Dr. Bernat received his Ph.D. in Clinical Psychology from the University of Michigan, where he also completed an APA-accredited internship and postdoctoral 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.

Areas of Interest

  • Emotion, Cognition
  • Health Disparities
  • Psychopathology
  • Substance Use
  • Criminal Behavior

Doctoral Programs

  • Clinical
  • Cognitive and Neural Systems (CNS)

Degrees

  • PhD
    Clinical Psychology, University of Michigan
  • MA
    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.

Currently funded work includes a focus on cue-processing among substance use among lower SES minority individuals in residential drug treatment. Broadly, projects there focus on brain mechanisms underlying substance use and psychopathology, and change in these mechanisms during treatment. For example, one thread focuses on changes in drug cue reactivity during the initial period of abstinence (referred to as cue-incubation), and how this can index vulnerability to relapse. Emerging transdiagnostic (dimensional) models of psychopathology play a prominent role in the inferences involved in this work. The most common model involves three primary factors: 1) impulse control (externalizing) problems such as substance dependence and antisocial behavior, 2) internalizing problems involving anxiety and depression, and 3) the shared variance between internalizing and externalizing (referred to as a psychopathology factor; p-factor). This parsimonious 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.

Health disparities are an important focus of current projects, for example, assessing how substance use and psychopathology are modulated by individual and contextual risk and protective factors (particularly relative to minority populations, e.g. experiences of discrimination). We are currently assessing these questions across different types data, including self-report, interview, physiological, behavioral, and epidemiological.

A longstanding methodological focus in the EEG/ERP work is based on advanced time-frequency decomposition techniques. This includes amplitude measures that can delineate active brain regions and phase-based functional connectivity measures to characterize dynamic communication between brain regions. Current methodological development efforts focus on characterizing event-related functional connectivity, dynamically as it unfolds in functional networks. This includes network characterization within frequency bands, as well as cross-frequency coupling (CFC; including phase-amplitude and amplitude-amplitude coupling). 

  • International
    Associate Editor, International Journal of Psychophysiology

Current Students

Edward Bernat
BPS 3123E
Department of Psychology
Email
ebernat [at] umd.edu