Frontiers in Psychology (Nov 2011)
EEG correlates of song prosody: A new look at the relationship between linguistic and musical rhythm
Abstract
Song composers incorporate linguistic prosody into their music when setting words to melody, a process called textsetting. Composers tend to align the expected stress of the lyrics with strong metrical positions in the music. The present study was designed to explore the idea that temporal alignment helps listeners to better understand song lyrics by directing listeners’ attention to instances where strong syllables occur on strong beats. Three types of textsettings were created by aligning metronome clicks with all, some or none of the strong syllables in sung sentences. Electroencephalographic (EEG) recordings were taken while participants listened to the sung sentences (primes) and performed a lexical decision task on subsequent words and pseudowords (targets, presented visually). Comparison of misaligned and well-aligned sentences showed that temporal alignment between strong/weak syllables and strong/weak musical beats were associated with modulations of induced beta and evoked gamma power, which have been shown to fluctuate with rhythmic expectancies. Furthermore, targets that followed well-aligned primes elicited greater induced alpha and beta activity, and better lexical decision task performance, compared with targets that followed misaligned and varied sentences. Overall, these findings suggest that alignment of linguistic stress and musical meter in song enhances musical beat tracking and comprehension of lyrics by synchronizing neural activity with strong syllables. This approach may begin to explain the mechanisms underlying the relationship between linguistic and musical rhythm in songs, and how rhythmic attending facilitates learning and recall of song lyrics. Moreover, the observations reported here coincide with a growing number of studies reporting interactions between the linguistic and musical dimensions of song, which likely stem from shared neural resources for processing music and speech.
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