PROJECT TITLE :

Local Multimodal Serial Analysis for Fusing EEG-fMRI: A New Method to Study Familial Cortical Myoclonic Tremor and Epilepsy

ABSTRACT:

Integrating information of neuroimaging multimodalities, like electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), has become popularly for investigating numerous sorts of epilepsy. But, there are also some issues for the analysis of simultaneous EEG-fMRI data in epilepsy: one is that the variation of HRFs, and another is low signal-to-noise ratio (SNR) in the information. Here, we have a tendency to propose a brand new multimodal unsupervised technique, termed native multimodal serial analysis (LMSA), that could make amends for these deficiencies in multimodal integration. A simulation study with comparison to the ancient EEG-informed fMRI analysis that directly implemented the overall linear model (GLM) was conducted to substantiate the superior performance of LMSA. Then, applied to the simultaneous EEG-fMRI information of familial cortical myoclonic tremor and epilepsy (FCMTE), some meaningful information of BOLD changes related to the EEG discharges, such as the cerebellum and frontal lobe (particularly within the inferior frontal gyrus), were found using LMSA. These results demonstrate that LMSA is a promising technique for exploring varied information to provide integrated info that will more our understanding of brain dysfunction.


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