The MMC Lab has currently three primary lines of investigation:
1. Studying human cognition through large-scale online experiments
Conducting research in the lab is time-consuming and costly. Consequently, lab experiments have typically suffered from a limited scale – e.g., small sample sizes, limited experimental manipulations - and generalizability – e.g., over-relying on Western university student participants, a rather unrepresentative sample.
Online behavioural research provides a promising way forward. Specifically, online research enables social and psychological experiments that would be nearly impossible in the lab by massively increasing the reach, scalability, and diversity of data collection. A key line of investigation in the MMC Lab is to develop paradigms capable to measure human behaviour using sophisticated production modalities online (e.g., tapping, singing, or speech), allowing us to run high-powered psychology studies with participants from all over the world.
- In this study, published in Behaviour Research Methods, we developed a novel technology that allows researchers to run high-precision sensorimotor synchronization studies (e.g., tapping to the beat of the music) through the web browser. Traditionally, such experiments could only be run effectively using specialist hardware in the laboratory. By making this technology viable online, we make it possible to collect sophisticated production data (e.g., tapping) from thousands of participants around the world in the space of hours. The technology is freely available here.
- In this study, published in Advances in Neural Information Processing Systems (NeurIPS 2020), and led by researchers in the Computational Auditory Perception Group, we developed a new method to measure mental representations with high resolution in several stimulus domains (e.g., colour, musical chords, speech, faces), collecting data online in 25 behavioural experiments with 5,179 human participants.
2. Cultural Evolution and Collective Cognition
Complex cultural traits, such as language and music, do not result only from individual brains, but also from being embedded in larger cultural processes of social interactions at the population level. For example, human song has been transmitted orally for countless human generations, changing over time under the influence of biological, cognitive, and cultural factors.
To explore how cultural transmission shapes the evolution of music and aesthetic creations, we examine cultural evolution artificially by running large-scale transmission chain experiments using sophisticated production modalities, such as tapping or singing. In this paradigm, artistic creations (e.g., rhythms, songs, paintings) are passed from one participant to the next. Over time, participants’ reproduction errors get amplified, allowing us to study how structural regularities and diversity emerge from the process of transmission. This paradigm can be extended in various exciting directions, such as exploring cultural transmission within evolving social networks, or other production modalities, including speech or gesture.
- In this study, published in the Current Biology, we developed an automatic online pipeline that streamlines large-scale cultural transmission experiments in the singing modality. We quantified the evolution of 3,424 melodies orally transmitted across 1,797 participants in the United States and India. We then ran a series of followup experiments to study the causal role of human transmission mechanism. The results showed that collective music evolution depends on a compromise between individual participant biases – biological, cognitive, cultural factors – and social dynamics that occur during cultural transmission. Overall, these results provide a new understanding into how cross-cultural similarities and differences in human song structures emerge via cultural transmission.
- In this study, led by Nori Jacoby, we applied our novel technology to perform online sensorimotor synchronization experiments to run large-scale iterated learning paradigms with finger tapping, where rhythms are transmitted across participants by tapping. This allowed us to measure rhythm perception and production in online participants from the US, India, and Brazil.
We also use methods from data science and computational sociology to study cultural processes by collecting and analysing real-world patterns of cultural consumption at a large scale. For example, using large music datasets available from audio streaming services (e.g., Spotify, Apple Music, YouTube, TikTok) to study the impact of globalization on the evolution of music and aesthetic cultures around the world, or to characterize cross-cultural similarities and differences in aesthetic practices and products.
3. Empirical Aesthetics, Social Norms, and Popularity Dynamics
How do we experience beauty? What are the main principles underlying popularity and fashion? The MCC Lab is interested in both the cognitive and cultural foundations of sensory valuation and aesthetic experience, in particular of complex and abstract stimuli such as music and art. One way in which we study aesthetic judgements and decisions is by running controlled psychological experiments in the lab, manipulating certain properties of the aesthetic product or the context in which it is presented, and measuring quantitatively participants’ responses to it. We also use big data and machine learning techniques to study large-scale music consumption behaviour in the real world, such as measuring how changes in musical features from popular songs may change over time due to psychological changes at the population level or prevailing environmental factors. See for example a list of selected publications on these topics:
- Anglada-Tort, M., Lee, H., Krause, A. E., & North, A. C. (2023). Here comes the sun: music features of popular songs reflect prevailing weather conditions. Royal Society Open Science, 10, 221443. https://doi.org/10.1098/rsos.221443
- Anglada-Tort, M., Masters, N., Steffens, J., North, A., & Müllensiefen, D. (2022). The Behavioural Economics of Music: Systematic review and future directions. Quarterly Journal of Experimental Psychology, 0(0). Doi: https://doi.org/10.1177/17470218221113761
- Anglada-Tort, M., Schofield, K., Trahan, T., & Müllensiefen, D. (2022). I’ve heard that brand before: the role of music recognition on consumer choice. International Journal of Advertising, 1-20. Doi: https://doi.org/10.1080/02650487.2022.2060568
- Anglada-Tort, M., Krause, A. E., & North, A. C. (2021). Popular music lyrics and musicians’ gender over time: A computational approach. Psychology of Music, 49(3), 426-444. Doi: https://doi.org/10.1177/0305735619871602
- Anglada-Tort, M., Steffens, J., & Müllensiefen, D. (2019): Names and titles matter: The impact of linguistic fluency and the affect heuristic on aesthetics and value judgements of music. Psychology of Aesthetics, Creativity, and the Arts, 13 (3), 277-292. Doi: https://dx.doi.org/10.1037/aca0000172
- Anglada-Tort, M., & Müllensiefen, D. (2017): The repeated recording illusion: The effects of extrinsic and individual difference factors on musical judgments. Music Perception, 35(1), 94-117. Doi: https://doi.org/10.1525/mp.2017.35.1.94
The group also studies popularity dynamics and the emergence of social norms in the context of aesthetics and fashion. One way in which we study such complex social phenomena is by simulating artificial cultural markets in the lab, for example by exploring dynamic patterns of interactions between thousands of participants when consuming creative work within evolving social networks.
Anglada-Tort, M., Harrison, P. M., Lee, H., & Jacoby, N. (2023). Large-scale singing experiments reveal oral transmission mechanism underlying music evolution. Current Biology, 33, 1-15. https://doi.org/10.1016/j.cub.2023.02.070
Anglada-Tort, M., Lee, H., Krause, A. E., & North, A. C. (2023). Here comes the sun: music features of popular songs reflect prevailing weather conditions. Royal Society Open Science, 10, 221443. https://doi.org/10.1098/rsos.221443
Steffens, J., & Anglada-Tort, M. (2023). The effect of visual recognition on listener choices when searching for music in playlists. Psychology of Aesthetics, Creativity, and the Arts. Advance online publication. https://doi.org/10.1037/aca0000562
Anglada-Tort, M., Harrison, P. M. C., & Jacoby, N. (2022): REPP: A robust cross-platform solution for online sensorimotor synchronization experiments. Behavioral Research Methods 4, 2271–2285 (2022). Doi: https://doi.org/10.3758/s13428-021-01722-2
Anglada-Tort, M., Harrison, P. M. C., & Jacoby, N. (2022). Studying the effect of oral transmission on melodic structure using online singing experiments. Proceedings of the Annual Meeting of the Cognitive Science Society, 44(44). Doi: https://escholarship.org/uc/item/3567q2vf
Niarchou, M., Gustavson, D. J., Sathirapongsasuti, F., Anglada-Tort, M., …, Jacoby, N., & Gordon R. L. (2022): Unravelling the genetic architecture of musical rhythm: a large-scale genome-wide association study of beat synchronization. Nature Human Behaviour 6, 1292–1309 (2022). Doi: https://doi.org/10.1038/s41562-022-01359-x
Anglada-Tort, M., Masters, N., Steffens, J., North, A., & Müllensiefen, D. (2023). The Behavioural Economics of Music: Systematic review and future directions. Quarterly Journal of Experimental Psychology, 76(5), 1177–1194. https://doi.org/10.1177/17470218221113761
Anglada-Tort, M., Schofield, K., Trahan, T., & Müllensiefen, D. (2022). I’ve heard that brand before: the role of music recognition on consumer choice. International Journal of Advertising, 1-20. Doi: https://doi.org/10.1080/02650487.2022.2060568
Jacoby, N., Polak, R., Grahn, J., Cameron, D. J., Lee, K. M., Godoy, R., … Anglada-Tort, M., Harrison, P. M. C., McPherson, M. J., Dolan, S., Durange, A., & Mcdermott, J. (2021, July 6). Universality and cross-cultural variation in mental representations of music revealed by global comparison of rhythm priors. Preprint Doi: https://doi.org/10.31234/osf.io/b879v
Savage, P. E., Jacoby, N., Margulis, E. H., Daikoku, H., Anglada- Tort, M., ... (2021). Building sustainable global collaborative networks: Recommendations from music studies and the social sciences. In E. H. Margulis, D. Loughridge, & P. Loui (Eds.), The science-music borderlands: Reckoning with the past, imagining the future. MIT Press. Preprint Doi: http://doi.org/10.31234/osf.io/cb4ys
Anglada-Tort, M., Krause, A. E., & North, A. C. (2021). Popular music lyrics and musicians’ gender over time: A computational approach. Psychology of Music, 49(3), 426-444. Doi: https://doi.org/10.1177/0305735619871602
Anglada-Tort, M., Keller, S., Steffens, J., & Müllensiefen, D. (2021): The impact of source effects on the evaluation of music for advertising: Are there differences in how advertising professionals and consumers judge music? Journal of Advertising Research, 61(1), 95-109. Doi: https://doi.org/10.2501/JAR-2020-016
Anglada-Tort, M., & Skov, M. (2020): What counts as Aesthetics in Science? A bibliometric Analysis and Visualization of the Scientific Literature from 1970 to 2018. Psychology of Aesthetics, Creativity, and the Arts, 16(3), 553–568. https://doi.org/10.1037/aca0000350
Harrison, P. M. C., Marjieh, R., Adolfi, F., van Rijn, P., Anglada-Tort, M., Tchernichovski, O., Larrouy-Maestri, P., & Jacoby, N.(2020). Gibbs Sampling with People. 34th Conference on Neural Information Processing Systems (NeurIPS 2020). Doi: https://arxiv.org/abs/2008.02595
Anglada-Tort, M., Steffens, J., & Müllensiefen, D. (2019): Names and titles matter: The impact of linguistic fluency and the affect heuristic on aesthetics and value judgements of music. Psychology of Aesthetics, Creativity, and the Arts, 13 (3), 277-292. Doi: https://dx.doi.org/10.1037/aca0000172
Anglada-Tort, M. (2019): Measuring stereotypes in music: A commentary on Susino and Schubert (2019). Empirical Musicology Review, 14(1-2), 16-21. Doi: http://dx.doi.org/10.18061/emr.v13i1-2.6387
Anglada-Tort, M., Thueringer, H., & Omigie, D. (2019): The busking experiment: A field study measuring behavioural responses to street music performances. Psychomusicology: Music, Mind, and Brain, 29(1), 46-55. Doi: http://dx.doi.org/10.1037/pmu0000236
Anglada-Tort, M., & Sanfilippo, K.R.M. (2019): Visualizing music psychology: A bibliometric analysis of Psychology of Music, Music Perception, and Musicae Scientiae from 1973 to 2017”, Music & Science, 2, 2059204318811786. Doi: https://doi.org/10.1177/2059204318811786
Anglada-Tort, M. (2018): Commentary on Canonne (2018): Listening to improvisation. Empirical Musicology Review. Doi: http://dx.doi.org/10.18061/emr.v13i1-2.6387
Anglada-Tort, M., Baker, T., & Müllensiefen, D. (2018): False memories in music listening: Exploring the misinformation effect and individual difference factors in auditory memory. Memory, 1-16. Doi: https://doi.org/10.1080/09658211.2018.1545858
Anglada-Tort, M., & Müllensiefen, D. (2017): The repeated recording illusion: The effects of extrinsic and individual difference factors on musical judgments. Music Perception, 35(1), 94-117. Doi: https://doi.org/10.1525/mp.2017.35.1.94
Ferré., P., Anglada-Tort, M., Guasch, M. (2017): “Processing of emotional words in bilinguals: Testing the effects of Word concreteness, task type and language status”, Second Language Research, 1- 24. Doi: https://doi.org/10.1177/0267658317744008