Why do humans make music? Theories of the evolution of musicality have focused mainly on the value of music for specific adaptive contexts such as mate selection, parental care, coalition signaling, and group cohesion. Synthesizing and extending previous proposals, we argue that social bonding is an overarching function that unifies all of these theories, and that musicality enabled social bonding at larger scales than grooming and other bonding mechanisms available in ancestral primate societies. We combine cross-disciplinary evidence from archeology, anthropology, biology, musicology, psychology, and neuroscience into a unified framework that accounts for the biological and cultural evolution of music. We argue that the evolution of musicality involves gene-culture coevolution, through which proto-musical behaviors that initially arose and spread as cultural inventions had feedback effects on biological evolution because of their impact on social bonding. We emphasize the deep links between production, perception, prediction, and social reward arising from repetition, synchronization, and harmonization of rhythms and pitches, and summarize empirical evidence for these links at the levels of brain networks, physiological mechanisms, and behaviors across cultures and across species. Finally, we address potential criticisms and make testable predictions for future research, including neurobiological bases of musicality and relationships between human music, language, animal song, and other domains. The music and social bonding hypothesis provides the most comprehensive theory to date of the biological and cultural evolution of music.

/pdf/music-as-a-coevolved-system-for-social-bonding-59cxv3huzt.pdf

Music as a coevolved system for social bonding

Biological and artificial information processing systems form representations that they can use to categorize, reason, plan, navigate, and make decisions. How can we measure the extent to which the representations formed by these diverse systems agree? Do similarities in representations then translate into similar behavior? How can a system's representations be modified to better match those of another system? These questions pertaining to the study of representational alignment are at the heart of some of the most active research areas in cognitive science, neuroscience, and machine learning. For example, cognitive scientists measure the representational alignment of multiple individuals to identify shared cognitive priors, neuroscientists align fMRI responses from multiple individuals into a shared representational space for group-level analyses, and ML researchers distill knowledge from teacher models into student models by increasing their alignment. Unfortunately, there is limited knowledge transfer between research communities interested in representational alignment, so progress in one field often ends up being rediscovered independently in another. Thus, greater cross-field communication would be advantageous. To improve communication between these fields, we propose a unifying framework that can serve as a common language between researchers studying representational alignment. We survey the literature from all three fields and demonstrate how prior work fits into this framework. Finally, we lay out open problems in representational alignment where progress can benefit all three of these fields. We hope that our work can catalyze cross-disciplinary collaboration and accelerate progress for all communities studying and developing information processing systems. We note that this is a working paper and encourage readers to reach out with their suggestions for future revisions. 

Getting aligned on representational alignment

https://doi.org/10.1016/j.cognition.2022.105205

Aesthetics of musical timing: Culture and expertise affect preferences for isochrony but not synchrony

https://doi.org/10.1016/j.cub.2023.02.070

Large-scale iterated singing experiments reveal oral transmission mechanisms underlying music evolution

Abstract Sensorimotor synchronization (SMS), the rhythmic coordination of perception and action, is a fundamental human skill that supports many behaviors, including music and dance (Repp, 2005; Repp &amp; Su, 2013). Traditionally, SMS experiments have been performed in the laboratory using finger tapping paradigms, and have required equipment with high temporal fidelity to capture the asynchronies between the time of the tap and the corresponding cue event. Thus, SMS is particularly challenging to study with online research, where variability in participants’ hardware and software can introduce uncontrolled latency and jitter into recordings. Here we present REPP (Rhythm ExPeriment Platform), a novel technology for measuring SMS in online experiments that can work efficiently using the built-in microphone and speakers of standard laptop computers. In a series of calibration and behavioral experiments, we demonstrate that REPP achieves high temporal accuracy (latency and jitter within 2 ms on average), high test-retest reliability both in the laboratory ( r = .87) and online ( r = .80), and high concurrent validity ( r = .94). We also show that REPP is fully automated and customizable, enabling researchers to monitor experiments in real time and to implement a wide variety of SMS paradigms. We discuss online methods for ensuring high recruiting efficiency and data quality, including pre-screening tests and automatic procedures for quality monitoring. REPP can therefore open new avenues for research on SMS that would be nearly impossible in the laboratory, reducing experimental costs while massively increasing the reach, scalability, and speed of data collection. 

/pdf/repp-a-robust-cross-platform-solution-for-online-1k3sr61w.pdf

REPP: A robust cross-platform solution for online sensorimotor synchronization experiments

Music is present in every known society, yet varies from place to place. What is universal to the perception of music? We measured a signature of mental representations of rhythm in 923 participants from 39 participant groups in 15 countries across 5 continents, spanning urban societies, indigenous populations, and online participants. Listeners reproduced random ‘‘seed’’ rhythms; their reproductions were fed back as the stimulus (as in the game of “telephone”), such that their biases (the prior) could be estimated from the distribution of reproductions. Every tested group showed a prior with peaks at integer ratio rhythms, suggesting that discrete rhythm “categories” at small integer ratios are universal. The occurrence and relative importance of different integer ratio categories varied across groups, often reflecting local musical systems. However, university students and online participants in non-Western countries tended to resemble Western participants, underrepresenting the variability otherwise evident across cultures. The results suggest the universality of discrete mental representations of music while showing their interaction with culture-specific traditions.

/pdf/universality-and-cross-cultural-variation-in-mental-1fan11rmsq.pdf

Universality and cross-cultural variation in mental representations of music revealed by global comparison of rhythm priors

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Universality and cross-cultural variation in mental representations of music revealed by global comparison of rhythm priors