David Schnyer, Ph.D.

Department of Psychology

University of Texas at Austin

Throughout my career, my research has been focused on understanding the brain basis of mental states. Having been trained under the first set of McDonald Pew Center for Cognitive Neuroscience Graduate Fellowships, I have always engaged a multidimensional approach in my research - testing well founded cognitive theories using multiple and complimentary research methodologies including: (a) task dissociations in a broad array of human populations - neurologically damaged patients, individuals in different stages of lifespan development, individuals in altered mental states and healthy controls, (b) human electro and magneto encephalographic recordings (EEG and MEG), (c) functional and structural Magnetic Resonance Imaging (MRI), and (d) the multimodal integration of fMRI and EEG/MEG. While I started my research narrowly focused on memory and memory disorders, my work has moved more steadily towards exploring individual differences in cognitive control due to genetics, risk factors for mental illness, aging and neurological injury.  You can find my website here.


Cognitive and Attentional Control

While the term cognitive control encompasses a broad range of human abilities, a significant portion of what constitutes cognitive control is attentional control. We can influence how we process and interact with the environment around us by what we attend to, including how effectively we can engage and disengage our focus. Currently, the most exciting experimental work in the domain of attention control is focused on the neurocognitive systems associated with attention control. Attentional control has been shown to play a major role in the vulnerability to and maintenance of mental illness and has been a focus of the NIMH RDoc framework as applied to mental disorders. Moreover, there are individual difference factors that have been shown to influence attentional control, such as genetics, sleep/circadian rhythms and structural and functional brain characteristics. These findings have led to exploring the use of behavioral, eye-tracking and real-time fMRI in a closed-loop neurofeedback approach. The purpose is to develop a training that can help improve attention control and the symptoms associated with its dysfunction.


Since its inception in 2009, I have been actively involved as site PI with a multidisciplinary team on the national TRACK-TBI study. TRACK-TBI is focused on determining sensitive biomarkers of severity of TBI injury and recovery and aims to create an extensive database of 3000 patients. The study is currently funded by NINDS, DOD, and One Mind along with contributions from multiple companies in the biomedical industry. As a member of the Neuroimaging Core (https://tracktbi.ucsf.edu/neuroimaging-core), I’ve contributed to the planning, collection and analysis of neuroimaging data collected at 2 timepoints, 3 and 6-months post injury. This work includes developing metrics of cross site comparison/quality control (American Journal of Neuroradiology, 2016) using both material and a human phantom. When completed, the TRACK-TBI study will have the largest database available of high quality neuroimaging data from well characterized patients who have experienced traumatic brain injury. We have already published data from the first phase of the study showing that MRI Improves 3-Month outcome prediction in mild traumatic brain injury (Annals of Neurology year???) over standard of care CT scans. Data has been published on DTI imaging (Journal of Neurotrauma, 2014) and resting-state functional MRI (Journal of Neurotrauma, 2017). Last year, UT Austin was the first site to begin collection of a new multishell diffusion acquisition sequence, which will result in the use of advanced neuroimaging methods that have not been used in this context before. 

In a separate study, we are testing a point-of-injury EEG based assessment tool for sports related concussion. This project is funded by the DOD and the company BrainScope developed the device. I am a member of the Neuroimaging Core for this project as well and we have begun discussing analysis of high quality structural, diffusion and resting-state MRI in a unique dataset of 240 concussed student athletes.  

Circadian Rhythms, Sleep, Cognition and Emotional Regulation

 Given the importance of cognitive control in daily functioning, we have spent time examining the influence of sleep/wake circadian rhythm patterns on cognitive functioning. This has been done using sleep deprivation paradigms (Sleep, 2009, Military Psychology, 2009), field tracking in college students (Sleep Medicine, 2013; Clinical Neurophysiology, 2015) and in aging (Neuropsychologia, 2015). Given the prevalence of portable biosensors (activity bands, smartphones, etc) to monitor health-related physiology in real-world settings, we are focused on understanding the extent to which subtle changes in daily patterns may be an early biomarker of emotional distress, disease or cognitive decline. As an interesting side collaboration related to field tracking of sleep/activity patterns, I have been working with scientists in engineering some of the next generation of biosensors. In particular, these include tattoo like sensors that have shown the ability to acquire high quality bioelectrical signals across multiple days of recording (Advanced Materials, 2015).