The long term goal of this project is to establish a multimodal functional neuroimaging methodology for noninvasively imaging brain activity and connectivity with high spatial and temporal resolution. We propose to develop and evaluate novel methods to integrate high-temporal-resolution electroencephalography (EEG) and high-spatial-resolution blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) for imaging neural activations and their interactions in humans. To achieve these goals, the following specific aims will be addressed: 1) Develop multimodal imaging methods to integrate EEG and fMRI for imaging brain activity. We will develop and refine novel neuroimaging methods for reconstructing current density distributions from integration of EEG and BOLD-fMRI. Of innovation is the proposed strategy to estimate time-variant source co-variance from both EEG and quantified BOLD responses, and to extend the method to the spatio- temporal-frequency domain. We will rigorously evaluate the proposed multimodal neuroimaging methods by means of systematic computer simulations and refine the strategy of integrating BOLD-fMRI with EEG. 2) Evaluate multimodal brain activity imaging through well-controlled human experimentation. We will evaluate our modeling assumptions with regard to the relationship between the BOLD response and the event-related electrophysiological response in a group of human subjects. We will evaluate the proposed methods using visual and motor paradigms in a group of healthy subjects. We will evaluate the proposed imaging approach using independent subdural potential recordings on 30 epilepsy patients performing the same motor and somatosensory tasks as in corresponding BOLD-fMRI and EEG studies. 3) Multimodal imaging of brain functional connectivity. We will extend the use of EEG and BOLD-fMRI for the estimation of brain functional connectivity among regions of interest. We will develop time-varying connectivity estimation methods and rigorous graph theory based analysis methods to assess the connectivity estimates. We will rigorously evaluate the fMRI-EEG integrated brain connectivity estimation methods by computer simulations and human experimentation including healthy subjects and patients undergoing surgical evaluation. The successful completion of the proposed research will: (1) enable us to address an important question in functional neuroimaging as to whether, and to what extent, multimodal integration of fMRI and EEG can further improve the performance of spatiotemporal neuroimaging;(2) enable us to develop and evaluate a novel high- resolution spatiotemporal functional neuroimaging approach, which promises to have great potential in terms of mapping human brain activity and connectivity in both healthy subjects and patients suffering from various neurological and psychiatric disorders.
The proposed work aims at developing and evaluating a high-resolution multimodal neuroimaging technology, which may provide a significantly enhanced ability to image dynamic brain function. The establishment of such a high-resolution spatio-temporal imaging modality may greatly enhance our ability to tackle and manage a number of neurological and mental disorders, and provide a significant benefit to patient healthcare.
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|Lu, Yunfeng; Worrell, Gregory A; Zhang, Huishi Clara et al. (2014) Noninvasive imaging of the high frequency brain activity in focal epilepsy patients. IEEE Trans Biomed Eng 61:1660-7|
|Zhou, Lian; Zhu, Shanan; He, Bin (2014) A reconstruction algorithm of magnetoacoustic tomography with magnetic induction for an acoustically inhomogeneous tissue. IEEE Trans Biomed Eng 61:1739-46|
|Roy, Abhrajeet; Baxter, Bryan; He, Bin (2014) High-definition transcranial direct current stimulation induces both acute and persistent changes in broadband cortical synchronization: a simultaneous tDCS-EEG study. IEEE Trans Biomed Eng 61:1967-78|
|Mariappan, Leo; Hu, Gang; He, Bin (2014) Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet. Med Phys 41:022902|
|Aarabi, Ardalan; He, Bin (2014) Seizure prediction in hippocampal and neocortical epilepsy using a model-based approach. Clin Neurophysiol 125:930-40|
|Zhang, Xiaotong; Liu, Jiaen; He, Bin (2014) Magnetic-resonance-based electrical properties tomography: a review. IEEE Rev Biomed Eng 7:87-96|
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