The impact of musical expertise on anticipatory semantic processing during online speech comprehension: An electroencephalography study

The modulating effect of musical expertise on lexical‐semantic prediction in speech‐in‐noise comprehension: Evidence from an EEG study

“…Consistent with the above hypothesis, our laboratory's previous EEG study found that musical expertise facilitates online lexical-semantic prediction at anticipatory stage in a quiet speech processing condition (Zheng et al, 2021). This facilitation effect was more prominent in an incongruent prosody-priming condition (than in the congruent condition).…”

“…As the experimental sentences of Reading Experiment were presented in a relatively slow word-by-word fashion, the online lexical-semantic processing could be quite easy for participants. Accordingly, musicians might selectively weaken the involvement of anticipatory semantic processing system in the reading comprehension situation when no interference disturbed the online comprehension progress (as was demonstrated in the congruent-prosodypriming condition of Zheng et al, 2021). Although further research is needed to examine the exact reasons underlying the above impeding effect in musicians, this impeding effect helps us understand the internal mechanisms underlying the musical-expertise enhancement effect on lexical-semantic prediction in speech-in-noise comprehension, which would be discussed below.…”

“…According to the OPERA theory (Patel, 2011(Patel, , 2014, musical expertise might modulate language prediction by strengthening the shared neural resources between music prediction and language prediction (Patel & Morgan, 2017;Zheng et al, 2021). Similar to language prediction, music prediction is performed at multiple levels (Patel & Iversen, 2014), such as anticipating the upcoming pitch/timbre of notes and the harmony of music pieces based on high-level prior knowledge (e.g., global structural rules) (Patel & Morgan, 2017) or low-level acoustic cues (Pearce & Wiggins, 2006).…”

“…Notably, lexical‐semantic prediction, the top‐down process of preactivation of lexical features of upcoming words based on available semantic contexts or long‐term memory knowledge (Kuperberg, 2021; Kuperberg & Jaeger, 2016), is hypothesized to improve the online processing efficiency of the degraded speech signal (e.g., Mattys et al, 2012; Pichora‐Fuller et al, 1995; Sohoglu et al, 2012). This mechanism may be critical for facilitating online speech‐in‐noise processing (Obleser & Kotz, 2010; Wang et al, 2013; Zekveld et al, 2012) and may be influenced by musical expertise (e.g., Zheng et al, 2021). The objective of this study was to examine whether and how musical expertise modulates the lexical‐semantic predictive processing during online speech‐in‐noise comprehension.…”

“…Either of these two processes might be temporally predominant in specific situations (e.g., at different positions of a sentence) (e.g., Li et al, 2020). Direct evidence for the anticipatory process comes from the findings showing significant ERP (event‐related potential) effects at the words preceding predictable target words (vs. unpredictable words) (e.g., an enhanced ERP‐negativity effect in Otten & Van Berkum, 2009; an enhanced ERP‐positivity effect in Wicha et al, 2004); these pretarget ERP effects were also found to be significantly correlated with the cloze probability values of upcoming target words (Li et al, 2020; Zheng et al, 2021). After the appearance of target words, it was widely observed that the highly predictable words elicited a reduced N400 effect (vs. the less predictable ones) (e.g., Federmeier et al, 2010; Hagoort & Brown, 2000; Li et al, 2017), which was taken to indicate easier integration of these predictable words with their preceding semantic contexts due to facilitated preactivation of their lexical features, reduced integration load, or both (Baggio & Hagoort, 2011).…”