Abstracts

RATIONALE: We recently imaged with high resolution the spatio-temporal structure of human primary somatosensory cortex (SI) in 5 patients with Curry? and whole cortex magnetoencephalography (MEG) coregistered with MRI (MSI). METHODS: We used a whole cortex neuromagnetometer with 100 dc SQUIDs and 68 sensor sites (C.T.F. Systems) in a magnetically shielded room (B.T.i., Vacuumschmelze). We recorded somatosensory evoked fields (SEFs) after stimulation of median nerve at the wrist above motor threshold. We coregistered MRI T1 images with MEG sensors. We applied Multiple Signal Classification (MUSIC) in a sphere fit to the MRI CSF boundary. We analyzed the data using singular value decomposition (SVD) to identify signal in the data. We used MUSIC to localize sources in the surface of cerebral cortex segmented at one millimeter. We imaged MEG MUSIC sources on MRI. We interactively enlarged and rotated Curry? images to visualize active sources in central sulcus, making cortex transparent and using magnification, like an intraoperative microscope. RESULTS: The SVD showed a clear distinction between signal and noise. Signals showed coherent covariance maps for spatial loadings and large singular values above the noise floor. The MUSIC analysis of SEF over 10-50 seconds and 50-150 seconds post-stimulus showed complex sets of multiple sources constrained to cortex. Some sources from 10-50 msec post-stimulus localized in the anterior bank of central sulcus. This non-invasive microscopic view was useful to test hypotheses about the location of sources of different brain event related responses. The enlarged images will be shown. CONCLUSIONS: Whole cortex MEG with MRI analyzed by algorithms which segment cortex and which image MEG and MRI simultaneously can show microscopic detail of dynamic cortical function. SVD appears useful to filter out noise, which does not have realistic spatial field structure or covariance, and to isolate brain signals of interest. Subsequent application of MUSIC allows the identification of individual sources. This has implications for clinical epileptology and neuroscience. Supported by NIH NS20806 and RR13276.