2017
DOI: 10.1007/s11055-017-0510-3
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Effects of Russian-Language Word Frequency on Mismatch Negativity in Auditory Event-Related Potentials

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Cited by 7 publications
(4 citation statements)
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“…These data are, first, coherent with previous neurophysiological studies, finding an automatic processing of phonological information such as lexicality [ 37 , 39 ] and lexical frequency [ 66 ] in pre-attentive speech perception. Then, the interaction between these phonological factors is also in line with a few previous studies, revealing an interplay between lexicality and lexical frequency during speech perception [ 38 , 42 ].…”
Section: Discussionsupporting
confidence: 89%
“…These data are, first, coherent with previous neurophysiological studies, finding an automatic processing of phonological information such as lexicality [ 37 , 39 ] and lexical frequency [ 66 ] in pre-attentive speech perception. Then, the interaction between these phonological factors is also in line with a few previous studies, revealing an interplay between lexicality and lexical frequency during speech perception [ 38 , 42 ].…”
Section: Discussionsupporting
confidence: 89%
“…We included several theoretical, lexical, and phonotactic factors that are known to influence results. While other studies found an influence on neural data, for example, of phonotactic probabilities (Bonte et al, 2005 ; Yasin, 2007 ; Emmendorfer et al, 2020 ) or the lexical frequency of words (Alexandrov et al, 2011 ; Shtyrov et al, 2011 ; Aleksandrov et al, 2017 ), we cannot provide evidence for those factors neither on the electrophysiological nor on the behavioral data. On the contrary, we have identified a new influencing factor on MMN data: we found that neural effects were not only driven by phonemic features but also by the perceptual and psychoacoustic differences in perceived loudness in the stimuli.…”
Section: General Discussion and Conclusioncontrasting
confidence: 65%
“…Another known influential factor on speech processing is the lexical frequency of the used real words. This influence can even be present when testing real words in a passive oddball paradigm and can lead to a stronger MMN response for words with higher lexical frequency in opposition to deviants with a lower or intermediate frequency of occurrence (Alexandrov et al, 2011 ; Shtyrov et al, 2011 ; Aleksandrov et al, 2017 ). Furthermore, it has been shown that phonotactic probabilities (sequential order of phonemes in words) influence MMN results with higher probability, accompanied by enhanced MMN effects (Bonte et al, 2005 ; Yasin, 2007 ; Emmendorfer et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…The MMN responses to well-known (high-frequency) words have greater amplitudes and earlier latencies compared to those of less-known (low-frequency) words ( Davis and Gaskell, 2009 ; Tamminen et al, 2015 ; Aleksandrov et al, 2017a ). The MMN response to pseudo words also differs from real words ( Shtyrov et al, 2005 ; Shtyrov and Pulvermüller, 2007 ) as the main differences are between acoustic or structural traits, and the processing is not influenced by the meaning ( Pulvermüller et al, 2001 ; Aleksandrov et al, 2017b ), generating a MMN with longer duration, later latency and lower amplitude.…”
Section: Introductionmentioning
confidence: 99%