Wavelet Decomposition-Based Analysis of Mismatch Negativity Elicited by a Multi-Feature Paradigm

• Дата: 2014
• Автори: Najafi-Koopaie, M., Sadjedi, H., Mahmoudian, S., Farahani, E.D., Mohebbi, M.
• Формат: Стаття
• Мова: English
• Опубліковано: Інститут фізіології ім. О.О. Богомольця НАН України 2014
• Назва видання: Нейрофизиология
• Онлайн доступ: http://dspace.nbuv.gov.ua/handle/123456789/148296
• Назва журналу: Digital Library of Periodicals of National Academy of Sciences of Ukraine
• Цитувати: Wavelet Decomposition-Based Analysis of Mismatch Negativity Elicited by a Multi-Feature Paradigm / M. Najafi-Koopaie, H. Sadjedi, S. Mahmoudian, E.D. Farahani, M. Mohebbi // Нейрофизиология. — 2014. — Т. 46, № 4. — С. 01-410. — Бібліогр.: 30 назв. — англ.

In this study, event-related potentials (ERPs) collected from normally hearing subjects and elicited by a multi-feature paradigm were investigated, and mismatch negativity (MMN) was detected. Standard stimuli and five types of deviant stimuli were presented in a specified sequence, while EEG data were recorded digitally at a 1024 sec–1 sampling rate. Two wavelet analyses were compared with a traditional difference-wave (DW) method. The Reverse biorthogonal wavelet with an order of 6.8 and the quadratic B-Spline wavelet were applied for seven-level decomposition. The sixth-level approximation coefficients were appropriate for extracting the MMN from the averaged trace. The results obtained showed that wavelet decomposition (WLD) methods extract MMN as well as a band-pass digital filter (DF). The differences of the MMN peak latency between deviant types elicited by B-Spline WLD were more significant than those extracted by the DW, DF, or Reverse biorthogonal WLD. Also, wavelet coefficients of the delta-theta range indicated good discrimination between some combinations of the deviant types.