Rhythm histograms and musical meter: A corpus study of Malian percussion music

Can rhythm-mediated reward boost learning, memory, and social connection? Perspectives for future research

Studies of rhythm processing and of reward have progressed separately, with little connection between the two. However, consistent links between rhythm and reward are beginning to surface, with research suggesting that synchronization to rhythm is rewarding, and that this rewarding element may in turn also boost this synchronization. The current mini review shows that the combined study of rhythm and reward can be beneficial to better understand their independent and combined roles across two central aspects of cognition: 1) learning and memory, and 2) social connection and interpersonal synchronization; which have so far been studied largely independently. From this basis, it is discussed how connections between rhythm and reward can be applied to learning and memory and social connection across different populations, taking into account individual differences, clinical populations, human development, and animal research. Future research will need to consider the rewarding nature of rhythm, and that rhythm can in turn boost reward, potentially enhancing other cognitive and social processes.

Music in the brain

Music is ubiquitous across human cultures - as a source of affective and pleasurable experience, moving us both physically and emotionally - and learning to play music shapes both brain structure and brain function. Music processing in the brain - namely, the perception of melody, harmony and rhythm - has traditionally been studied as an auditory phenomenon using passive listening paradigms. However, when listening to music, we actively generate predictions about what is likely to happen next. This enactive aspect has led to a more comprehensive understanding of music processing involving brain structures implicated in action, emotion and learning. Here we review the cognitive neuroscience literature of music perception. We show that music perception, action, emotion and learning all rest on the human brain's fundamental capacity for prediction - as formulated by the predictive coding of music model. This Review elucidates how this formulation of music perception and expertise in individuals can be extended to account for the dynamics and underlying brain mechanisms of collective music making. This in turn has important implications for human creativity as evinced by music improvisation. These recent advances shed new light on what makes music meaningful from a neuroscientific perspective.

Genome-wide association study of musical beat synchronization demonstrates high polygenicity

Moving in synchrony to the beat is a fundamental component of musicality. Here we conducted a genome-wide association study to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with 69 loci reaching genome-wide significance (P < 5 × 10^-8) and single-nucleotide-polymorphism-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central-nervous-system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through separate experiments) and of the genome-wide association study (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations.

Mapping between sound, brain and behaviour: four-level framework for understanding rhythm processing in humans and non-human primates

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'.

Extreme precision in rhythmic interaction is enabled by role-optimized sensorimotor coupling: analysis and modelling of West African drum ensemble music

Human social interactions often involve carefully synchronized behaviours. Musical performance in particular features precise timing and depends on the differentiation and coordination of musical/social roles. Here, we study the influence of musical/social roles, individual musicians and different ensembles on rhythmic synchronization in Malian drum ensemble music, which features synchronization accuracy near the limits of human performance. We analysed 72 recordings of the same piece performed by four trios, in which two drummers in each trio systematically switched roles (lead versus accompaniment). Musical role, rather than individual or group differences, is the main factor influencing synchronization accuracy. Using linear causal modelling, we found a consistent pattern of bi-directional couplings between players, in which the direction and strength of rhythmic adaptation is asymmetrically distributed across musical roles. This differs from notions of musical leadership, which assume that ensemble synchronization relies predominantly on a single dominant personality and/or musical role. We then ran simulations that varied the direction and strength of sensorimotor coupling and found that the coupling pattern used by the Malian musicians affords nearly optimal synchronization. More broadly, our study showcases the importance of ecologically valid and culturally diverse studies of human behaviour. This article is part of the theme issue 'Synchrony and rhythm interaction: from the brain to behavioural ecology'.

An evolutionary theory of music needs to care about developmental timing

Both target papers cite evidence from infancy and early childhood to support the notion of human musicality as a somewhat static suite of capacities; however, in our view they do not adequately acknowledge the critical role of developmental timing, the acquisition process, or the dynamics of social learning, especially during later periods of development such as middle childhood.

Expectancy-based rhythmic entrainment as continuous Bayesian inference

When presented with complex rhythmic auditory stimuli, humans are able to track underlying temporal structure (e.g., a "beat"), both covertly and with their movements. This capacity goes far beyond that of a simple entrained oscillator, drawing on contextual and enculturated timing expectations and adjusting rapidly to perturbations in event timing, phase, and tempo. Previous modeling work has described how entrainment to rhythms may be shaped by event timing expectations, but sheds little light on any underlying computational principles that could unify the phenomenon of expectation-based entrainment with other brain processes. Inspired by the predictive processing framework, we propose that the problem of rhythm tracking is naturally characterized as a problem of continuously estimating an underlying phase and tempo based on precise event times and their correspondence to timing expectations. We present two inference problems formalizing this insight: PIPPET (Phase Inference from Point Process Event Timing) and PATIPPET (Phase and Tempo Inference). Variational solutions to these inference problems resemble previous "Dynamic Attending" models of perceptual entrainment, but introduce new terms representing the dynamics of uncertainty and the influence of expectations in the absence of sensory events. These terms allow us to model multiple characteristics of covert and motor human rhythm tracking not addressed by other models, including sensitivity of error corrections to inter-event interval and perceived tempo changes induced by event omissions. We show that positing these novel influences in human entrainment yields a range of testable behavioral predictions. Guided by recent neurophysiological observations, we attempt to align the phase inference framework with a specific brain implementation. We also explore the potential of this normative framework to guide the interpretation of experimental data and serve as building blocks for even richer predictive processing and active inference models of timing.

Perception of Nigerian Dùndún Talking Drum Performances as Speech-Like vs. Music-Like: The Role of Familiarity and Acoustic Cues

It seems trivial to identify sound sequences as music or speech, particularly when the sequences come from different sound sources, such as an orchestra and a human voice. Can we also easily distinguish these categories when the sequence comes from the same sound source? On the basis of which acoustic features? We investigated these questions by examining listeners’ classification of sound sequences performed by an instrument intertwining both speech and music: the dùndún talking drum. The dùndún is commonly used in south-west Nigeria as a musical instrument but is also perfectly fit for linguistic usage in what has been described as speech surrogates in Africa. One hundred seven participants from diverse geographical locations (15 different mother tongues represented) took part in an online experiment. Fifty-one participants reported being familiar with the dùndún talking drum, 55% of those being speakers of Yorùbá. During the experiment, participants listened to 30 dùndún samples of about 7s long, performed either as music or Yorùbá speech surrogate (n = 15 each) by a professional musician, and were asked to classify each sample as music or speech-like. The classification task revealed the ability of the listeners to identify the samples as intended by the performer, particularly when they were familiar with the dùndún, though even unfamiliar participants performed above chance. A logistic regression predicting participants’ classification of the samples from several acoustic features confirmed the perceptual relevance of intensity, pitch, timbre, and timing measures and their interaction with listener familiarity. In all, this study provides empirical evidence supporting the discriminating role of acoustic features and the modulatory role of familiarity in teasing apart speech and music.

Tapping Force Encodes Metrical Aspects of Rhythm

Humans possess the ability to extract highly organized perceptual structures from sequences of temporal stimuli. For instance, we can organize specific rhythmical patterns into hierarchical, or metrical, systems. Despite the evidence of a fundamental influence of the motor system in achieving this skill, few studies have attempted to investigate the organization of our motor representation of rhythm. To this aim, we studied-in musicians and non-musicians-the ability to perceive and reproduce different rhythms. In a first experiment participants performed a temporal order-judgment task, for rhythmical sequences presented via auditory or tactile modality. In a second experiment, they were asked to reproduce the same rhythmic sequences, while their tapping force and timing were recorded. We demonstrate that tapping force encodes the metrical aspect of the rhythm, and the strength of the coding correlates with the individual's perceptual accuracy. We suggest that the similarity between perception and tapping-force organization indicates a common representation of rhythm, shared between the perceptual and motor systems.

Neural and Behavioral Evidence for Frequency-Selective Context Effects in Rhythm Processing in Humans

When listening to music, people often perceive and move along with a periodic meter. However, the dynamics of mapping between meter perception and the acoustic cues to meter periodicities in the sensory input remain largely unknown. To capture these dynamics, we recorded the electroencephalography while nonmusician and musician participants listened to nonrepeating rhythmic sequences, where acoustic cues to meter frequencies either gradually decreased (from regular to degraded) or increased (from degraded to regular). The results revealed greater neural activity selectively elicited at meter frequencies when the sequence gradually changed from regular to degraded compared with the opposite. Importantly, this effect was unlikely to arise from overall gain, or low-level auditory processing, as revealed by physiological modeling. Moreover, the context effect was more pronounced in nonmusicians, who also demonstrated facilitated sensory-motor synchronization with the meter for sequences that started as regular. In contrast, musicians showed weaker effects of recent context in their neural responses and robust ability to move along with the meter irrespective of stimulus degradation. Together, our results demonstrate that brain activity elicited by rhythm does not only reflect passive tracking of stimulus features, but represents continuous integration of sensory input with recent context.

An Analysis of Rhythmic Patterns with Unsupervised Learning

This paper presents a model capable of learning the rhythmic characteristics of a music signal through unsupervised learning. The model learns a multi-layer hierarchy of rhythmic patterns ranging from simple structures on lower layers to more complex patterns on higher layers. The learned hierarchy is fully transparent, which enables observation and explanation of the structure of the learned patterns. The model employs tempo-invariant encoding of patterns and can thus learn and perform inference on tempo-varying and noisy input data. We demonstrate the model’s capabilities of learning distinctive rhythmic structures of different music genres using unsupervised learning. To test its robustness, we show how the model can efficiently extract rhythmic structures in songs with changing time signatures and live recordings. Additionally, the model’s time-complexity is empirically tested to show its usability for analysis-related applications.

A Probabilistic Model of Meter Perception: Simulating Enculturation

Enculturation is known to shape the perception of meter in music but this is not explicitly accounted for by current cognitive models of meter perception. We hypothesize that the induction of meter is a result of predictive coding: interpreting onsets in a rhythm relative to a periodic meter facilitates prediction of future onsets. Such prediction, we hypothesize, is based on previous exposure to rhythms. As such, predictive coding provides a possible explanation for the way meter perception is shaped by the cultural environment. Based on this hypothesis, we present a probabilistic model of meter perception that uses statistical properties of the relation between rhythm and meter to infer meter from quantized rhythms. We show that our model can successfully predict annotated time signatures from quantized rhythmic patterns derived from folk melodies. Furthermore, we show that by inferring meter, our model improves prediction of the onsets of future events compared to a similar probabilistic model that does not infer meter. Finally, as a proof of concept, we demonstrate how our model can be used in a simulation of enculturation. From the results of this simulation, we derive a class of rhythms that are likely to be interpreted differently by enculturated listeners with different histories of exposure to rhythms.