Biology subjects

Harrison, P. M. C.

Publications and source records attributed to Harrison, P. M. C..

4 recordsLinked to original sources

bioRxiv2022

Reshaping musical consonance with timbral manipulations and massive online experiments

The phenomenon of musical consonance is an essential feature in diverse musical styles. The traditional belief, supported by centuries of Western music theory and psychological studies, is that consonance derives from simple ( harmonic) frequency ratios between tones. Here we show through massive large-scale behavioral experiments (235,440 judgments) that harmonic consonance preferences can be deeply reshaped by timbral manipulations, even as far as to induce preferences for inharmonic intervals. We show how such effects may have shaped the cultural evolution of diverse scale systems ranging from the gamelans slendro scale to the tuning of Western mean-tone and equal-tempered scales. Through computational modeling we show that these timbral manipulations elegantly dissociate competing psychoacoustic mechanisms underlying consonance, and we derive an updated computational model combining liking of harmonicity, disliking of fast beats (roughness), and liking of slow beats. Altogether, this work showcases how large-scale behavioral experiments can inform classical questions in auditory perception. Author summary"We reveal effects of timbre on consonance perception that motivate a new understanding of the evolution of musical scales."

neuroscience↗

bioRxiv2022

Studying the Effect of Oral Transmission on Melodic Structure using Online Iterated Singing Experiments

Since 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.

neuroscience↗

bioRxiv2020

Long-term implicit memory for sequential auditory patterns in humans

To understand auditory scenes, listeners track and retain the statistics of sensory inputs as they unfold over time. We combined behavioural manipulation and modelling to investigate how sequence statistics are encoded into long-term memory and used to interpret incoming sensory signals. In a series of experiments, participants detected the emergence of regularly repeating patterns in novel rapid sound sequences. Unbeknownst to them, a few regular patterns reoccurred sparsely (every [~]3 minutes). Reoccurring sequences showed a rapidly growing detection time advantage over novel sequences. This effect was implicit, robust to interference, and persisted up to 7 weeks. Human performance was reproduced by a memory-constrained probabilistic model, where sequences are stored as n-grams and are subject to memory decay. Results suggest that similar psychological mechanisms may underlie integration processes over different-time scales in memory formation and flexible retrieval.

neuroscience↗

bioRxiv2020

PPM-Decay: A Computational Model of Auditory Prediction with Memory Decay

Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies - one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pattern detection experiment - we show how this decay kernel improves the models predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection. The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm).

animal behavior and cognition↗