Edward Bernat

Assistant Professor

Dr. Bernat received his Ph.D. in Clinical Psychology from the University of Michigan, where he also completed an APA-accredited internship and post-doctoral work in Biomedical Engineering. He subsequently served as a Research Associate in Clinical Psychology at the University of Minnesota and then core faculty in Clinical Psychology at Florida State University. Dr. Bernat joined the Psychology faculty at the University of Maryland-College Park in 2013.

CV: My CV
Degrees
  • PhD Clinical Psychology, University of Michigan

Dr. Bernat’s research focuses on brain mechanisms that underlie individual differences in cognitive and affective processing.  This involves basic science work developing measures for critical mechanisms, and clinical-translational work assessing how these mechanisms relate to psychopathology and individual differences.  Newly funded grants extend this work by investigating how these brain mechanisms change during substance dependence treatment (National Institute on Drug Addiction, NIDA) and anxiety/depression treatment (Department of Defense, DOD). 

Emerging dimensional models of psychopathology play a prominent role in the inferences involved in this work.  The most common model involves two primary factors: 1) impulse control (externalizing) problems such as substance dependence, antisocial behavior, and psychopathy, and 2) internalizing problems involving anxiety and depression.  This parsimonious 2-factor model provides reduced complexity when relating psychopathology to brain mechanisms.  More importantly, however, this offers empirically-based approaches to identifying potential neurobiological factors underlying multiple related or comorbid clinical problems.  Further, identifying such factors will contribute towards both understanding etiology and developing interventions. 

A primary methodological focus is on advanced time-frequency decomposition techniques employed with EEG/MEG data. This includes amplitude measures that can delineate active brain regions and functional connectivity measures to characterize dynamic communication between brain regions. A major current methodological focus is on developing higher resolution time-frequency representations of event-related functional connectivity, dynamically as it unfolds.  To bring better spatial resolution, further integration between these EEG/MEG decomposition approaches and MRI/fMRI neuroimaging data is currently being advanced, including a new simultaneous EEG/fMRI system being developed currently with the Maryland Neuroimaiging Center (MNC).  EEG and MRI neuroimaging modalities are accompanied by a number of other physiological measures (e.g. skin conductance, startle blink, facial muscle, heart rate, eye tracking) which offer critical additional information about affective and cognitive processes.

3123E Biology-Psychology Building
Neuroscience and Cognitive Science
Phone: (301) 405-8374
Email: ebernat@umd.edu