title: Evaluation of adaptive PARAFAC alogorithms for tracking of simulated moving brain sources.
abstract: In this paper, we proposed an online 2D localization method for tracking of dynamic moving brain sources. For this purpose, we used an adaptive version of PARAllel FACtor (PARAFAC) analysis for factorization of electroencephalographic (EEG) signals. We utilized Boundary Element Method (BEM) with four layers to solve the forward problem for the simulated EEG signals caused by two moving dipoles within the brain. Then, we created an appropriate tensor built by second order statistics of EEG signals. We adopted an online method to brain source localization called the Recursive Least Squares Tracking (RLST) as an adaptive PARAFAC algorithm with two windowing schemes. Finally, we evaluated the performance of the method applied to EEG signals.
authors.forename: Ardeshir
authors.initials: A
authors.lastname: Fotouhi
authors.forename: Ehsan
authors.initials: E
authors.lastname: Eqlimi
authors.forename: Bahador
authors.initials: B
authors.lastname: Makkiabadi
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D016208:Databases, Factual; D004569:Electroencephalography / Q000379:methods; D005163:Factor Analysis, Statistical; D006801:Humans; D016018:Least-Squares Analysis; D008962:Models, Theoretical