Sonsoles Alonso

This paper introduces T-TVFC, a method for targeted time-varying functional connectivity analysis, and shows it captures task-related information in thalamocortical networks not found in traditional methods.

The paper improves the stability of time-varying functional connectivity estimates using Hidden Markov Models and hierarchical clustering on fMRI and MEG data.

This paper investigates whether fMRI functional connectivity reflects dynamic neural communication by developing and applying PCCA to show context-dependent, cognitively relevant changes in connectivity trajectories.