2008 21st IEEE International Symposium on Computer-Based Medical Systems 2008
DOI: 10.1109/cbms.2008.72
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Extraction of the Mismatch Negativity on Two Paradigms Using Independent Component Analysis

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Cited by 3 publications
(5 citation statements)
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“…However, they noted that application of the DW procedure reduced the SNR of the MMN, in turn, yielding poorer classification accuracy. Recently, the proposed ICA decomposition procedure was also tested on more prototypical MMN protocol, employing an interrupted sound paradigm (Kalyakin et al, 2008). The stimulus setup in that paradigm was based on the present paradigm.…”
Section: Discussionmentioning
confidence: 99%
“…However, they noted that application of the DW procedure reduced the SNR of the MMN, in turn, yielding poorer classification accuracy. Recently, the proposed ICA decomposition procedure was also tested on more prototypical MMN protocol, employing an interrupted sound paradigm (Kalyakin et al, 2008). The stimulus setup in that paradigm was based on the present paradigm.…”
Section: Discussionmentioning
confidence: 99%
“…The ICA decomposition procedure to extract the MMN in an uninterrupted sound paradigm was originally proposed in [12] and then extended by the authors with results of statistical comparison in [11]. In this study, the implementation of the procedure was fully identical to that reported in these two studies.…”
Section: Ica Decomposition Proceduresmentioning
confidence: 90%
“…However, neither the DW nor ODF procedures extracted the MMN with characteristics expected from substantial number of publications: the more deviant stimulus (i.e., 30 ms) elicits a more pronounced MMN, whose peak amplitude is larger and whose latency is shorter, than the less deviant stimulus (i.e., 50 ms). Recently, a new procedure to extract a cleaner MMN than after application of the DW and ODF procedures was initially proposed in [12] using the same data as in [6,10] and then extended by the authors with results of statistical comparison in [11]. The procedure was based on independent component analysis (ICA) [8].…”
Section: Introductionmentioning
confidence: 99%
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