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Multiple current dipole estimation in a realistic head model using R-MUSIC

Neural activity in the human brain can be modeled as a volume conductor with current dipoles representing collections of neuronal sources. Determining the spatio-temporal characteristics of the sources from such models requires a solution to the inverse electrostatic problem. In this study, the Recursive MUSIC algorithm was used to invert combinations of synchronous and asynchronous dipolar sources in an anatomically realistic head model. The performance was analyzed at signal-to-noise ratios from 0 to 30 dB. Localization of independent sources was excellent, even at low signal-to-noise ratios, demonstrating the potential performance advantages of a spatio-temporal analysis over a purely spatial treatment. Localization for synchronous sources was substantially degraded at signal-to-noise ratios below 20 dB, demonstrating a need for improved methods to distinguish between asynchronous and synchronous sources.