Studying the effect of oral transmission on melodic structure using online iterated singing experiments

ince generations, singing and speech have been mainly transmitted orally. How does oral transmission shape the evolution of music? Here, we developed a method for conducting online transmission experiments, in which sung melodies are passed from one singer to the next. We show that cognitive and motor constraints play a profound role in the emergence of melodic structure. Specifically, initially random tones develop into more structured systems that increasingly reuse and combine fewer elements, making melodies easier to learn and transmit over time. We discuss how our findings are compatible with melodic universals found in most human cultures and culturally specific characteristics of participants' previous musical exposure. Overall, our method efficiently automates online singing experiments while enabling large-scale data collection using standard computers available to everyone. We see great potential in further extending this work to increase the efficiency, scalability, and diversity of research on cultural evolution and cognitive science

Visualizing Music Psychology: A Bibliometric Analysis of Psychology of Music, Music Perception, and Musicae Scientiae from 1973 to 2017

Music psychology has grown drastically since being established in the middle of the 19th century. However, until now, no large-scale computational bibliometric analysis of the scientific literature in music psychology has been carried out. This study aims to analyze all published literature from the journals Psychology of Music, Music Perception, and Musicae Scientiae. The retrieved literature comprised a total of 2,089 peer-reviewed articles, 2,632 authors, and 49 countries. Visualization and bibliometric techniques were used to investigate the growth of publications, citation analysis, author and country productivity, collaborations, and research trends. From 1973 to 2017, with a total growth rate of 11%, there is a clear increase in music psychology research (i.e., number of publications, authors, and collaborations), consistent with the general growth observed in science. The retrieved documents received a total of 33,771 citations ( M = 16.17, SD = 26.93), with a median (Q1—Q3) of 7 (2—20). Different bibliometric indicators defined the most relevant authors, countries, and keywords as well as how they relate and collaborate with each other. Differences between the three journals are also discussed. This type of analysis, not without its limitations, can help understand music psychology and identify future directions within the field

Gibbs sampling with people

A core problem in cognitive science and machine learning is to understand how humans derive semantic representations from perceptual objects, such as color from an apple, pleasantness from a musical chord, or seriousness from a face. Markov Chain Monte Carlo with People (MCMCP) is a prominent method for studying such representations, in which participants are presented with binary choice trials constructed such that the decisions follow a Markov Chain Monte Carlo acceptance rule. However, while MCMCP has strong asymptotic properties, its binary choice paradigm generates relatively little information per trial, and its local proposal function makes it slow to explore the parameter space and find the modes of the distribution. Here we therefore generalize MCMCP to a continuous-sampling paradigm, where in each iteration the participant uses a slider to continuously manipulate a single stimulus dimension to optimize a given criterion such as 'pleasantness'. We formulate both methods from a utility-theory perspective, and show that the new method can be interpreted as 'Gibbs Sampling with People' (GSP). Further, we introduce an aggregation parameter to the transition step, and show that this parameter can be manipulated to flexibly shift between Gibbs sampling and deterministic optimization. In an initial study, we show GSP clearly outperforming MCMCP; we then show that GSP provides novel and interpretable results in three other domains, namely musical chords, vocal emotions, and faces. We validate these results through large-scale perceptual rating experiments. The final experiments use GSP to navigate the latent space of a state-of-the-art image synthesis network (StyleGAN), a promising approach for applying GSP to high-dimensional perceptual spaces. We conclude by discussing future cognitive applications and ethical implications

Gibbs sampling with people

A core problem in cognitive science and machine learning is to understand how humans derive semantic representations from perceptual objects, such as color from an apple, pleasantness from a musical chord, or seriousness from a face. Markov Chain Monte Carlo with People (MCMCP) is a prominent method for studying such representations, in which participants are presented with binary choice trials constructed such that the decisions follow a Markov Chain Monte Carlo acceptance rule. However, while MCMCP has strong asymptotic properties, its binary choice paradigm generates relatively little information per trial, and its local proposal function makes it slow to explore the parameter space and find the modes of the distribution. Here we therefore generalize MCMCP to a continuous-sampling paradigm, where in each iteration the participant uses a slider to continuously manipulate a single stimulus dimension to optimize a given criterion such as 'pleasantness'. We formulate both methods from a utility-theory perspective, and show that the new method can be interpreted as 'Gibbs Sampling with People' (GSP). Further, we introduce an aggregation parameter to the transition step, and show that this parameter can be manipulated to flexibly shift between Gibbs sampling and deterministic optimization. In an initial study, we show GSP clearly outperforming MCMCP; we then show that GSP provides novel and interpretable results in three other domains, namely musical chords, vocal emotions, and faces. We validate these results through large-scale perceptual rating experiments. The final experiments use GSP to navigate the latent space of a state-of-the-art image synthesis network (StyleGAN), a promising approach for applying GSP to high-dimensional perceptual spaces. We conclude by discussing future cognitive applications and ethical implications

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

Commonality and variation in mental representations of music revealed by a cross-cultural comparison of rhythm priors in 15 countries

Music is present in every known society but varies from place to place. What, if anything, is universal to music cognition? We measured a signature of mental representations of rhythm in 39 participant groups in 15 countries, spanning urban societies and Indigenous populations. 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 sparse prior with peaks at integer-ratio rhythms. However, the importance of different integer ratios varied across groups, often reflecting local musical practices. Our results suggest a common feature of music cognition: discrete rhythm 'categories' at small-integer ratios. These discrete representations plausibly stabilize musical systems in the face of cultural transmission but interact with culture-specific traditions to yield the diversity that is evident when mental representations are probed across many cultures. [Abstract copyright: © 2024. The Author(s).

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

Both music and language are found in all known human societies, yet no studies have compared similarities and differences between song, speech, and instrumental music on a global scale. In this Registered Report, we analyzed two global datasets: (i) 300 annotated audio recordings representing matched sets of traditional songs, recited lyrics, conversational speech, and instrumental melodies from our 75 coauthors speaking 55 languages; and (ii) 418 previously published adult-directed song and speech recordings from 209 individuals speaking 16 languages. Of our six preregistered predictions, five were strongly supported: Relative to speech, songs use (i) higher pitch, (ii) slower temporal rate, and (iii) more stable pitches, while both songs and speech used similar (iv) pitch interval size and (v) timbral brightness. Exploratory analyses suggest that features vary along a “musi-linguistic” continuum when including instrumental melodies and recited lyrics. Our study provides strong empirical evidence of cross-cultural regularities in music and speech

Globally, songs and instrumental melodies are slower, higher, and use more stable pitches than speech: a registered report

Both music and language are found in all known human societies, yet no studies have compared similarities and differences between song, speech, and instrumental music on a global scale. In this Registered Report, we analyzed two global datasets: (i) 300 annotated audio recordings representing matched sets of traditional songs, recited lyrics, conversational speech, and instrumental melodies from our 75 coauthors speaking 55 languages; and (ii) 418 previously published adult-directed song and speech recordings from 209 individuals speaking 16 languages. Of our six preregistered predictions, five were strongly supported: Relative to speech, songs use (i) higher pitch, (ii) slower temporal rate, and (iii) more stable pitches, while both songs and speech used similar (iv) pitch interval size and (v) timbral brightness. Exploratory analyses suggest that features vary along a “musi-linguistic” continuum when including instrumental melodies and recited lyrics. Our study provides strong empirical evidence of cross-cultural regularities in music and speech

Visualizing Music Psychology: A Bibliometric Analysis of Psychology of Music, Music Perception, and Musicae Scientiae from 1973 to 2017

Music psychology has grown drastically since being established in the middle of the 19th century. However, until now, no large-scale computational bibliometric analysis of the scientific literature in music psychology has been carried out. This study aims to analyze all published literature from the journals Psychology of Music, Music Perception, and Musicae Scientiae. The retrieved literature comprised a total of 2,089 peer-reviewed articles, 2,632 authors, and 49 countries. Visualization and bibliometric techniques were used to investigate the growth of publications, citation analysis, author and country productivity, collaborations, and research trends. From 1973 to 2017, with a total growth rate of 11%, there is a clear increase in music psychology research (i.e., number of publications, authors, and collaborations), consistent with the general growth observed in science. The retrieved documents received a total of 33,771 citations (M 1⁄4 16.17, SD 1⁄4 26.93), with a median (Q1—Q3) of 7 (2—20). Different bibliometric indicators defined the most relevant authors, countries, and keywords as well as how they relate and collaborate with each other. Differences between the three journals are also discussed. This type of analysis, not without its limitations, can help understand music psychology and identify future directions within the field

What counts as Aaesthetics in science? A bibliometric analysis and visualization of the scientific literature from 1970 to 2018

Many scientific disciplines give rise to research published under the moniker of aesthetics. For instance, both psychology and neuroscience have highly active subfields focused on aesthetics research, known as empirical aesthetics and neuroaesthetics. However, it remains unclear what aesthetics is about, and, consequently, if aesthetics research pursued by different scientific disciplines addresses common problems. It is, therefore, difficult to assess how well aesthetics is doing as a scientific enterprise, identify and compare its main subfields, and quantify its productivity. To give an unbiased account of what counts as aesthetics across scientific disciplines, we conducted a bibliometric analysis of every publication found in Web of Science tagged as aesthetics. Spanning, 1970 to 2018, the retrieved literature comprised a total of 27,159 papers, 45,832 authors, and 123 countries. Visualization and bibliometric techniques were used to investigate the main research trends and subfields, growth of publications, citation analysis, and country productivity and collaborations. From 1970 to 2018, there was a clear increase in aesthetics research over time, with a stronger growth in recent years. The retrieved documents received a total of 217,931 citations, with a mean of 8.02 citations per document (SD = 25.7). Both a cluster analysis of the data, and a comparative analysis a posteriori, revealed that the aesthetics literature clusters into distinct research areas that differ significantly in their object of interest, research productivity and impact. This finding suggests that aesthetics is better thought of as a confederate of research traditions than a whole unified by common problems and research strategies