Functional Electro-physiological Neuroimaging  

Among the prevailing functional neuroimaging techniques, electroencephalography (EEG) and magnetoencephalography (MEG) have the excellent millisecond temporal resolution, which allows us to precisely study the timing of human brain activity. The goal of electromagnetic source imaging using EEG/MEG signals is to noninvasively reconstruct brain electrical activity from external surface potentials and/or magnetic fields, which is also known as the EEG/MEG ¡°inverse problem¡±. The determination of brain electrical activity by solving EEG/MEG inverse problems provides complement spatial locations of underlying neural substrates, at each time snapshot with the resolution of millisecond or tens of milliseconds. With high resolutions in both temporal and spatial domains, EEG/MEG based electrophysiological neuroimaging techniques have a unique window to monitor the spatio-temporal evolution of neuronal activity within the human brain. We are interested in developing novel EEG/MEG neuroimaging approaches, exploring them in neuroscience researches for studying neuronal processing in the working brain, and applying to clinical diagnosis of severe neurological diseases, such as epilepsy, schizophrenia, and Alzheimer's diseases.


Bioelectromagnetic phenomena in living human arise from excitable tissues, which are observable from the microscopic levels (ion channel, cell) to the macroscopic levels (muscle, heart, brain). The advancements in the theory and measurement of modern bioelectromagnetism have led to improvements in medical diagnostic and therapeutic methods and, as a result, for example, it is impossible to imagine a hospital without electrocardiography and electroencephalography. We are interested in developing novel signal acquiring schemes in probing these biological signals, which are promising to maximize the acquisition of useful information bits under the constraints caused by the physical specifications of medical devices, such as size and requirement of portable design. We work on the development of asymmetric system to deal with multiple-dimensional bioelectrical signals, which has relatively simplified data acquisition components at sensors and data reconstruction of increased complexity at the end of server, which is achieved by advanced computational approaches. The development of such an asymmetric system will make medical devices portable and increase their diagnostic power.

  Mathematical Modeling and Computational Engineering   Although bioelectromagnetism is based strongly on the general theory of electromagnetism, the theory and the analytic methods of bioelectromagnetism are very different from those of general electromagnetism because of the nature of the bioelectric sources and the volume conductors. The theory of bioelectromagnetism deals mainly with electrophysiological models of bioelectric generators, excitability of tissues, and the behavior of bioelectric and biomagnetic fields in and around the volume conductors formed by the body. We are interested in the construction of novel mathematical models with increased complexities to precisely stand for highly-defined biological systems. We work on the development of computational engineering approaches to interpret bioelectromagnetic phenomena under normal and diseased conditions.  
  Neuro-modulation Devices  

A neuromodulation device and method treats could be applied to a number of central and peripheral targets. These neuronal targets include the spinal cord, the peripheral nerves, the brain cortex, and deep brain nuclei. Present clinical indications for this treatment include neuropathic pain (failed back surgery syndrome, chronic regional pain syndrome, and peripheral nerve injury), ischemic pain (peripheral vascular disease and angina), seizures, movement disorders related to Parkinson¡¯s disease, and other functional disorders such as bladder dysfunction (urge incontinence). The neuromodulation devices usually include a pulse generator that provides stimulation pulses and an implantable lead that applies the stimulation pulses to neural tissue. An activity sensor senses activity level of the patient and a processor, responsive to the activity sensor, controls the provision of the stimulation pulses by the pulse generator. We are interested in the development of precise closed-loop control of neural tissue stimulations to adapt the stimulation therapy to changes in the patient's condition and the development of long term activity monitoring through the processor.