the other, as in the bilingual color-word Stroop paradigm.
Mechanical and biomedical engineering professor Yusheng Feng will use the equipment to develop a real-time feedback tutoring algorithm to monitor students’ brain activity when they are studying science, technology, engineering and mathematics. He also will use the algorithm to provide students with learning disabilities feedback to improve their study habits by providing vivid encouraging visualization cues.
More than two-dozen UTSA faculty members and their graduate and undergraduate students are actively involved in brain research and education, many of whom are affiliated with the UTSA Neurosciences Institute, a multidisciplinary research organization for integrated brain studies.
University of Texas at San Antonio (UTSA)
U.S. Army Research Laboratory (ARL)
University of Texas at San Antonio (UTSA)
Deborah Silliman Wolfe