The analysis of functional magnetic resonance imaging (fMRI) data can greatly benefit from flexible analytic approaches. In particular, the advent of data-driven approaches to identify whole-brain time-varying connectivity and activity has revealed a number of interesting relevant variation in the data which, when ignored, can provide misleading information. In this lecture, I will provide a comparative introduction of a range of data-driven approaches to estimating time-varying connectivity.
From 1D to 5D: Data-driven Discovery of Whole-brain Dynamic Connectivity in fMRI Data
