Detecting change in BOLD signal between sessions for atlas-based anatomical ROIs

An algorithm using pre-defined regions of interest (ROIs) to detect differences between sessions in Blood Oxygen-Level Dependent (BOLD) signal is proposed and results from a reproducibility study are reported here. It is important to know whether tests for change have the desired statistical properties, e.g., low variability between sessions and unbiased false-positive rates, under null conditions so one is confident in any conclusions based on the metric and test used. This study examined three cognitive tasks: Stroop, response inhibition, Sternberg digits, and a visually-cued finger tapping task, in 20 healthy subjects. Each subject had two fMRI sessions, one week apart. A series of ROI summaries was constructed by choosing different proportions of voxels from the ROI and calculating the mean of t values for the selected voxels. The choice of voxels was based on the magnitude of the t values, selecting the maximum value, then the top 1%, and so on until all voxels in the ROI were included. No ROIs were found to have significant differences between sessions based on paired comparison t tests. Generally, the observed false-positive rates were near the expected rates for all summaries and tasks, although the Sternberg and Response Inhibition tasks did have higher false-positive rates when alpha>/= 0.1 for some ROI summaries. This study indicates results are reproducible and also have the desired statistical properties under null conditions.