One prominent direction towards the interpretation of fMRI data has been the assessment of functional connectivity (FC), a pair-wise measure of statistical interdependence between time courses of regional activity. Here, I will outline how this already very rich characterization can be extended to capture additional features of brain function.
I will start by moving towards a dynamic functional connectome view, where functional interplays between brain areas are successively re-estimated along sub-spans of a scanning
Finally, I will introduce a methodological framework that enables to shift focus from FC to effective connectivity, where causal (rather than correlational) relationships between brain regions can be unraveled .
 Preti, Maria Giulia*, Bolton, Thomas AW*, and Dimitri Van De Ville. “The dynamic functional connectome: state-of-the-art and perspectives.” Neuroimage 160 (2017): 41-54.
 Bolton, Thomas AW, et al. “Interactions between large-scale functional brain networks are captured by sparse coupled HMMs.” IEEE transactions on medical imaging 37.1 (2
 Bolton, Thomas AW, et al. “Brain dynamics in ASD during movie‐watching show idiosyncratic functional integration and segregation.” Human brain mapping 39.6 (2018): 2391-2404.
 Huang, Weiyu*, Bolton, Thomas AW*, et al. “A Graph Signal Processing Perspective on Functional Brain Imaging.” Proceedings of the IEEE (2018)