Retrieving connectivity patterns from functional neuroimaging data essentially deals with a problem of data-driven system identification. That is to find a directional or non-directional functional network that can explain or predict the relationship among the data at various brain locations. While neuronal interactions are physically enabled by anatomical connections, which may be reconstructed from diffusion tensor MRI [77], the consistency between functional and anatomical connectivity remains to be investigated. Moreover, neuronal circuitry at microscopic scales entails inhibitory and excitatory connections. The dynamic yet balanced behaviors of neuronal inhibition and excitation fulfill the regional computation, as well as the large-scale synchrony and interaction among regions. The linkage between the large-scale functional network and neuronal microcircuits remains unclear. Interpretations of functional connectivity in terms of excitation and inhibition are currently missing, but potentially important.
