Narges Moradi

This study improves EEG source localization by using high spatial-frequency components from fMRI, showing better performance than traditional methods.

This paper introduces a noise removal method for EEG gamma-band signals using Holo-Hilbert spectral analysis to reduce artifacts while preserving the original signal.

The paper introduces a new measure of brain network complexity using random walks and finds that the positive functional connectivity network has higher complexity than other network types.

This paper applies spatiotemporal empirical mode decomposition to resting-state fMRI to remove global signal noise, resulting in more accurate functional connectivity matrices.