Dynamic Neuroimaging by MEG, Constrained by MRI and fMRI
MEG is a direct measure of the electrical activity of populations of neurons, with excellent temporal resolution. However, the spatial characterization of sources depends on the solution of an ill-posed inverse problem. MRI provides high resolution volumetric data defining the anatomy of the head and brain; alternative MRI data acquisition strategies allow mapping of hemodynamic correlates of neural function. However, functional MRI (fMRI) and related techniques are limited by the slow timecourse of the hemodynamic response and the ill-defined relationship between neural activation and associated hemodynamic changes. Given such complementary strengths and weaknesses, the integration of multiple imaging technologies should provide dynamic functional neuroimaging capabilities with optimal spatial and temporal resolution. We are exploring a range of strategies for the integrated analysis of data from MRI, fMRI and MEG.
KeywordsfMRI Data Equivalent Source Equivalent Current Dipole Active Voxels Weighted Pseudoinverse
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