A new statistical test based on the wavelet cross-spectrum to detect time-frequency dependence between non-stationary signals: Application to the analysis of cortico-muscular interactions

► The study of coherence is at the heart of techniques for research in neuroscience. ► Coherence is a normalized measure of dependence between two signals. ► A significant level of wavelet coherence does not imply a true dependence. ► A new test on the wavelet cross-spectrum improves detection of significant dependence. ► Estimation of T-F correlations between simulated or EEG-EMG data is more accurate.