Currently, the lab has several major research programs.

Core 1: Brain Computer Interface/Neurofeedback
We are developing neuroimaging techniques to interface between brain activities and computer/robotic control. This new breed of technology, called Brain-computer-interface, would help people with severe disabilities and neuromuscular diseases such as ALS. As the extension of this BCI application, functional MRI method capable of biofeedback of brain function may help individuals with stroke or brain damage learn to modulate their own brain function, and consolidate the function via cortical plasticity and learning. We are currently developing batteries of MRI sequence and processing algorithms, combined with more traditional approach such as MRI-compatible EEG

Core 2: PET-MRI Fusion System Development: Molecular Imaging
With international collaboration with Gachon Medical School in Korea, we are implementing new imaging methods and testing unprecedented world-first fusion system of ultra-high field MRI ( 7 Tesla) MRI and high-resolution PET system. We are currently focusing on the implementation of real-time fMRI and diffusion tensor MRI. We are also adding cell imaging capability to the system using reduced field-of-view, specially-selective excitation.

Core 3: Stem Cell MR Imaging for Regenerative Medicine
The MRI detection of superparamagnetic iron-oxide particles (SPIO) -labeled cells is important in cell-replacement therapies, which can help monitoring the migration/proliferation of cells following the transplantation. Selective and positive contrast for SPIO-labeled cells is warranted with suppression of background tissue, and recently, several methods to elicit positive contrast have been suggested. We are developing cell MR methods that are (1) clinically practical (scan time less than 20 minutes), (2) clinically relevant (more than 1 month monitoring of cell migration and proliferation observable at microscopic resolution). We have developed simple means of detecting SPIO-labeled cells by using susceptibility weighted echo-time encoding technique (SWEET) whereby the subtraction of two sets of image volumes acquired at slightly-shifted echo time generates positive contrast at the cell position.

Core 4: Tissue Engineering Project/ MEMS application to Regenerative Medicine
The future success of the regenerative medicine will rely heavily of tissue engineering whereby the living tissue can be grown artificially. However, strategic spatial placement of specific cell types and cellular environment along with mechanical support is challenging. We are developing 3D 'on-demand' cell printer technology that will enable to place multiple types of cell(s) in coordinates in 3-dimension with pinpoint accuracy (individual cell size). Thermosensitive gel and classical scaffold material can be used to provide the mechanical stability. We are also working with our international partners to develop Micro electro-mechanical systems (MEMS) technology which will standardize the stem cell growth method.

Core 5: Imaging of Early Human Development
Under the guidance of professor Gary Zientara who pioneered the preterm infant imaging at BWH, we are studying the functional and structural (white matter) neurodevelopment of preterm and term newborns using functional MRI and diffusion tensor MRI. The study of early human development, especially on the neurodevelopment, can provide crucial scientific information on stem cell growth and differentiation. In addition, the information gathered from the study can be used for the treatment/intervention of abnormal brain development often associated with premature birth.

Core 6: Brain Mapping for Neuroscience/Clinical Medicine
Using fMRI, we have worked on numerous cognitive neuroscientific topics (sleep, learning, memory, plasticity, imagery), complementary and alternative medicine (acupuncture fMRI, mediation, hypnosis), neurodegenerative diseases (Alzheimer's disease), neurology (epilepsy, multiple sclerosis), brain tumor surgical planning, interventional radiology and clinical psychiatry (depression, schizophrenia). We also applied neural network approach in analyzing dynamic contrast MRI signal from breast cancer detection and characterization.

Core 7: Bioinformatics
Immense data acquired from the biosystems, in general, require efficient data processing and archiving. We are working with our research partners to tackle this complicated task concentrating on processing medical image data.