Time-frequency analysis of single-sweep event-related potentials by means of fast wavelet transform

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Demiralp T., Yordanova J., Kolev V., Ademoglu A., Devrim M., Samar V.

BRAIN AND LANGUAGE, cilt.66, sa.1, ss.129-145, 1999 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 66 Sayı: 1
  • Basım Tarihi: 1999
  • Doi Numarası: 10.1006/brln.1998.2028
  • Dergi Adı: BRAIN AND LANGUAGE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.129-145
  • İstanbul Üniversitesi Adresli: Evet

Özet

A time-frequency decomposition was applied to the event-related potentials (ERPs) elicited in an auditory oddball condition to assess differences in cognitive information processing. Analysis in the time domain has revealed that cognitive processes are reflected by various ERP components such as N1, P2, N2, P300, and late positive complex. However, the heterogeneous nature of these components has been strongly emphasized due to simultaneously occurring processes. The wavelet transform (WT), which decomposes the signal onto the time-frequency plane, allows the time-dependent and frequency-related information in ERPs to be captured and precisely measured. A four-octave quadratic B-spline wavelet transform was applied to single-sweep ERPs recorded in an auditory oddball paradigm. Frequency components in delta, theta, and alpha ranges reflected specific aspects of cognitive information processing. Furthermore, the temporal position of these components was related to specific cognitive processes. (C) 1999 Academic Press.

A time–frequency decomposition was applied to the event-related potentials (ERPs) elicited in an auditory oddball condition to assess differences in cognitive information processing. Analysis in the time domain has revealed that cognitive processes are reflected by various ERP components such as N1, P2, N2, P300, and late positive complex. However, the heterogeneous nature of these components has been strongly emphasized due to simultaneously occurring processes. The wavelet transform (WT), which decomposes the signal onto the time–frequency plane, allows the time-dependent and frequency-related information in ERPs to be captured and precisely measured. A four-octave quadratic B-spline wavelet transform was applied to single-sweep ERPs recorded in an auditory oddball paradigm. Frequency components in delta, theta, and alpha ranges reflected specific aspects of cognitive information processing. Furthermore, the temporal position of these components was related to specific cognitive processes.