Stephen Coombes

Associate Professor

My laboratory is focused on sensorimotor processing in the human brain. Following a PhD in motor control, I completed postdoctoral training in human brain imaging. My laboratory has recently published a series of articles that use state-of-the-art neuroimaging measures to identify the brain circuits that integrate pain and motor processes. We have leveraged this information to develop machine learning algorithms that classify pain perception with 90% accuracy in healthy controls. We have also published important papers that use diffusion MRI and probabilistic tractography to identify key white matter tracts that link the sensorimotor cortex with the cerebral peduncle. We have published our work in journals that include Cerebral Cortex, Neuroimage, Human Brain Mapping, Pain, Journal of Neurophysiology, Psychological Science, Clinical Neurophysiology, and Emotion.

Research Interests
Dr. Stephen Coombes’ research focuses on the integration between motor, pain, and emotional processes. He also examines the structure and function of sensorimotor and memory brain circuits in neurodegenerative disorders.
Selected Publications

  • Wang, W.E., Ho, R.L.M., Gatto, B., van der Veen, S.M., Underation, M.K., Thomas, J.S., Antony, A.B., and Coombes, S.A. (2021). Cortical Dynamics of Movement-Evoked Pain in Chronic Low Back Pain. Journal of Physiology. 599(1):289-305
  • Archer, D. B., D. E. Vaillancourt and S. A. Coombes (2017). “A Template and Probabilistic Atlas of the Human Sensorimotor Tracts using Diffusion MRI.” Cerebral Cortex: 1-15.
  • Misra, G. and S. A. Coombes (2015). “Neuroimaging Evidence of Motor Control and Pain Processing in the Human Midcingulate Cortex.” Cerebral cortex 25(7): 1906-1919.
  • Misra, G., E. Ofori, J. W. Chung and S. A. Coombes (2017). “Pain-Related Suppression of Beta Oscillations Facilitates Voluntary Movement.” Cerebral Cortex 27(4): 2592-2606.
  • Misra, G., W. E. Wang, D. B. Archer, A. Roy and S. A. Coombes (2017). “Automated classification of pain perception using high-density electroencephalography data.” Journal of Neurophysiology 117(2): 786-795.