INTRODUCTION:Aligning movements with external rhythms depends on temporal adaptation and anticipation, jointly captured by the ADaptation and Anticipation Model (ADAM). Cerebellar pathology disrupts these mechanisms during gradual tempo changes, but its role in synchronization under unpredictable rhythmic structure remains unclear. METHODS:Sixty-one participants (16 cerebellar, 45 controls) performed a finger-tapping task at 100 beats-per-minute with phase-shifts (±90°) or period-changes (±10%). Synchronization was assessed by quantifying asynchrony (mean, variability) and modeled with ADAM to estimate adaptation (phase, period correction), anticipation (temporal prediction, anticipatory error correction), and noise (timekeeper, motor). Mixed-effects ANOVAs assessed effects of group, stimulus, and perturbation type; regressions identified predictors of synchronization variability. RESULTS:Patients showed higher asynchrony variability. Both groups increased phase and period correction from baseline to perturbation (p < 0.001), with stronger changes for period than phase perturbations (p < 0.006). Controls corrected more to metronomes, yet patients engaged period correction for music (p = 0.009). Temporal prediction relied on weighed averaging of preceding intervals under perturbations (p = 0.008), more with music, and particularly in patients (p = 0.0095). Anticipatory error correction was higher for metronomes than music (p = 0.045) and for period-changes (p < 0.0001), with stimulus effects restricted to controls. Timekeeper and motor noise rose with perturbations (p < 0.0001) and strongly predicted synchronization variability. CONCLUSION:Period-changes engaged adaptation more than phase-shifts, and music elicited larger corrective responses than metronomes. Patients showed reduced phase correction for metronomes, greater reliance on period correction for music, and elevated timekeeper noise. Findings indicate that the cerebellum contributes to multiple components of adaptation and anticipation, offering insights for designing targeted rehabilitation.

This review integrates anthropological and neuroscientific perspectives to elucidate music-induced trance processes and their relevance to non-ordinary states of consciousness (NSCs). The objectives are to deepen the understanding of trance phenomena, delineate links across diverse trance expressions, and inform future neuroscientific research. Drawing on anthropological insights, we examine the phenomenology, reported benefits, and central role of music in trance-inducing practices. Examples ranging from traditional shamanism to contemporary rave culture reveal shared cultural narratives and highlight a common set of musical features that facilitate trance induction and maintenance across ritualistic and recreational contexts. On the neuroscientific front, we review brain imaging studies that map neural activity and connectivity during music-induced trance processes. Findings suggest that different forms of trance may engage partially overlapping neural dynamics, including increased synchronization in low-frequency bands and shifts from executive control networks to limbic and default mode networks. These patterns underline the dynamic interplay between cognitive, emotional, and sensory systems during trance, although the current empirical evidence remains fragmented and methodologically heterogeneous. Our interdisciplinary synthesis emphasizes trance as both a cultural and biological phenomenon and calls for future integration of phenomenological and neurophysiological data to build comprehensive models of music-induced NSCs.

Music is widely recognized for its ability to foster social bonding. Yet, while research has largely focused on interpersonal movement coordination, other ways in which music can connect people have received comparatively less attention. We argue that music-related social bonding extends beyond coordinated movement and emerges through multiple forms of imagined and shared social experience. We propose a conceptual framework comprising three interrelated pathways: interpersonal coordination, shared social experience without explicit behavioral coordination, and imagined social experience during solitary listening. Across these pathways, music recruits interacting mechanisms of temporal prediction, self-other integration, reward processing, and social-cognitive alignment that together promote social closeness, affiliation, and prosocial orientation. We further highlight how musical features and individual differences shape these processes. By integrating evidence from music psychology, cognitive neuroscience, and social psychology, this framework broadens current perspectives on how music promotes social bonding and identifies conceptual and methodological directions for future research.

Most people engage with music informally or through the standard school curriculum rather than through extensive professional practice, resulting in graded levels of accumulated musical training. In this study, we used cross-validated machine learning on whole-brain structural connectomes to investigate whether individual differences in brain wiring predict variation in musical training across 225 adults with none-to-moderate training levels. Connectomes were weighted by fiber bundle capacity (FBC), a quantitative diffusion MRI metric of structural connectivity. Musical training was quantified using the Gold-MSI Musical Training subscale (F3), a self-reported measure encompassing both formal and informal musical practice. Subcortical white-matter pathways linking thalamus, putamen, and pallidum with sensorimotor cortex carried the strongest predictive signal (r = 0.261; R2 = 0.068; p_perm = 0.003). Furthermore, this connectivity predicted the association between musical training and auditory perception skill, which was present in individuals with stronger subcortical-sensorimotor connectivity (+1 SD: β = 0.192, p = 0.004), but absent in those with weaker connectivity (-1 SD: β = -0.066, p = 0.488). Subcortical-sensorimotor connectivity is, therefore, the strongest structural correlate of graded musical training in non-specialists within the general population, identifying the structural neural substrate on which the training-skill association depends. This work warrants renewed targeted focus on subcortical circuits in models of musical expertise.

Predictions of content (“what”) and timing (“when”) have been widely investigated in both music and speech research. Considering that music and speech serve distinct communicative functions, predictions of content and timing, as well as their interplay, are likely to exhibit domain-specific characteristics. However, because these domains have largely been studied in isolation, the neural bases of content–timing interactions remain poorly understood. This review sets multiple objectives. The first is to provide an overview of how the neural correlates of content and timing predictions in music and speech have been investigated through the lenses of Predictive Coding and Dynamic Attending Theory. The second is to evaluate the extent to which these frameworks account for the interaction between content and timing predictions, particularly at a neurophysiological level. The third is to highlight points of convergence between the two frameworks that are often difficult to identify due to differences in nomenclature and research design. The fourth is to propose an integrative perspective through which methodological strengths from both research traditions can be complementarily implemented to further our understanding of the neural bases of content and timing predictions in music and speech, by considering different decisions that must be taken when investigating prediction in music and speech (stimulus, analysis, and interpretation decisions). Reconciling key aspects of these theoretical frameworks across multiple levels of description (i.e., computational, algorithmic, implementational) within music and speech processing can provide insights into prediction as a fundamental aspect of cognition.

Moving in unison to a musical beat can blur boundaries between individual movements, fostering prosociality. However, structured patterns of sounds and silences in rhythms (meter) allow various ways of moving to the beat. How do these different rhythmic interpretations affect social connectedness? Unacquainted dyads drummed in unison, and at more complex integer multiple and polyrhythmic ratios. Coordination requires continuously tracking who does what and when. We varied trackability by manipulating task-sharing (the same or separate drum pads, and audible or inaudible partner drumming). More complex ratios decreased social connectedness. However, coordination revealed a dichotomy between unison and the more complex ratios: in unison drumming, participants automatically tracked and adjusted to each other's actions, but both integer multiples and polyrhythms separated the two participants' actions in time, allowing one to be stable despite their partner being variable. Hearing each other increased participants' mutual reliance on each other's actions, but by itself did not increase connectedness. However, sharing a drum pad and audio significantly boosted self-other merging ratings. Notably, more stable coordination facilitated integrated self-other representations. Our findings are consistent with the premise that meter provides a shared cognitive-motor scaffold that enables group cohesion, while simultaneously allowing individual expression through multi-part rhythm production.

Coordinating actions with others is essential for successful social interaction. Such coordination, as in sports and musical performances, often relies on sound, requiring the brain to process and integrate acoustic information related to the actions of 'self' and 'other' while maintaining sufficient distinction between them. However, such self-other differentiation can be challenged during real-world auditory interactions due to self and other signals being mixed when arriving at the eardrum, creating the potential for agency confusion and impaired coordination. Here we combined dual-EEG and frequency tagging techniques to investigate the behavioural and brain mechanisms supporting the self-other distinction during a joint auditory-motor synchronisation task. Twenty-five dyads synchronised self-paced, finger pressure-controlled continuous sound modulations. The results revealed better synchronisation when participants were associated with distinct sounds (different frequency and brightness) and designated leadership roles, facilitating the processing of self and other information and their separation at both peripheral and central levels. The results also indicated that this neural facilitation was stronger in the right hemisphere than the left, as well as for self than other, suggesting critical roles of spectral information and control over one's own actions for auditory self-other distinction and coordination. These findings highlight complementary behavioural and brain mechanisms compensating for self-other masking inherent to auditory interactions, opening new avenues to understanding interpersonal coordination and its disorders.

Experiencing music often entails the perception of a periodic beat. Despite being a widespread phenomenon across cultures, the nature and neural underpinnings of beat perception remain largely unknown. In the last decade, there has been a growing interest in developing methods to probe these processes, particularly to measure the extent to which beat-related information is contained in behavioral and neural responses. Here, we propose a theoretical framework and practical implementation of an analytic approach to capture beat-related periodicity in empirical signals using frequency-tagging. We highlight its sensitivity in measuring the extent to which the periodicity of a perceived beat is represented in a range of continuous time-varying signals with minimal assumptions. We also discuss a limitation of this approach with respect to its specificity when restricted to measuring beat-related periodicity only from the magnitude spectrum of a signal, and introduce a novel extension of the approach based on autocorrelation to overcome this issue. We test the new autocorrelation-based method using simulated signals and by re-analyzing previously published data, and show how it can be used to process measurements of brain activity as captured with surface EEG in adults and infants in response to rhythmic inputs. Taken together, the theoretical framework and related methodological advances confirm and elaborate the frequency-tagging approach as a promising window into the processes underlying beat perception and, more generally, temporally coordinated behaviors.

During ensemble performance, musicians predict their own and their partners’ action outcomes to smoothly coordinate in real time. The neural auditory-motor system is thought to contribute to these predictions by running internal forward models that simulate self- and other-produced actions slightly ahead of time. What remains elusive, however, is whether and how own and partner actions can be represented simultaneously and distinctively in the sensorimotor system, and whether these representations are content-specific. Here, we applied multivariate pattern analysis (MVPA) to functional magnetic resonance imaging (fMRI) data of duetting pianists to dissociate the neural representation of self- and other-produced actions during synchronous joint music performance. Expert pianists played familiar right-hand melodies in a 3 T MR-scanner, in duet with a partner who played the corresponding left-hand basslines in an adjacent room. In half of the pieces, pianists were motorically familiar (or unfamiliar) with their partner’s left-hand part. MVPA was applied in primary motor and premotor cortices (M1, PMC), cerebellum, and planum temporale of both hemispheres to classify which piece was performed. Classification accuracies were higher in left than right M1, reflecting the content-specific neural representation of self-produced right-hand melodies. Notably, PMC showed the opposite lateralization, with higher accuracies in the right than left hemisphere, likely reflecting the content-specific neural representation of other-produced left-hand basslines. Direct physiological support for the representational alignment of partners’ M1 and PMC should be gained in future studies using novel tools like interbrain representational similarity analyses. Surprisingly, motor representations in PMC were similarly precise irrespective of familiarity with the partner’s part. This suggests that expert pianists may generalize contents of familiar actions to unfamiliar pieces with similar musical structure, based on the auditory perception of the partner’s part. Overall, these findings support the notion of parallel, distinct, and content-specific self and other internal forward models that are integrated within cortico-cerebellar auditory-motor networks to support smooth coordination in musical ensemble performance and possibly other forms of social interaction.

Developments in cognitive neuroscience have led to the emergence of hyperscanning, the simultaneous measurement of brain activity from multiple people. Hyperscanning is useful for investigating social cognition, including joint action, because of its ability to capture neural processes that occur within and between people as they coordinate actions toward a shared goal. Here, we provide a practical guide for researchers considering using hyperscanning to study joint action and seeking to avoid frequently raised concerns from hyperscanning skeptics. We focus specifically on Electroencephalography (EEG) hyperscanning, which is widely available and optimally suited for capturing fine-grained temporal dynamics of action coordination. Our guidelines cover questions that are likely to arise when planning a hyperscanning project, ranging from whether hyperscanning is appropriate for answering one's research questions to considerations for study design, dependent variable selection, data analysis and visualization. By following clear guidelines that facilitate careful consideration of the theoretical implications of research design choices and other methodological decisions, joint action researchers can mitigate interpretability issues and maximize the benefits of hyperscanning paradigms.

Why are some individuals more musical than others? Neither cognitive testing nor classical localizationist neuroscience alone can provide a complete answer. Here, we test how the interplay of brain network organization and cognitive function delivers graded perceptual abilities in a distinctively human capacity. We analyze multimodal magnetic resonance imaging, cognitive, and behavioral data from 200+ participants, focusing on a canonical working memory network encompassing prefrontal and posterior parietal regions. Using graph theory, we examine structural and functional frontoparietal network organization in relation to assessments of musical aptitude and experience. Results reveal a positive correlation between perceptual abilities and the integration efficiency of key frontoparietal regions. The linkage between functional networks and musical abilities is mediated by working memory processes, whereas structural networks influence these abilities through sensory integration. Our work lays the foundation for future investigations into the neurobiological roots of individual differences in musicality.

Periodicity is a fundamental property of biological systems, including human movement systems. Periodic movements support displacements of the body in the environment as well as interactions and communication between individuals. Here, we use electroencephalography (EEG) to investigate the neural tracking of visual periodic motion, and more specifically, the relevance of spatiotemporal information contained at and between their turning points. We compared EEG responses to visual sinusoidal oscillations versus nonlinear Rayleigh oscillations, which are both typical of human movements. These oscillations contain the same spatiotemporal information at their turning points but differ between turning points, with Rayleigh oscillations having an earlier peak velocity, shown to increase an individual's capacity to produce accurately synchronized movements. EEG analyses highlighted the relevance of spatiotemporal information between the turning points by showing that the brain precisely tracks subtle differences in velocity profiles, as indicated by earlier EEG responses for Rayleigh oscillations. The results suggest that the brain is particularly responsive to velocity peaks in visual periodic motion, supporting their role in conveying behaviorally relevant timing information at a neurophysiological level. The results also suggest key functions of neural oscillations in the Alpha and Beta frequency bands, particularly in the right hemisphere. Together, these findings provide insights into the neural mechanisms underpinning the processing of visual periodic motion and the critical role of velocity peaks in enabling proficient visuomotor synchronization.

Human interaction often requires the precise yet flexible interpersonal coordination of rhythmic behavior, as in group music making. The present fMRI study investigates the functional brain networks that may facilitate such behavior by enabling temporal adaptation (error correction), prediction, and the monitoring and integration of information about 'self' and the external environment. Participants were required to synchronize finger taps with computer-controlled auditory sequences that were presented either at a globally steady tempo with local adaptations to the participants' tap timing (Virtual Partner task) or with gradual tempo accelerations and decelerations but without adaptation (Tempo Change task). Connectome-based predictive modelling was used to examine patterns of brain functional connectivity related to individual differences in behavioral performance and parameter estimates from the adaptation and anticipation model (ADAM) of sensorimotor synchronization for these two tasks under conditions of varying cognitive load. Results revealed distinct but overlapping brain networks associated with ADAM-derived estimates of temporal adaptation, anticipation, and the integration of self-controlled and externally controlled processes across task conditions. The partial overlap between ADAM networks suggests common hub regions that modulate functional connectivity within and between the brain's resting-state networks and additional sensory-motor regions and subcortical structures in a manner reflecting coordination skill. Such network reconfiguration might facilitate sensorimotor synchronization by enabling shifts in focus on internal and external information, and, in social contexts requiring interpersonal coordination, variations in the degree of simultaneous integration and segregation of these information sources in internal models that support self, other, and joint action planning and prediction.

A growing body of research has been studying cognitive benefits that arise from music training in childhood or adulthood. Many studies focus specifically on the cognitive transfer of music training to language skill, with the aim of preventing language deficits and disorders and improving speech. However, predicted transfer effects are not always documented and not all findings replicate. While we acknowledge the important work that has been done in this field, we highlight the limitations of the persistent dichotomy between musicians and nonmusicians and argue that future research would benefit from a movement towards skill-based continua of musicianship instead of the currently widely practiced dichotomization of participants into groups of musicians and nonmusicians. Culturally situated definitions of musicianship as well as higher awareness of language diversity around the world are key to the understanding of potential cognitive transfers from music to language (and back). We outline a gradient approach to the study of the musical mind and suggest the next steps that could be taken to advance the field.

Movement dataset reviews exist but are limited in coverage, both in terms of size and research discipline. While topic-specific reviews clearly have their merit, it is critical to have a comprehensive overview based on a systematic survey across disciplines. This enables higher visibility of datasets available to the research communities and can foster interdisciplinary collaborations. We present a catalogue of 704 open datasets described by 10 variables that can be valuable to researchers searching for secondary data: name and reference, creation purpose, data type, annotations, source, population groups, ordinal size of people captured simultaneously, URL, motion capture sensor, and funders. The catalogue is available in the supplementary materials. We provide an analysis of the datasets and further review them under the themes of human diversity, ecological validity, and data recorded. The resulting 12-dimension framework can guide researchers in planning the creation of open movement datasets. This work has been the interdisciplinary effort of researchers across affective computing, clinical psychology, disability innovation, ethnomusicology, human-computer interaction, machine learning, music cognition, music computing, and movement neuroscience.

In small musical groups, performers can seem to coordinate their movements almost effortlessly in remarkable exhibits of joint action and entrainment. To achieve a common musical goal, co-performers interact and communicate using non-verbal means such as upper-body movements, and particularly head motion. Studying these phenomena in naturalistic contexts can be challenging since most techniques make use of motion capture technologies that can be intrusive and costly. To investigate an alternative method, we analyze video recordings of a professional instrumental ensemble by extracting trajectory information using pose estimation algorithms. We examine Kansei perspectives such as the analysis of non-verbal expression conveyed by bodily movements and gestures, and test for causal relationships and directed influence between performers using the Granger Causality method. We compute weighted probabilities representing the likelihood that each performer Granger Causes co-performers’ movements. Effects of different aspects of musical textures were examined and results indicated stronger directionality for homophonic textures (clear melodic leader) than polyphonic (ambiguous leadership).

Humans perceive and spontaneously move to one or several levels of periodic pulses (a meter, for short) when listening to musical rhythm, even when the sensory input does not provide prominent periodic cues to their temporal location. Here, we review a multi-levelled framework to understanding how external rhythmic inputs are mapped onto internally represented metric pulses. This mapping is studied using an approach to quantify and directly compare representations of metric pulses in signals corresponding to sensory inputs, neural activity and behaviour (typically body movement). Based on this approach, recent empirical evidence can be drawn together into a conceptual framework that unpacks the phenomenon of meter into four levels. Each level highlights specific functional processes that critically enable and shape the mapping from sensory input to internal meter. We discuss the nature, constraints and neural substrates of these processes, starting with fundamental mechanisms investigated in macaque monkeys that enable basic forms of mapping between simple rhythmic stimuli and internally represented metric pulse. We propose that human evolution has gradually built a robust and flexible system upon these fundamental processes, allowing more complex levels of mapping to emerge in musical behaviours. This approach opens promising avenues to understand the many facets of rhythmic behaviours across individuals and species. This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.

Interpersonal coordination is exemplified in ensemble musicians, who coordinate their actions deliberately in order to achieve temporal synchronisation in their performances. However, musicians also move parts of their bodies unintentionally or spontaneously, sometimes in ways that do not directly produce sound from their instruments. Musicians' movements—intentional or otherwise—provide visual signals to co-performers, which might facilitate temporal synchronisation. In large ensembles, a conductor also provides a visual cue, which has been shown to enhance synchronisation. In the present study, we tested how visual cues from a co-performer and a conductor affect processes of temporal anticipation, synchronisation, and ancillary movements in a sample of primarily non-musicians. We used a dyadic synchronisation drumming task, in which paired participants drummed to the beat of tempo-changing music. We manipulated visual access between partners and a virtual conductor. Results showed that the conductor improved synchronisation with the music, but synchrony with the music did not improve when partners could see each other. Temporal prediction was improved when partners saw the conductor, but not each other. Ancillary movements of the head were more synchronised between partners when they could see each other, and greater ancillary synchrony at beat-related frequencies of movement was associated with greater drumming synchrony. These results suggest that compatible audio-visual cues can improve intentional synchronisation, that ancillary movements are affected by seeing a partner, and that attended vs. incidental visual cues thus have partially dissociable effects on temporal coordination during joint action.