Rikkert Hindriks

The paper characterizes second-order mixing effects in EEG/MEG cross-spectra and derives properties of signal mixing using resolution operators and cross-talk functions.

The paper constructs invariant features for EEG/MEG signals using Grassmann manifolds to improve the analysis of functional connectivity in brain activity.

This paper introduces graph neural fields, a framework for modeling brain activity on the human connectome, and demonstrates its ability to reproduce BOLD fMRI harmonic power spectra.

This study reconstructs resting-state networks from macaque ECoG data using source-space independent component analysis, identifying seven cortical generators in the motor system with spatially continuous dynamics.

This study investigates the reliability and variability of resting-state fMRI functional connectivity, showing that while single links are unreliable, whole-brain correlation structures are stable and can serve as functional fingerprints.

This study identifies 16 cortical alpha generators in resting-state MEG data and shows they form functional networks including the default mode and ventral attention networks.