Title :
Constraining Minimum-Norm Inverse by Phase Synchronization and Signal Power of the Scalp EEG Channels
Author :
Majumdar, Kaushik
Author_Institution :
Odyssee Group, Inst. Nat. de Rech. en Inf. et en Autom., Sophia Antipolis
fDate :
4/1/2009 12:00:00 AM
Abstract :
In this paper, the goal is to further improve the output of the scalp EEG source localization by the Euclidean minimum-norm (MN) inverse during single trials. Trials have been selected based on signal power at specific time intervals in specific locations. Then the source localization has been performed by MN. It has been observed that close to a dominant cortical source of EEG, as determined by the MN, both pairwise phase synchronization of a channel with its nearest neighbors and the cumulative signal power of the channels within that neighborhood become high (normalized values remain above certain thresholds). This has also been verified through simulations on the subject´s real head model. The conclusion of our study is that only those sources are to be chosen for which MN inverse, and signal power and phase synchronization profile converge. A novel fast Fourier transform (FFT) based phase synchronization measuring algorithm between a pair of signals has been developed whose time complexity is no more than that of the FFT.
Keywords :
electroencephalography; fast Fourier transforms; medical signal processing; synchronisation; Euclidean minimum-norm inverse; cumulative signal power; fast Fourier transform based phase synchronization; pairwise phase synchronization; scalp EEG channels; scalp EEG source localization; time complexity; Bayesian methods; Brain modeling; Electroencephalography; Fast Fourier transforms; Magnetic heads; Nearest neighbor searches; Phase measurement; Scalp; Signal to noise ratio; Statistics; Time measurement; Distributed source model; EEG; fast Fourier transform (FFT); minimum norm (MN); phase synchronization; real head model; Adult; Algorithms; Brain Mapping; Cerebral Cortex; Cluster Analysis; Cortical Synchronization; Fourier Analysis; Humans; Male; Median Nerve; Models, Neurological; Transcutaneous Electric Nerve Stimulation;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2008.2008637