The main focus of my research is early diagnosis of Alzheimer's disease using computational modeling of combined TMS-EEG. I compare key measures of cortical excitability, connectivity, and plasticity in health and disease in order to discover early bio-markers for cognitive decline in Alzheimer’s disease patients. I use a variety of statistical and computational methods including biophysical modeling and graph theory.
I am a research officer at the lab of Prof. Mike Ridding. I quantitatively analyse non-invasive brain stimulation and electroencephalogram data in human subjects. My current research projects includes:
- The association of resting state functional connectivity with plasticity response to non-invasive brain stimulation.
- Characterising changes in cortical connectivity following application of non-invasive brain stimulation.
|Columbia University||United States||Master's degree|
|Sharif University of Technology||Iran||Bachelor's degree|
|2017||Hordacre, B., Moezzi, B., Goldsworthy, M., Rogasch, N., Graetz, L. & Ridding, M. (2017). Resting state functional connectivity measures correlate with the response to anodal transcranial direct current stimulation. European Journal of Neuroscience, 45, 6, 1-9.
|2016||Moezzi, B., Iannella, N. & McDonnell, M. (2016). Ion channel noise can explain firing correlation in auditory nerves. Journal of Computational Neuroscience, 41, 2, 193-206.
|2016||Hordacre, B., Goldsworthy, M., Vallence, A., Darvishi, S., Moezzi, B., Hamada, M. ... Ridding, M. (2016). Variability in neural excitability and plasticity induction in the human cortex: A brain stimulation study. Brain Stimulation, 10, 3, -.
|2014||Moezzi, B., Iannella, N. & McDonnell, M. (2014). Modeling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics. Frontiers in Computational Neuroscience, 8, Dec, 163-1-163-12.