I find it very much fascinating to use NIBS techniques to probe the function and role of specific cortical areas in cognitive and emotional functions both in healthy and patient populations. Investigating the effects of TMS on brain activity and its potential to modulate cortical excitablity in the context of TMS-fMRI studies and using it as a perturbation tool to find out more about the dynamics of the brain across healthy population and different psychopathologies in the context of TMS-EEG studies, is another research line that is highly of interest to me. In addition to all that, I very much like to also look at the autonomic nervous system and how it affects and is affected by higher-level cortical areas as I think bottom-up mechanisms play as important a role (if not more important) in shaping and guiding cognitive processes such as attention, perception, etc.
A very general mix of cognition, emotion, and behavior one may say!
Non-Invasive Brain Stimulation
Autonomic Nervous System
Publications & Submissions:
Kazemi, R., Rostami, R., Dehghan, S., Nasiri, Z., Lotfollahzadeh, S., Hadipour, A. L., ... & Ikeda, S. (2020). Alpha Frequency rTMS Modulates Theta Lagged Nonlinear Connectivity in Dorsal Attention Network. Brain Research Bulletin. Volume 162, September 2020, Pages 271-281.
6 Hz Transcranial Alternating Current Stimulation of mPFC Improves Sustained Attention and Modulates Alpha Phase Synchronization and Power in Dorsal Attention Network, Under Review in Cognitive Neuroscience, Current Debates, Research, & Reports.
Effect of 10Hz rTMS over Right DLPFC on Heart Rate Variability and Emotional Processing and Regulation: Investigation of a Social Neuroscience Model of Adult Attachment, In Prep.
Effects of 20 Sessions of Unilateral & Bilateral rTMS on Rumination and Depression in MDD Patients, Original Study, In Prep.
Transdiagnostic Role of Glutamate [Excitotoxicity] and White Matter Damage in Neuropsychiatric Disorders (GAD, MDD, OCD, and Schizophrenia), In Prep.
EEG Predictors of Response to rTMS Treatment in MDD Patients , Using Deep Learning Classification (Focus on Gender Effects), Pilot Multisite Project in Iran and Turkey.