Inter-Subject EEG Correlation Reflects Time-Varying Engagement with Natural Music

Abstract

Musical engagement can be conceptualized through various activities, modes of listening, and listener states - among these a state of focused engagement. Recent research has reported that this state can be indexed by the inter-subject correlation (ISC) of EEG responses to a shared naturalistic stimulus. While statistically significant ISC has been reported during music listening, these reports have considered only correlations computed across entire excerpts and do not provide insights into time-varying engagement. Here we present the first EEG-ISC investigation of time-varying engagement within a musical work. From a sample of 23 adult musicians who listened to a cello concerto movement, we find varying levels of ISC throughout the excerpt. In particular, significant ISC is observed during periods of musical tension that build to climactic highpoints, but not at the highpoints themselves. In addition, we find that a control stimulus retaining low-frequency envelope characteristics of the intact music, but little other temporal structure, also elicits significant neural correlation, though to a lesser extent than the original. In all, our findings shed light on temporal dynamics of listener engagement during music listening, establish connections between salient musical events and EEG-ISC, and clarify specific listener states that are indexed by this measure.

Inter-Subject Correlation during New Music Listening: A Study of Electrophysiological and Behavioral Responses to Steve Reich’sPiano Phase

“…The topographies and coefficient significance for RC1 are in line with those computed in previous music EEG ISC studies (B. Kaneshiro et al, 2020Kaneshiro et al, , 2021; given that subsequent RCs did not correspond to significant ISC in a closely related study with similar distributions of coefficients (B. Kaneshiro et al, 2021), here we compute ISC only for RC1.…”

“…Comparing the present percentages of significant time-resolved ISCs for EEG data in RC1 with those reported by B. Kaneshiro et al (2021) shows that our highest EEG ISC (for Remix) eclipses their finding of 37% (in response to Elgar's cello concerto); our Original, Abrupt Change, and Segment Shuffle stimuli elicit higher percentages of significant ISC than their control condition (an envelope-scaled but otherwise temporally unstructured manipulation); and our Tremolo condition approximates the percentage found for their control condition (8%).…”

“…We followed the procedure of B. Kaneshiro et al (2021) to compute the EEG ISC of RC1 response vectors. First, we computed ISC across the entire duration of each stimulus.…”

“…The data preprocessing procedure used here is described in detail in B. Kaneshiro et al (2021). Briefly, data were preprocessed on a per-recording basis: Each recording was highpass (above 0.3 Hz), notch (between 59 and 61 Hz) and lowpass (below 50 Hz) zero-phase filtered before being downsampled from 1 kHz to 125 Hz.…”

“…We observed a sharp drop in RC coefficients after the first, most-correlated component (RC1); given that past research has reported negligible ISC in subsequent RCs in this scenario (B. Kaneshiro et al, 2021), we proceeded with ISC analyses using RC1 data only, as was done by B. Kaneshiro et al (2020).…”