A Superior Software Solution for Functional MEG (Magnetoencephalography) Brain Imaging
High spatial stability and continuous temporal dynamics, without compromising spatial or temporal resolution. Elimination of “spiky-looking” discontinuities that are often observed in the conventional minimum L1-norm approaches. Reduced computational cost compared with many non-linear optimization approaches, such as non-linear multiple-dipole modeling.
Non-invasive detection of the exact site of brain abnormalities and localization of the sources of seizures in patients with epilepsy. Assists surgeons to localize and avoid the speech centers of the patient’s brain during surgery. Establishes the functionality of various areas of the brain.
Dr. Huang at UC San Diego has developed a vector-based spatial–temporal analysis using a L1-minimum-norm (VESTAL) solution. This technology overcomes the problems associated with conventional minimum L1-norm approaches. The simulations showed that VESTAL could resolve sources that are 100 percent correlated; therefore, additional assumptions about their temporal dynamics are not needed, eliminating potential skewing of images. Furthermore, when VESTAL was used to analyze human median-nerve MEG responses, it demonstrated high temporal stability and spatial resolution due to its capability of distinguishing sources that were exceedingly close in proximity to each other.
State Of Development VESTAL was tested in computer simulations and the performance of VESTAL was further examined using human MEG responses evoked by unilateral median-nerve stimulations. This is the first demonstration using MEG to map out the cortical areas in the somatosensory system simultaneously with high spatial resolution. In addition, VESTAL showed early activation in the thalamus and has the potential for localizing deep sources. Related Materials Tech ID/UC Case 19798/2009-826-0 Related Cases 2009-826-0
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