Literature DB >> 18703088

Independent component analysis on the mismatch negativity in an uninterrupted sound paradigm.

Igor Kalyakin1, Narciso González, Tommi Kärkkäinen, Heikki Lyytinen.   

Abstract

We compared the efficiency of the independent component analysis (ICA) decomposition procedure against the difference wave (DW) and optimal digital filtering (ODF) procedures in the analysis of the mismatch negativity (MMN). The comparison was made in a group of 54 children aged 8-16 years. The MMN was elicited in a passive oddball protocol presenting uninterrupted auditory stimulation consisting of two frequent alternating tones (600 and 800 Hz) of 100 ms duration each. Infrequently, one of the 600 Hz tones was shortened to 50 or 30 ms. The event related potentials (ERPs) were decomposed into the MMN-like and non-MMN-like independent components (ICs) through the FastICA algorithm. The ICA decomposition procedure extracted a cleaner MMN compared to the ODF or DW procedures. It extracted the MMN, whose characteristics concurred with the substantial number of publications demonstrating a significantly larger peak amplitude and shorter latency of the MMN in response to the more deviant stimulus (30 ms) compared to the less deviant stimulus (50 ms). The MMN to these two deviant stimuli did not differ in the peak amplitude or latency when it was extracted through the other two procedures. The ICA decomposition and ODF procedures, similarly, significantly improved the single trial signal-to-noise ratio (SNR) of the MMN compared to the DW procedure. Due to this improvement, the proposed ICA decomposition procedure might allow shortening of the recording session and could be used to study the MMN in paradigms similar to this with small modifications.

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Year:  2008        PMID: 18703088     DOI: 10.1016/j.jneumeth.2008.07.012

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  4 in total

1.  Answering six questions in extracting children's mismatch negativity through combining wavelet decomposition and independent component analysis.

Authors:  Fengyu Cong; Igor Kalyakin; Hong Li; Tiina Huttunen-Scott; Yixiang Huang; Heikki Lyytinen; Tapani Ristaniemi
Journal:  Cogn Neurodyn       Date:  2011-06-28       Impact factor: 5.082

2.  Weighted Blind Source Separation Can Decompose the Frequency Mismatch Response by Deviant Concatenation: An MEG Study.

Authors:  Teppei Matsubara; Steven Stufflebeam; Sheraz Khan; Jyrki Ahveninen; Matti Hämäläinen; Yoshinobu Goto; Toshihiko Maekawa; Shozo Tobimatsu; Kuniharu Kishida
Journal:  Front Neurol       Date:  2022-02-25       Impact factor: 4.003

3.  Hilbert-Huang versus Morlet wavelet transformation on mismatch negativity of children in uninterrupted sound paradigm.

Authors:  Fengyu Cong; Tuomo Sipola; Tiina Huttunen-Scott; Xiaonan Xu; Tapani Ristaniemi; Heikki Lyytinen
Journal:  Nonlinear Biomed Phys       Date:  2009-02-02

4.  Event-related potentials to unattended changes in facial expressions: detection of regularity violations or encoding of emotions?

Authors:  Piia Astikainen; Fengyu Cong; Tapani Ristaniemi; Jari K Hietanen
Journal:  Front Hum Neurosci       Date:  2013-09-11       Impact factor: 3.169

  4 in total

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