Title :
Integrated MEG/EEG and fMRI model based on neural masses
Author :
Babajani, A. ; Soltanian-Zadeh, Hamid
Author_Institution :
Electr. & Comput. Eng. Dept., Tehran Univ.
Abstract :
We introduce a bottom-up model for integrating electroencephalography (EEG) or magnetoencephalography (MEG) with functional magnetic resonance imaging (fMRI). An extended neural mass model is proposed based on the physiological principles of cortical minicolumns and their connections. The fMRI signal is extracted from the proposed neural mass model by introducing a relationship between the stimulus and the neural activity and using the resultant neural activity as input of the extended Balloon model. The proposed model, validated using simulations, is instrumental in evaluating the upcoming combined methods for simultaneous analysis of MEG/EEG and fMRI
Keywords :
biomedical MRI; electroencephalography; magnetoencephalography; medical image processing; neurophysiology; physiological models; EEG; MEG; bottom-up model; cortical minicolumns; electroencephalography; extended Balloon model; extended neural mass model; fMRI; functional magnetic resonance imaging; magnetoencephalography; neural activity; signal extraction; Brain modeling; Electroencephalography; Enterprise resource planning; Hemodynamics; Intelligent control; Magnetic resonance imaging; Magnetoencephalography; Process control; Spatial resolution; Spatiotemporal phenomena; EEG; MEG; fMRI; integrated model; neural mass; Algorithms; Brain; Brain Mapping; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Evoked Potentials; Humans; Magnetic Resonance Imaging; Magnetoencephalography; Models, Neurological; Nerve Net; Systems Integration;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2006.873748