Time-Frequency Analysis of EEG Based on Event Related Cognitive Task

  • Xiao-Tong Wen
  • Xiao-Jie Zhao
  • Li Yao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


Compared with traditional time analysis and frequency analysis, time-frequency analysis of EEG not only reveals more abundant information but also reflects their dynamic temporal oscillatory activities. Event related potential (ERP) is a kind of cognitive electroencephalogram (EEG) signal, which are directly related with task and average across spontaneous EEG. Effective time-frequency representation method and how to analyze EEG based on the event related cognitive task in time-frequency domain according to their experiment speciality are the hot study at present. In current paper, a new time-frequency method about filter bank and Hilbert transform (FBHT) was introduced, and the application for ERP and ER-EEG signal were explored in order to mine new information effectively during the classic Stroop cognitive task.


Stroop Task Wavelet Packet Wigner Distribution Wavelet Packet Decomposition High Time Frequency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bianchi, A.M., Mainardi, L.T., Cerutti, S.: Time-Frequency Analysis of Biomedical Signals. Trans. Inst. Meas. & Control 22(3), 215–230 (2000)Google Scholar
  2. 2.
    Blanco, S., Figliola, A., Quian Quiroga, R.: Time-Frequency Analysis of Electroencephalogram Series III: Wavelet Packets and Information Cost Function. Phys. Rev. E 57, 932–940 (1998)CrossRefGoogle Scholar
  3. 3.
    Williams, W.J.: Recent Advances in Time-Frequency Representations: Some Theoretical Foundation. In: Time-Frequency and Wavelets in Biomedical Signal. IEEE Press Series in Biomedical Engineering (1997)Google Scholar
  4. 4.
    Durka, P.J., Blinowska, K.J.: A Unified Time Frequency Parameterization of EEGs. IEEE Eng. Med. Biol. Mag. 20(5), 47–53 (2001)CrossRefGoogle Scholar
  5. 5.
    Hagoort, P., Hald, L., Bastiaansen, M., Petersson, K.M.: Integration of Word Meaning and World Knowledge in Language Comprehension. Science 304(5669), 438–441 (2004)CrossRefGoogle Scholar
  6. 6.
    Peng, D.L., Guo, T.M., Wei, J.H., Xiao, L.H.: An ERP Study on Processing Stages of Children’s Stroop Effect. Sci. Tech. Engng. 4(2), 84–88 (2004)Google Scholar
  7. 7.
    Polich, J., Kok, A.: Cognitive and Biological Determinants of P300: An Integrative Review. Biol. Psychol. 41(2), 103–146 (1995)CrossRefGoogle Scholar
  8. 8.
    Squires, N.K., Ollo, C.: Comparison of Endogenous Event-Related Potentials in Attend and Nonattend Conditions Latency Changes with Normal Aging. Clin. Neurophysiol. 110(3), 564–574 (1999)CrossRefGoogle Scholar
  9. 9.
    Lachaux, J.P., Rodriguez, E., Martinerie, J., Adam, C., Hasboun, D., Varela, F.J.: A Quantitative Study of Gamma-Band Activity in Human Intracranial Recordings Triggered by Visual Stimuli. European Journal of Neuroscience 12(7), 2608–2622 (2000)CrossRefGoogle Scholar
  10. 10.
    Wen, X.T., Zhao, X.J., Yao, L.: Synchrony of Basic Neuronal Network Based on Event Related EEG. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol. 3498, pp. 725–730. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiao-Tong Wen
    • 2
  • Xiao-Jie Zhao
    • 1
    • 2
  • Li Yao
    • 1
    • 2
  1. 1.Department of ElectronicsBeijing Normal UniversityBeijingChina
  2. 2.Institute of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina

Personalised recommendations