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In the last decade, an increasing interest has arisen in investigating the relationship between the electrophysiological and hemodynamic measurements of brain activity, such as EEG and (BOLD) fMRI. In particular, changes in BOLD have been shown to be associated with changes in the spectral profile of neuronal activity, rather than with absolute neural power. On the other hand, though, recent findings showed that different EEG rhythms are independently related to changes in the BOLD signal: therefore, it would be important to distinguish between the contributions of the different EEG rhythms to BOLD fluctuations when modeling the relationship between EEG and BOLD. Here we proposed a novel method to perform EEG-informed fMRI analysis, so that the EEG regressors take into account both the changes in the spectral profile and the rhythms distinction. We applied it to EEG-fMRI data during a bimanual motor task in healthy subjects, and compared the results with those obtained by regressing fMRI data onto a single regressor covering the entire range of frequencies, ignoring the distinction between different EEG rhythms. Our results showed that the proposed method better captures the correlations between BOLD signal and EEG rhythms modulations, identifying task-related well localized activated volumes.