Causal Source Analysis of EEG

DESCRIPTION (provided by applicant): We propose to develop, validate, and commercialize innovative software tools for the study of causal dynamics of large-scale brain networks in humans. These tools may be used to provide neurologists with a reliable diagnostic for locating epilepsy seizure foci, and to provide neuroscientists with new analytic tools for assessing neural information transmission in the human brain. During Phase I, analysis methods will be developed and implemented to estimate the causal connectivity among selected brain regions. These methods are based on the computing the causal information between time series that represent brain activity in selected regions of interest, using the REGAE (regional brain activity estimation) algorithm. A nonparametric test of statistical significance will be developed and applied to the casual estimates. The results will be visualized using a causal diagram, indicating the statistically significant causal paths between brain regions, and their characteristic lags. The methods will be verified using simulated data, and evaluated with EEG data from epilepsy patients, as well as with evoked response data from normal subjects. Upon completion of development and testing, the new tools will be integrated into our existing EMSE Suite product for commercialization.