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Indexed by:会议论文

Date of Publication:2017-10-14

Included Journals:EI

Volume:459

Page Number:693-702

Abstract:Time-frequency (TF) analysis of event-related potentials (ERPs) using Complex Morlet Wavelet Transform has been widely applied in cognitive neuroscience research. It has been widely suggested that the center frequency (fc) and bandwidth (σ) should be considered in defining the mother wavelet. However, the issue how parametric variation of fc and σ of Morlet wavelet transform exerts influence on ERPs time-frequency results has not been extensively discussed in previous research. The current study, through adopting the method of Complex Morlet Continuous Wavelet Transform (CMCWT), aims to investigate whether time-frequency results vary with different parametric settings of fc and σ. Besides, the nonnegative canonical polyadic decomposition (NCPD) is used to further confirm the differences manifested in time-frequency results. Results showed that different parametric settings may result in divergent time-frequency results, including the corresponding time-frequency representation (TFR) and topographical distribution. Furthermore, no similar components of interest were obtained from different TFR results by NCPD. The current research, through highlighting the importance of parametric setting in time-frequency analysis of ERP data, suggests that different parameters should be attempted in order to get optimal time-frequency results. © 2018, Springer Nature Singapore Pte Ltd.