The brain has all of the hallmarks of a complex system, with meaningful activity occurring at a wide range of spatial and temporal scales. When measured with resting state fMRI, all of this activity is compressed into a single measurement of the resulting hemodynamic response for each voxel at each time point. However, by leveraging the spatial, temporal and spectral properties of different types of activity, we may be able to identify signatures in the rs-fMRI signal. In this talk, I will describe some of the types of activity that we expect to contribute to the rs-fMRI signal and features that might allow us to selectively extract them for use in research or the clinic.