title: Exploring fMRI data for periodic signal components.
abstract: We use a Bayesian framework to detect periodic components in fMRI data. The resulting detector is sensitive to periodic components with a flexible number of harmonics and with arbitrary amplitude and phases of the harmonics. It is possible to detect the correct number of harmonics in periodic signals even if the fundamental frequency is beyond the Nyquist frequency. We apply the signal detector to locate regions that are highly affected by periodic physiological artifacts, such as cardiac pulsation.
authors: Informatics and Mathematical Modelling, Technical University of Denmark B321, Lyngby, Denmark. lkh@imm.dtu.dk
authors: Lars Kai
authors: LK
authors: Hansen
authors: Finn Arup
authors: FA
authors: Nielsen
authors: Jan
authors: J
authors: Larsen
mesh_terms: D016477:Artifacts; D001499:Bayes Theorem; D001921:Brain / Q000502:physiology*; D003627:Data Interpretation, Statistical; D005544:Forecasting; D006801:Humans; D008279:Magnetic Resonance Imaging; D011336:Probability