Ongoing Research Projects 

TRACK-TBI

Our lab has been part of a multi-site longitudinal study for over a decade. Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) is designed to collect clinical, imaging, genetic, proteomic, and neuropsychological data on traumatic brain injury.). 

Each year in the United States approximately 1.7 million people sustain a TBI and effective treatment has yet to be discovered. Traumatic brain injury is a contributing factor to one-third of injury-related deaths, as well as a contributing factor to long-term physical, cognitive, and psychological disabilities. To this date, there have not been any successful clinical trials or treatments. This failure has been linked to the outdated and blunt TBI classification system.

The goal of TRACK-TBI is to create a large, high quality database that integrates clinical, imaging, proteomic, genomic and outcome biomarkers to improve TBI classification/taxonomy and outcome assessments, identify the health and ecomonic impact of mild TBI patient disposition, and create a legacy database with analytic tools and resources to support TBI research.

Sleep/Activity, Cognition and Mood

The results from the studies of sleep deprivation are providing my lab with an exciting new model for examining global changes in brain function using behavioral studies alongside structural and functional brain imaging methodologies. Sleep deprivation provides a unique model of diffuse brain injury that can be studied within subject in an ABA design. Experimental results have important implications for understanding the brain mechanisms of a host syndromes involving diffuse brain injury, such as: anoxia due to cardiac arrest, traumatic brain injury (TBI) and even changes associated with aging.

More recently, we have extended our SD work to examining the role of sleep/circadian rhythm patterns in naturalistic settings on cognition. An examination of the association between chronic sleep restriction and electrocortical arousal in college students in both young and older adults. These studies combine field-based actigraphy recordings over extended periods of time with behavioral and functional imaging measures, as well as sleep/circadian rhythm-associated genetics. 

The field based recordings have led us to collaborate with individuals in the biomedical engineering and computer science departments here at UT to develop mobile monitoring and intervention applications that utilize real-time sensor data to assess an individual’s cognitive and mood states and push interventions to them through mobile social media platforms.