Dr. Huang is a leading scientist in developing advanced computational approaches to the analysis of magnetoencephalography (MEG) and electrophysiological (EEG) data, and in applying MEG/EEG to study neurological and psychiatric disorders in human. As an Associate Professor of Department of Radiology at University of California, San Diego (UCSD), and a Radiology Physicist at VA San Diego Healthcare System (VASDHS), Mingxiong Huang has been working for UCSD and VASDHS since March 2004.  Dr. Huang received his PhD in biomedical physics from Northeastern University at Boston in 1995.  During 1995­1997, Dr. Huang worked as a postdoctoral research associate in the Biophysics Group at Los Alamos National Laboratory, a group with international reputation of MEG research.  During 1997­2004, Dr. Huang was first a Research Assistant Professor (December 1997­April 2003), and then a Research Associate Professor (May 2003­February 2004) of Department of Radiology at University of New Mexico, while jointly as a Core Research Scientist at the Center for Functional Brain Imaging (CFBI), New Mexico VA Health Care System in Albuquerque. Recently, Dr. Huang has organized the installation of the state-of-the-art MEG system at Radiology Imaging Laboratory, UCSD. He is currently in charge of the daily operation of the MEG system and providing trainings to other investigators. The UCSD MEG group is considered by many MEG scientists one of the strongest MEG programs in the world.

One of Dr. Huang’s research areas primarily focused on the forward and inverse modeling of MEG and EEG.  For MEG/EEG forward modeling, he studied a variety of MEG/EEG head models, e.g., sensor-weighted multiple spherical model, boundary element models, and finite element models.  His research areas in the MEG/EEG inverse modeling covered: 1) spatio-temporal multiple dipole models using multi-start (MSST) global minimization, genetic algorithm, simulated annealing, and multiple signal classification (MUSIC); 2) inverse modeling with lead fields including minimum L1-, L2-norm solutions, and maximum entropy approach. Vector-based spatio-temporal analysis with minimum L1-norm (VESTAL) has been one of the latest developments by Dr. Huang and his collaborators for providing high resolution and stability in both spatial and time domains.

Dr. Huang’s second research interest has been applying advanced MEG forward and inverse modeling techniques to the study of human somatosensory, motor, auditory, visual, and cognitive functions on both normal subjects and patients with neurological disorders (e.g., stroke, head trauma, brain tumor, and epilepsy) and psychiatric disorders (e.g., schizophrenia and PTSD) using MEG.  For example, Dr. Huang and his collaborators showed that median-nerve stimulation in normal subjects could be used to measure responses from not only somatosensory areas but also the primary motor area using MEG.  This finding has offered direct clinical application in monitoring primary motor function in acute stroke patients who have difficulty in performing an active motor test since the MEG median-nerve test is completely passive, requiring no effort from the patients.  Using simultaneous MEG and EEG measurements, recently Dr. Huang has also found that, in control subjects, the MEG and EEG measurements correlate perfectly.  However, significant asynchrony exists between EEG and MEG auditory responses in schizophrenia patients.  This finding has been so far the only study in the literature revealing MEG-EEG asynchrony in auditory response in schizophrenia.  Currently, Dr. Huang and his collaborators are also performing studies to explore the diagnostic value of MEG on detecting mild traumatic brain injury.

Collaborators within UCSD Radiology Department: Dr. Roland Lee, Dr. Eric Halgren, Dr. Deborah Harrington, Dr. Anders Dale.