Abstract
The precision of four methods of quantifying neuroelectric signals has been improved by increasing EEG spatial sampling, using up to 124 electrodes, and by accurate anatomical registration of the EEG with Magnetic Resonance Images (MRIs). One such method, equivalent dipole modeling, is a well-known form of source localization which is useful when the generator of the scalp recorded signal approximates a simple dipolar source, as is usually the case with early and mid-latency Evoked Potentials (EPs). Two methods of enhancing spatial detail which benefit from increased spatial sampling include the Laplacian Derivation and the Finite Element Deblurring method. The latter is a new technique which estimates the EP distribution at the superficial cortical surface. The fourth method, Evoked Potential Covariance, characterizes the spatiotemporal relationships among EP segments at different recording sites. This is useful when studying “functional neural networks” underlying higher cognitive functions. These methods are reviewed and examples of results of their application in recent experiments are presented.