The overall objective of the proposed research is to develop hardware, software, and techniques to substantially expand the utility of Magnetoencephalography (MEG), both as a clinical diagnostic tool and as a modality for basic studies in the neurosciences.
One aim of the research is to develop new analytical techniques and software to exploit the unique ability of MEG to extract more significant kinds of information from magnetic fields of physiologic origin and to make these techniques readily usable. Effective methods for distinguishing and localizing weak generators which fire almost simultaneously with stronger ones have been developed by the applicants. As a demonstration of these techniques and of their transferability, it is proposed to study anomalies in the auditory evoked responses of dyslexic individuals. A method has been developed to monitor subtle spectral changes in MEG signals accompanying changes in alertness or arousal which is more quantitative than the conventional sleep stage classification. This technique will be refined and applied to the analysis of spontaneous MEG activity during migraine headache. A second capability of MEG is the completely non-invasive measurement of very slow (DC) shifts which are known to arise in a variety of pathological conditions. Such shifts cannot readily be studied using surface electroencephalography (EEC) because of impedance changes which inevitably occur at the electrode-skin interface. Unfortunately, MEG measurements are also contaminated by noise, both environmental (even in elaborately shielded rooms) and from regions of the patient's body not under study, a serious problem for the observation of spontaneous low frequency activity. Noise cancellation techniques provided by neuromagnetometer manufacturers have proven inadequate to deal with such problems, in some cases themselves introducing artifacts into the data. Significant progress in noise cancellation techniques involving noise pattern recognition has been made. Progress has also been made in measuring absolute values of DC magnetic fields, such as are expected to arise from currents of injury and from spreading cortical depression. These techniques will be applied to studies of spontaneous MEG activity in migraine patients and in epilepsy surgery patients as well as a rat model of epilepsy, in both of which fields due to injury currents will be studied pre and post surgery. Useful progress has been made in mathematical modeling of MEG signals from spreading cortical depression (SCD) and in creating a phantom for the study of resistivity chances such as occur in SCD.
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