
Muhammad Parvaz, PhD
Muhammad Adeel Parvaz (Preferred Name)
About Me
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).
Language
English
Position
ASSOCIATE PROFESSOR | Psychiatry, ASSOCIATE PROFESSOR | Neuroscience, ASSOCIATE PROFESSOR | Artificial Intelligence and Human Health
Research Topics
Addiction, Biomedical Sciences, Cognitive Neuroscience, MRI, Neurobiology, Neuromodulation, Neurophysiology, Neuroscience, Prefrontal Cortex, Psychiatry, Schizophrenia, Systems Neuroscience
Multi-Disciplinary Training Areas
Artificial Intelligence and Emerging Technologies in Medicine [AIET], Neuroscience [NEU]
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PhD, Stony Brook University
Publications
Selected Publications
- The electroencephalography protocol for the Accelerating Medicines Partnership® Schizophrenia Program: Reliability and stability of measures. Daniel H. Mathalon, Spero Nicholas, Brian J. Roach, Tashrif Billah, Suzie Lavoie, Thomas Whitford, Holly K. Hamilton, Lauren Addamo, Andrey Anohkin, Tristan Bekinschtein, Aysenil Belger, Kate Buccilli, John Cahill, Ricardo E. Carrión, Stefano Damiani, Ilvana Dzafic, Bjørn H. Ebdrup, Igor Izyurov, Johanna Jarcho, Raoul Jenni, Anna Jo, Sarah Kerins, Clarice Lee, Elizabeth A. Martin, Rocio Mayol-Troncoso, Margaret A. Niznikiewicz, Muhammad Parvaz, Oliver Pogarell, Julio Prieto-Montalvo, Rachel Rabin, David R. Roalf, Jack Rogers, Dean F. Salisbury, Riaz Shaik, Stewart Shankman, Michael C. Stevens, Yi Nam Suen, Nicole C. Swann, Xiaochen Tang, Judy L. Thompson, Ivy Tso, Julian Wenzel, Juan Helen Zhou, Jean Addington, Luis Alameda, Celso Arango, Nicholas J.K. Breitborde, Matthew R. Broome, Cheryl M. Corcoran, Rene S. Kahn. Schizophrenia
- Speak and You Shall Predict: Evidence That Speech at Initial Cocaine Abstinence Is a Biomarker of Long-Term Drug Use Behavior. Carla Agurto, Guillermo A. Cecchi, Sarah King, Elif K. Eyigoz, Muhammad A. Parvaz, Nelly Alia-Klein, Rita Z. Goldstein. Biological Psychiatry
- Methamphetamine-related working memory difficulties underpinned by reduced frontoparietal responses. Robert J. Roy, Muhammad A. Parvaz, Ken T. Wakabayashi, Robert J.R. Blair, Nicholas A. Hubbard. Addiction Biology