Maria Rubega

The paper introduces a linear adaptive filter that uses structural connectivity priors to improve dynamic and directed functional connectivity estimation in electrophysiological data.

This paper introduces a new Kalman filter algorithm, STOK, for modeling dynamic brain networks and shows it outperforms classical methods in tracking time-varying connectivity patterns.

This paper introduces a method using network harmonics to track fast EEG dynamics during a face detection task with subsecond resolution.

This study uses high-density EEG to find altered directed functional connectivity in the right amygdala of depression patients compared to healthy controls.

The paper uses white matter structural connectivity to improve EEG functional connectivity by smoothing signals in a graph space derived from structural data, increasing resemblance to fMRI connectivity.