Physiological Noise Extraction in FMRI Data Using Empirical Mode Decomposition

Hsu-Lei Lee¹, Jürgen Hennig¹

Physiological noise caused by ecg- and/or breathing related pulsatility may introduce temporal correlations that are unrelated to neuronal processes in a resting-state network analysis. As physiological noise is often non-linear and non-stationary, signal extracted by simple filtering will deviate from the actual noise, and so as global regression methods like RETROICOR. In this study we implemented empirical mode decomposition (EMD) on resting-state fMRI time-series and extracted cardiac components which has a time-frequency curve that well matches the true heart rate acquired by external ECG during the scan.