Fig. 2.

Generating a PPI regressor. (a) We start with a regressor representing the main effect of task (in this case, a block design) (dashed line), and convolve it with the HRF to get an HRF convolved task regressor (black line). The horizontal grey line is zero. (b) We extract a time course from our seed region of interest (blue line). If this region of interest was active during the task, the time course of activity from the seed region will be correlated with the HRF convolved task regressor. (c) We generate a PPI regressor (red line) as an element-by-element product of the HRF convolved task (black line) and seed ROI (blue line) regressors. Note that the PPI regressor is correlated with the seed region time course during task blocks, but anti-correlated with it during rest blocks. Consequently, voxels that are always correlated with the seed ROI (e.g. due to anatomical connections that are not task-relevant) will have an overall regression co-efficient of zero for the PPI regressor, but voxels which are more correlated with the seed ROI during task blocks than during rest will show a positive correlation with the PPI regressor.