Margherita Carboni

The paper introduces a multimodal neuroimaging dataset containing EEG, MRI, and behavioral data for studying visual evoked potentials and brain connectivity.

This paper introduces the connectome spectrum as a method to represent brain activity using structural connectivity, showing it provides a more compact and informative representation of fast brain dynamics.

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

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.