The ability of functional MRI to acquire data from multiple brain areas has spurred developments not only in voxel-by-voxel analyses, but also in multivariate techniques critical to quantifying the interactions between brain areas. As the number of multivariate techniques multiplies, however, few studies in any modality have directly compared different connectivity measures, and fewer still have done so in the context of well-characterized neural systems. To focus specifically on the temporal dimension of interactions between brain regions, we compared Granger causality and coherency (Sun et al., 2004, 2005: Neuroimage 21:647-658, Neuroimage 28:227-237) in a well-studied motor system (1) to gain further insight into the convergent and divergent results expected from each technique, and (2) to investigate the leading and lagging influences between motor areas as subjects performed a motor task in which they produced different learned series of eight button presses. We found that these analyses gave convergent but not identical results: both techniques, for example, suggested an anterior-to-posterior temporal gradient of activity from supplemental motor area through premotor and motor cortices to the posterior parietal cortex, but the techniques were differentially sensitive to the coupling strength between areas. We also found practical reasons that might argue for the use of one technique over another in different experimental situations. Ultimately, the ideal approach to fMRI data analysis is likely to involve a complementary combination of methods, possibly including both Granger causality and coherency.