ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2018, Vol. 26 ›› Issue (8): 1349-1364.doi: 10.3724/SP.J.1042.2018.1349

• Research Method • Previous Articles     Next Articles

Application of time-frequency analysis in investigating non-phase locked components of EEG

WU Xia1, ZHONG Chupeng1, DING Yulong1, QU Zhe1()   

  1. 1 Department of psychology, Sun Yat-sen University, Guangzhou 510006, China
  • Received:2017-10-16 Online:2018-08-15 Published:2018-07-02
  • Contact: Zhe QU


Since the introduction of the time-frequency analysis technique into the field of EEG data in the 1980’s, researchers can excavate non-phase locked components in EEG signals, overcoming the previous shortcomings of traditional ERP methods. In the field of psychology, the two most commonly used time-frequency analysis methods are wavelet transform and Hilbert transform. Power, phase locking index (PLI), and coherence are three important indices of time-frequency analysis. Power in different frequency band is typically considered to reflect different mental processes. For example, α power is frequently related to selective attention, while γ energy is often associated with feature binding. Researchers use PLI to investigate the mechanism generated by an ERP component. Coherence indicates the exchange of information between long-distance brain regions and cognitive control of higher-level brain regions in the low-level brain regions, which show different patterns in various complex cognitive tasks.

Key words: time-frequency analysis, wavelet transform, Hilbert transform, power, PLI, coherence

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