Department of Anesthesia, Pain Management & Perioperative Medicine

Faculty of Medicine

Javeria Hashmi, PhD

Associate Professor

javeria-hashmi
Department of Anesthesia, Pain Management & Perioperative Medicine , Department of Medical Neuroscience , Department of Physics & Atmospheric Science , Department of Psychology and Neuroscience

Email: Javeria.Hashmi@dal.ca
Research Topics:
  • Pain
  • Cognition
  • Brain Development
  • Anesthesia
  • Predictive Analysis
  • fMRI-MEG
  • Graph Theory
  • Machine learning

Education:

  • PhD, University of Toronto
  • Post-doctoral Fellow Northwestern University, Feinberg School of Medicine, Department of Physiology (2010-2013)
  • Post-doctoral Fellow Harvard Medical School/MGH, Department of Neurology, Department of Psychiatry (2013-2015)
  • MSc, University of Western Ontario

Research interests:

Dr. Hashmi is dedicated to understanding the behavioral relevance of large-scale neural communication in the brain. Her lab uses multimodal brain imaging and leading-edge analytical approaches such as graph theory and machine learning for studying physiological functions of brain networks. The focus is on studying sensory and affective pain as a modality to understand how the brain processes information to generate perception.

Related information:

Biography:

Dr. Hashmi is a Canada Research Chair (CRC) Tier II (Pain) nominee who has trained in brain imaging and pain research in top-tier labs at the University of Toronto, Northwestern and Harvard. She investigates the role of network efficiency and neural communication in pain perception, brain development, sex-differences and anesthesia.

Selected publications:

  1. Hashmi, M.A, Hashmi, J.A. (2025).  Chronic Pain and the Limits of AI: Why Expert Knowledge Matters. PAIN. Accepted.
  2. Sunavsky, A, Hashmi, M.A, Robertson, J.W, Veinot, J, Hashmi, J.A. (2025). The nucleus accumbens- prefrontal connectivity as a predictor of chronic low back pain. PAIN. 10, 1097.
  3. Veinot, J, Douglas, C,  Hashmi, J.A. (2025). Low working memory underpins the association between aberrant functional properties of pain modulation circuitry and chronic back pain severity . Journal of PAIN. 104795
  4. Pak, V, Hashmi, J.A. (2023). Top-down threat bias in pain perception is predicted by higher segregation between resting-state networks. Network Neuroscience. 7(4): 1248-1265.
  5. Wang S, Veinot J, Goyal A, Khatibi A, Lazar S.W, Hashmi JA. (2022). Distinct networks of periaqueductal gray columns in pain and threat processing. Neuroimage. 250: 118936.