fMRI-based techniques can only deliver data at a macroscopic view of this network, since fMRI provides brain activity measurements at the level of the voxel (a cube typically measuring several millimeters per side). fMRI techniques are therefore restricted to describing brain networks at the upper levels of their hierarchy (i.e., functional areas, functional systems). To further complicate matters, the number (and locations) of functional areas (and even functional systems) in the human brain is poorly understood, and so researchers are currently unable to form clean networks corresponding to the brain's functional architecture. Lacking strong constraints, human brain networks are defined and measured in a variety of ways, including forming networks with nodes of voxels (e.g., Buckner et al. 2009; Sepulcre et al. 2010; Fransson et al. 2010), pre-defined anatomical parcellations of voxels (e.g., He et al. 2009), or pre-defined regions of interest obtained from fMRI studies (e.g., Dosenbach et al. 2007; Fair et al. 2009). While ultimately any region definition technique should be subject to anatomical constraints, current anatomical parcellation schemes underestimate the number of functional areas in the brain.
