Muhammad Parvaz

Muhammad Parvaz, PhD

Muhammad Adeel Parvaz (Preferred Name)

  • ASSISTANT PROFESSOR | Psychiatry
  • ASSISTANT PROFESSOR | Neuroscience

Research Topics:

Addiction, Biomedical Sciences, Cognitive Neuroscience, MRI, Neurobiology, Neuromodulation, Neurophysiology, Neuroscience, Prefrontal Cortex, Psychiatry, Schizophrenia, Systems Neuroscience

Dr. Parvaz's primary research interest includes studying cognitive-affective interactions underlying deficits in motivation, reinforcement learning and inhibitory control in mental health disorders, specifically in substance use disorders, using behavioral, computational and neuroimaging techniques. As a cognitive neuroscientist with a background in biomedical engineering, he places special emphasis on understanding disease mechanisms with an eye towards developing clinically useful biomarkers to accelerate bench-to-bedside translation of lab-based assessments. His research involves tracking neurobehavioral plasticity during the onset of as well as remission from substance use disorders. At the clinical translation side of this work, he is developing and testing interventions for craving reduction during behavioral and neuromodulation techniques. In parallel, he is also interested in studying the onset and development of aberrant cognitive-affective interaction in adolescents as well as risk factors that render some youth vulnerable to develop psychopathological phenotypes (e.g., substance use disorder, eating disorders and psychosis). For these studies, his group uses a comprehensive multimodal approach with multiscale modeling of environmental (socio-economic factors), clinical (rating scales), behavioral (cognitive tasks), molecular (MR spectroscopy and blood based inflammatory markers), physiological (EEG) and circuit-level (fMRI) biomarkers to more precisely define the phenotype of interest and to track or predict individualized outcomes (e.g., development of substance use disorders in adolescents and relapse in treatment seeking addicted individuals).

Multi-Disciplinary Training Areas

Artificial Intelligence and Emerging Technologies in Medicine [AIET], Neuroscience [NEU]

Education

PhD, Stony Brook University