Music exhibits some cross-cultural similarities, despite its variety across the world. Evidence from a broad range of human cultures suggests the existence of musical universals 1 , here defined as strong regularities emerging across cultures above chance. In particular, humans demonstrate a general proclivity for rhythm 2 , although little is known about why music is particularly rhythmic and why the same structural regularities are present in rhythms around the world. We empirically investigate the mechanisms underlying musical universals for rhythm, showing how music can evolve culturally from randomness. Human participants were asked to imitate sets of randomly generated drumming sequences and their imitation attempts became the training set for the next participants in independent transmission chains. By perceiving and imitating drumming sequences from each other, participants turned initially random sequences into rhythmically structured patterns. Drumming patterns developed into rhythms that are more structured, easier to learn, distinctive for each experimental cultural tradition and characterized by all six statistical universals found among world music 1 ; the patterns appear to be adapted to human learning, memory and cognition. We conclude that musical rhythm partially arises from the influence of human cognitive and biological biases on the process of cultural evolution 3. Percussion instruments may have provided the first form of musical expression in human evolution. Great apes, our closest living relatives, show drumming behaviour 4 , which they can learn socially 5 , producing some human-like rhythmic sequences 6. Percussive behaviour may therefore have already been present in our ancestors some million years ago, before the split between the human and Pan lineages 2. Archaeological findings also suggest that the first human musical instrument might have been percussive, as also attested in modern hunter-gatherer societies around the world 7. This makes rhythm a particularly apt musical dimension for reconstructing crucial steps in the evolution of music. Six rhythmic features can be considered human universals, showing a greater than chance frequency overall and appearing in all geographic regions of the world. These statistical universals 1 are:
*Previous work has shown that the N400 ERP component is elicited by all words, whether presented in isolation or in structured contexts, and that its amplitude is modulated by semantic association and contextual predictability. What is less clear is the extent to which the N400 response is modulated by semantic incongruity when predictability is held constant. In the current study we examine N400 modulation associated with independent manipulations of predictability and congruity in an adjective-noun paradigm that allows us to precisely control predictability through corpus counts. Our results demonstrate small N400 effects of semantic congruity (yellow bag vs. innocent bag), and much more robust N400 effects of predictability (runny nose vs. dainty nose) under the same conditions. These data argue against unitary N400 theories according to which N400 effects of both predictability and incongruity reflect a common process such as degree of integration difficulty, as large N400 effects of predictability were observed in the absence of large N400 effects of incongruity. However, the data are consistent with some versions of unitary 'facilitated access' N400 theories, as well as multiple-generator accounts according to which the N400 can be independently modulated by facilitated conceptual/lexical access (as with predictability) and integration difficulty (as with incongruity, perhaps to a greater extent in full sentential contexts).
Short Title (<50 characters): How cognition creates rhythm via cultural evolutionAbstract (<200 words): Musical rhythm, in all its cross-cultural diversity, exhibits several commonalities across world cultures. Traditionally, music research has been split in two fields. Some scientists focused on musicality, namely the human biocognitive predispositions for music, with an emphasis on cross-cultural similarities. Other scholars investigated music, seen as cultural product, focusing on the large variation in world musical cultures. Recent experiments found deep connections between music and musicality, reconciling these opposing views. Here we address the question of how individual cognitive biases affect the process of cultural evolution of music. Data from two experiments is analyzed using two different, complementary techniques. In the experiments, participants hear drumming patterns and imitate them. These patterns are then given to the same or another participant to imitate. The structure of these -initially random -patterns is tracked down to later experimental 'generations'. Frequentist statistics show how participants' biases are amplified by cultural transmission, making drumming patterns more structured. Structure is achieved faster than in transmission within, rather than between, participants. A Bayesian model approximates the motif structures participants learned and created. Overall, our data and model show that individual biases for musicality play a central role in shaping cultural transmission of musical rhythm. Main text (no more than 3500 words, 2-4 figures and/or tables): Do not incorporate tables, illustrations, figure legends, or footnotes within the main stream of text. Word count: 3159
Why does musical rhythm have the structure it does? Musical rhythm, in all its cross-cultural diversity, exhibits commonalities across world cultures. Traditionally, music research has been split into two fields. Some scientists focused on musicality, namely the human biocognitive predispositions for music, with an emphasis on cross-cultural similarities. Other scholars investigated music, seen as a cultural product, focusing on the variation in world musical cultures. Recent experiments found deep connections between music and musicality, reconciling these opposing views. Here, we address the question of how individual cognitive biases affect the process of cultural evolution of music. Data from two experiments are analyzed using two complementary techniques. In the experiments, participants hear drumming patterns and imitate them. These patterns are then given to the same or another participant to imitate. The structure of these initially random patterns is tracked along experimental "generations." Frequentist statistics show how participants' biases are amplified by cultural transmission, making drumming patterns more structured. Structure is achieved faster in transmission within rather than between participants. A Bayesian model approximates the motif structures participants learned and created. Our data and models suggest that individual biases for musicality may shape the cultural transmission of musical rhythm.
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