Department of Psychiatry & Behavioral Sciences
Mentors: Kelvin Lim, M.D., Department of Psychiatry & Behavioral Sciences
Hamed Ekhtiari, Ph.D., M.D., Department of Psychiatry & Behavioral Sciences
Project: Development of Personalized, Reliable, Generalizable, and Valid Targeting Neuromarker in Neuromodulation for Addiction
Ghazaleh Soleimani is a postdoctoral associate collaborating with Hamed Ekhtiari, Alex Opitz, and Kelvin O. Lim. Her research interests include the development of optimized brain stimulation protocols informed by brain mapping tools. She aims to understand how transcranial electrical and magnetic stimulation affects neural and behavioral outcomes. Utilizing MRI neuroimaging, EEG data, signal processing, and machine learning techniques, she investigates the relationship between stimulation-induced electric fields and changes in brain functions and behaviors. Her research is directed toward creating personalized brain stimulation protocols and refining stimulation parameters for individuals with substance use disorders (SUD).
Ghazaleh is developing an innovative approach to improving neuromodulation targeting strategies and developing new treatments for SUD, using multimodal neuroimaging. Her work builds upon resting state fMRI and drug cue reactivity data to identify targeting neuromarkers in the fronto-limbic network for addiction treatment. Her project will utilize new multimodal neuroimaging data, including high-quality structural, resting-state, and task-based fMRI data from multiple groups of participants with different SUDs, including test-retest data. Connectome-based predictive modeling using machine learning methods will also be applied to predict individual behavior (craving) from brain connectivity. This pipeline provides a unique opportunity to develop, validate, and test the reliability and generalizability of targeting neuromarkers in independent samples with SUDs. The ultimate goal is to integrate these insights into developing a precise, individualized MRI-guided TMS protocol targeting the fronto-limbic circuit, a known predictor of relapse in SUDs.
