Musical Meter Modulates the Allocation of Attention across Time

Abstract

Dynamic Attending Theory predicts that attention is allocated hierarchically across time during processing of hierarchical rhythmic structures such as musical meter. Event-related potential (ERP) research demonstrates that attention to a moment in time modulates early auditory processing as evidenced by the amplitude of the first negative peak (N1) approximately 100 ms after sound onset. ERPs elicited by tones presented at times of high and low metric strength in short melodies were compared to test the hypothesis that hierarchically structured rhythms direct attention in a manner that modulates early perceptual processing. A more negative N1 was observed for metrically strong beats compared to metrically weak beats; this result provides electrophysiological evidence that hierarchical rhythms direct attention to metrically strong times during engaged listening. The N1 effect was observed only on fast tempo trials, suggesting that listeners more consistently invoke selective processing based on hierarchical rhythms when sounds are presented rapidly. The N1 effect was not modulated by musical expertise, indicating that the allocation of attention to metrically strong times is not dependent on extensive training. Additionally, changes in P2 amplitude and a late negativity were associated with metric strength under some conditions, indicating that multiple cognitive processes are associated with metric perception.

Beat-based and memory-based temporal expectations in rhythm: similar perceptual effects, different underlying mechanisms

“…Temporal expectations have been reported to both enhance and attenuate the auditory P1 and N1 responses. Enhancement of sensory responses at expected time points (Bouwer & Honing, 2015;Escoffier et al, 2015;Fitzroy & Sanders, 2015;Hsu, Hämäläinen, & Waszak, 2013;Rimmele, Jolsvai, & Sussman, 2011;Tierney & Kraus, 2013) is in line with entrainment models of temporal expectations, which assume increased sensory gain at expected time points (Large & Jones, 1999). By contrast, attenuation of sensory responses at expected time points (Lange, 2009;Paris, Kim, & David, 2016;Sanabria & Correa, 2013;Sherwell, Garrido, & Cunnington, 2017;van Atteveldt et al, 2015) is in line with predictive models of brain function that assert more efficient processing of incoming information when predicted information is suppressed (Friston, 2005;Marzecová, Widmann, Sanmiguel, Kotz, & Schröger, 2017;Schröger, Kotz, & SanMiguel, 2015;Schröger, Marzecová, & Sanmiguel, 2015).…”

Temporal expectancies driven by self- and externally generated rhythms

“…However, Schafer et al (1981) found a larger P2 potential in the condition where no temporal information was available compared to when a tone appeared in synchrony with the beat. Recently, Fitzroy and Sanders (2015) found a larger P2 for auditory tones which appeared at a weak (unattended) compared to strong (attended) metric beat with a similar time interval (150-190 ms) and posterior topography of the effect (although this was the case in a musicians group only; in a non-musician group the effect was reversed). The present study confirms these latter results.…”

Effects of metric hierarchy and rhyme predictability on word duration in The Cat in the Hat

“…It may be the case that the regular metric structure of these texts helps listeners attend better to the content they hear. Specifically, regular metric patterns allow listeners to make predictions about when in time upcoming information is going to occur (Huron, 2006;Fitzroy & Sanders, 2015). Moreover, adult listeners have been shown to exploit regular metric patterns as cues to speech segmentation (Mattys & Samuel, 1997), lexical organization (Breen, Dilley, McAuley, & Sanders, 2014), syntactic structure (Schmidt-Kassow & Kotz, 2009), and semantic structure (Rothermich, Schmidt-Kassow, & Kotz, 2012).…”