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Attention is not constant but rather fluctuates over time and these attentional fluctuations may prioritize the processing of certain events over others. In music listening, the pleasurable urge to move to music (termed 'groove' by music psychologists) offers a particularly convenient case study of oscillatory attention because it engenders synchronous and oscillatory movements which also vary predictably with stimulus complexity. In this study, we simultaneously recorded pupillometry and scalp electroencephalography (EEG) from participants while they listened to drumbeats of varying complexity that they rated in terms of groove afterwards. Using the intertrial phase coherence of the beat frequency, we found that while subjects were listening, their pupil activity became entrained to the beat of the drumbeats and this entrained attention persisted in the EEG even as subjects imagined the drumbeats continuing through subsequent silent periods. This entrainment in both the pupillometry and EEG worsened with increasing rhythmic complexity, indicating poorer sensory precision as the beat became more obscured. Additionally, sustained pupil dilations revealed the expected, inverted U-shaped relationship between rhythmic complexity and groove ratings. Taken together, this work bridges oscillatory attention to rhythmic complexity in relation to musical groove., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The ability to perceive the beat in music is crucial for both music listeners and players with expert musicians being notably skilled at noticing fine deviations in the beat. However, it is unclear whether this beat perception ability is enhanced in trained musicians who continue to practice relative to musicians who no longer play. Thus, we investigated this by comparing active musicians', inactive musicians', and nonmusicians' beat alignment ability scores on the Computerized Adaptive Beat Alignment Test (CA-BAT). 97 adults with diverse musical experience participated in the study, reporting their years of formal musical training, number of instruments played, hours of weekly music playing, and hours of weekly music listening, in addition to their demographic information. While initial tests between groups indicated active musicians outperformed inactive musicians and nonmusicians on the CA-BAT, a generalized linear regression analysis showed that there was no significant difference once differences in musical training had been accounted for. To ensure that our results were not impacted by multicollinearity between music-related variables, nonparametric and nonlinear machine learning regressions were employed and confirmed that years of formal musical training was the only significant predictor of beat alignment ability. These results suggest that expertly perceiving fine differences in the beat is not a use-dependent ability that degrades without regular maintenance through practice or musical engagement. Instead, better beat alignment appears to be associated with more musical training regardless of continued use., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Spiech, Endestad, Laeng, Danielsen and Haghish.)

Groove, understood as an enjoyable compulsion to move to musical rhythms, typically varies along an inverted U-curve with increasing rhythmic complexity (e.g., syncopation, pickups). Predictive coding accounts posit that moderate complexity drives us to move to reduce sensory prediction errors and model the temporal structure. While musicologists generally distinguish the effects of pickups (anacruses) and syncopations, their difference remains unexplored in groove. We used pupillometry as an index to noradrenergic arousal while subjects listened to and rated drumbeats varying in rhythmic complexity. We replicated the inverted U-shaped relationship between rhythmic complexity and groove and showed this is modulated by musical ability, based on a psychoacoustic beat perception test. The pupil drift rates suggest that groovier rhythms hold attention longer than ones rated less groovy. Moreover, we found complementary effects of syncopations and pickups on groove ratings and pupil size, respectively, discovering a distinct predictive process related to pickups. We suggest that the brain deploys attention to pickups to sharpen subsequent strong beats, augmenting the predictive scaffolding's focus on beats that reduce syncopations' prediction errors. This interpretation is in accordance with groove envisioned as an embodied resolution of precision-weighted prediction error., (© 2022. The Author(s).)

Visual working memory (VWM) is typically found to be severely limited in capacity, but this limitation may be ameliorated by providing familiar objects that are associated with knowledge stored in long-term memory. However, comparing meaningful and meaningless stimuli usually entails a confound, because different types of objects also tend to vary in terms of their inherent perceptual complexity. The current study therefore aimed to dissociate stimulus complexity from object meaning in VWM. To this end, identical stimuli - namely, simple color-shape conjunctions - were presented, which either resembled meaningful configurations ("real" European flags), or which were rearranged to form perceptually identical but meaningless ("fake") flags. The results revealed complexity estimates for "real" and "fake" flags to be higher than for unicolor baseline stimuli. However, VWM capacity for real flags was comparable to the unicolor baseline stimuli (and substantially higher than for fake flags). This shows that relatively complex, yet meaningful "real" flags reveal a VWM capacity that is comparable to rather simple, unicolored memory items. Moreover, this "nationality" benefit was related to individual flag recognition performance, thus showing that VWM depends on object knowledge., (© 2021. The Author(s).)