My research focus is to improve the accuracy of fMRI localization to better understand neural networks in motor, language and cognitive functions and to employ the ensuing insight to diagnoses and possible treatments of human brain diseases. My ultimate goal is to develop new and improved strategies utilizing magnetic resonance imaging (MRI) and functional MRI (fMRI) technologies for diagnosis and treatment of human brain dysfunctions. Validating fMRI mapping with the other brain mapping methods is an important area of research for accessing the clinical feasibility testing. I have been actively developing multimodality image mapping methods to evaluate fMRI localization against the other functional imaging modalities.

My research topics include fMRI motion correction, correlation of fMRI signals with clinical brain mapping tools for presurgical evaluations, cross-validation of fMRI activation maps with the other brain mapping tools (i.e., electrocortical stimulation mapping, EFAM, optical imaging), modeling of motion related image distortion, spin saturation and susceptibility induced field inhomogeneity, multimodality image registration for detection and treatment monitoring of brain disorders, diffusion tensor imaging of peripheral nerves in diabetes. My group has been developing advanced algorithms for detecting head motion at each slice acquisition in fMRI time series data and analyzing and modeling image artifacts associated with the dynamic head motion, i.e., dynamic changes in field inhomogeneity and image distortion. Specifically my new research direction focuses on combining emerging methodologies in MRI acquisition design and robust image registration and processing for analysis and integration of structural and functional information to efficiently support clinical utilities of quantitative fMRI/MRI (Link).