Abstract：
:Currently, event-related potential (ERP) signals are analysed in the time domain (ERP technique) or in the frequency domain (Fourier analysis and variants). In techniques of time-domain and frequency-domain analysis (short-time Fourier transform, wavelet transform) assumptions concerning linearity, stationarity, and templates are made about the brain signals. In the time-frequency component analyser (TFCA), the assumption is that the signal has one or more components with non-overlapping supports in the time-frequency plane. In this study, the TFCA technique was applied to ERPs. TFCA determined and extracted the oscillatory components from the signal and, simultaneously, localized them in the time-frequency plane with high resolution and negligible cross-term contamination. The results obtained by means of TFCA were compared with those obtained by means of other commonly used techniques of ERP analysis, such as bilinear time-frequency distributions and wavelet analysis. It is suggested that TFCA may serve as an appropriate tool for capturing the localized ERP components in the time-frequency domain and for studying the intricate, frequency-based dynamics of the human brain.
journal_name
J Neurosci Methodsjournal_title
Journal of neuroscience methodsauthors
Ozdemir AK,Karakaş S,Cakmak ED,Tüfekçi DI,Arikan Odoi
10.1016/j.jneumeth.2004.12.003subject
Has Abstractpub_date
2005-06-30 00:00:00pages
107-25issue
1-2eissn
0165-0270issn
1872-678Xpii
S0165-0270(04)00437-6journal_volume
145pub_type
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