Exploring fMRI data for periodic signal components.
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.
Hansen
Lars Kai
LK
Informatics and Mathematical Modelling, Technical University of Denmark B321, Lyngby, Denmark. lkh@imm.dtu.dk
Nielsen
Finn Arup
FA
Larsen
Jan
J
D016477:Artifacts; D001499:Bayes Theorem; D001921:Brain / Q000502:physiology*; D003627:Data Interpretation, Statistical; D005544:Forecasting; D006801:Humans; D008279:Magnetic Resonance Imaging; D011336:Probability