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.