title: Box-Jenkins intervention analysis of functional magnetic resonance imaging data.
abstract: Data obtained in functional magnetic resonance imaging (fMRI) typically form a time series of MRI signal collected over a period of time at constant intervals. These data are potentially autocorrelated and may contain time trends. Therefore, any assessment of significant changes in the MRI signal over a certain period of time requires the use of specific statistical techniques. For that purpose we used the Box-Jenkins intervention time series analysis to determine brain activation during task performance. We found that for a substantial number of pixels there was significant autocorrelation and, occasionally, time trends. In these cases, use of the classical t-test would not be appropriate. In contrast, Box-Jenkins intervention analysis, by detrending the series and by explicitly taking into account the correlation structure, provides a more appropriate method to determine the presence of significant activation during the task period in fMRI data.
authors.affiliation: Veterans Affairs Medical Center and Department of Physiology, University of Minnesota Medical School, Minneapolis 55417, USA.
authors.forename: G A
authors.initials: GA
authors.lastname: Tagaris
authors.forename: W
authors.initials: W
authors.lastname: Richter
authors.forename: S G
authors.initials: SG
authors.lastname: Kim
authors.forename: A P
authors.initials: AP
authors.lastname: Georgopoulos
mesh_terms: D006801:Humans; D008279:Magnetic Resonance Imaging; D013223:Statistics as Topic; D013997:Time Factors