Differences in Neurocognitive Mechanisms Underlying the Processing of Center-Embedded and Non–embedded Musical Structures

Abstract

In music, chords are organized into hierarchical structures based on recursive or embedded syntax. How the brain extracts recursive grammar is a central question in musical cognition and other cognitive neuroscience, but the precise mechanism remains unclear. By analyzing event related potentials (ERPs) and neural oscillatory activity, the present study investigated neurocognitive mechanisms underlying the processing of center-embedded structure in music by examining the differences in center-embedded and non-embedded structure processing and evaluating how these differences are affected by musical proficiency. Based on Western musical proficiency, the subjects were divided into two groups, non-experts and experts. The results revealed that for non-experts, the processing of center-embedded structure elicited greater early right-anterior negativity (ERAN) and N5 components as well as, reduced alpha and gamma activities than did the non-embedded structure. For experts, no significant difference in the ERP response was observed between the processing of non-embedded and center-embedded structures; however, the processing of center-embedded structure elicited increased beta activity compared to non-embedded structure. These findings indicate that listeners different in proficiency would rely on different cognitive neural mechanisms in music processing with the syntactic complexity increases.

Tension Experience Induced By Nested Structures In Music

“…LPC is an ERP correlate of syntactic processing in language (Friederici et al, 1993 ; Kaan et al, 2000 ; Hahne, 2001 ; Mueller et al, 2005 ; Phillips et al, 2005 ) and music (Patel, 1998 ; Neuhaus, 2013 ; Sun et al, 2018 ), reflecting the integrative process and the cognitive resources allocation. Evidence of LPCs for the processing of non-adjacent tonal integration is also given by previous research on musical syntax violation (Koelsch et al, 2013 ; Ma et al, 2018a , b ; Zhou et al, 2019 ). The LPC effect observed in our study may be ascribed to the more cognitive resources required by combining local information into higher global hierarchical units for the nested structure than the non-nested structure.…”

“…Until recently, Koelsch et al ( 2013 ) first explored the neural responses to the processing of nested structure and found that structurally irregular endings elicited larger early right anterior negativity (ERAN) and N5 components than structurally regular endings, reflecting the structural integration for long-distance dependence. Similar components, such as N5 and late positive component (LPC), were also observed in music nested structure processing by Chinese listeners (Ma et al, 2018a , b ; Zhou et al, 2019 ). These results demonstrated the integration of harmonic cadence into the originally tonal context and the cognitive processing of nested structure.…”

“…Furthermore, given that the key point representing the tonality return was the cadence in the nested structure, the event-related potential (ERP) responses were locked to the final chords. Based on the cognitive processing of nested structure reported in previous studies (Koelsch et al, 2013 ; Ma et al, 2018a , b ; Zhou et al, 2019 ), we also predicted that larger N5 or LPC would be elicited by the nested structure compared to the non-nested structure, reflecting the cognitive processing of long-distance structural integration.…”

“…Given that the processing of a doubly nested structure may be difficult for nonmusicans, only highly proficient musicians were included in our study. Although previous studies have found that both Western and Chinese nonmusicians exhibited specific neural responses to integrate tonally long-distance dependency, the musical sequences with doubly nested structure were barely used in their studies (e.g., Koelsch et al, 2013 ; Ma et al, 2018a , b ). Future studies should investigate whether nonmusicans can process musical tension induced by complex structures and the influence of musical training on such processing.…”

“…A priori sample size was calculated using G*power (G*power version 3.1.9.4), and the result indicated that a sample of 27 was required in our study to reach 90% power and for detecting an effect size of f = 0.30, with α = 0.05. The effect size was based on a previous study investigating the processing of nested structure in music (Ma et al, 2018a ). Therefore, we recruited 30 subjects for our experiment.…”