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Supplemental material, sj-docx-1-pom-10.1177_03057356221141735 for Reminiscence bump invariance with respect to genre, age, and country by James Renwick and Matthew H. Woolhouse in Psychology of Music

Additional file 1. CONSORT 2010 checklist of information to include when reporting a pilot or feasibility trial.

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Thursday, May 23 • 9:00am - 10:30am Session 1A: Productive Consumers / Consommateurs productifs 1.Eddy Borges-Rey (University of Stirling), Re-imagining online music prosumption: Creative Appropriations and Music Imagery. 2.Yannick Lapointe (Université Laval), Le travail créatif de l'auditeur : le cas de la scène haute-fidélité. 3. Matthew Woolhouse (McMaster University), Heigh-Ho, Heigh-Ho, It's Off To Work We Go: The Influence of Employment Patterns on Music Downloading. Chair / Président: William Echard

Research on memory often describes the remarkable longevity of music. However, memory for music is not uniform. Cook (1987) found that participants were not able to tell apart excerpts that modulated from those that did not when the excerpt was longer than 1 minute in length. This suggests that participants were no longer able to remember, and compare, musical keys after a relatively short period of time. Farbood (2016) and Woolhouse et al. (2016) further explored the limitations of memory for tonal structures finding that, in fact, harmonic memory only lasts up to 21 seconds after modulation. However, this research was done using homophonic stimuli—arpeggios or quarter-note chords—that may not be representative of the music participants would be listening to regularly. The focus of this project was to explore how the addition of certain musical features, such as melodic or rhythmic figurations, may influence harmonic memory. Observing these possible influences may provide us with insight into the processes responsible for auditory memory and how it differs from other domains, such as speech or vision. Chapter 1 explores prominent memory literature and music cognition experiments that support, or address concerns with, common memory models. Here, I introduce a cognitive system which reconciles music research with models by memory specialists such as Baddeley and Snyder. Chapter 2 presents a detailed account of background empirical literature, including Farbood (2016) and Woolhouse et al. (2016). Though fundamental to the exploration of temporally nonadjacent harmonic memory, this research is potentially limited in its generalizability due to the homophonic nature of the stimuli. Chapter 3 explores this limitation by testing the effects of adding surface features—melodic and rhythmic components often used for elaboration in composition—on memory for large-scale tonal structures. Results found that harmonic memory is, indeed, enhanced and prolonged by these elaborative components, lasting up to 33 seconds, well past the limit found in previous research. Farbood (2016) further claimed that harmonic memory is significantly interrupted by new, highly harmonic excerpts. However, results from Woolhouse et al. (2016), Spyra et al. (2021) and those from Chapter 3 all question this claim as they employed stimuli that was highly harmonic. Chapter 4 investigates the contradiction by testing whether functional diatonic, functional chromatic, or random sequences degraded harmonic memory for an original key. Functional diatonic intervening information resulted in increased harmonic memory, directly contradicting Farbood’s original findings. In Chapter 5, these results are explored in terms of prominent memory models in the field of cognition, supporting standard models of memory such as that by Baddeley and Hitch (1974) or Atkinson and Shiffrin (1968), as well as my proposed cognitive system. This is further elaborated by discussing the process of undergoing a musical judgement task from perception through to decision-making. In summary, this project suggests that more generalizable stimuli containing realistic musical features produce a significant boost in harmonic memory. Furthermore, this arguably calls into question standard practices in analysis that categorize surface features as hierarchically less important than ’deeper’ harmonic events, and thus, potentially less important from a cognitive perspective. Which is to say, this evidence suggests that these features may play a vital role in remembering nonadjacent harmonic structures. Dissertation Doctor of Philosophy (PhD) Memory for music is often celebrated for its longevity. Music is a complex stimulus, however, and not all of its characteristics are remembered equally well. Past research has found that participants were not able to remember musical keys after a surprisingly short period of time: Farbood (2016) and Woolhouse et al. (2016) found that harmonic memory—i.e., memory for a key—lasts up to 21 seconds after a key change. Compared to nursery rhymes remembered from childhood bedtimes, this is remarkably limited. Yet this research did not fully explore which musical characteristics affect harmonic memory as it was done using simple musical stimuli: compositions made of blocks of chords. Whereas a string of chords might sound pleasant, it may not be representative of the type of music that people listen to regularly (with complex melodies and instrumentation). The focus of this project was to explore musical factors, such as melodies or rhythms, and measure how they interact with musical memory. Observing specific aspects of the stimulus gives us a window into the complexities of human memory, particularly that of the auditory domain. Chapter 1 provides an overview of memory literature with a focus on common memory models and the musical research that supports them or contributes to their development. Here, I propose a cognitive system which integrates prominent models that otherwise describe different stages of processing complex auditory stimuli. Chapter 2 presents a detailed account of background empirical literature. This provides a basis for a series of experiments outlined in Chapters 3 and 4. These experiments investigate how components of music influence harmonic memory. Components include Surface Features, or ornamentations in music such as melodies or rhythms, and Harmony, the structure of the key itself which can make an excerpt sound more, or less, familiar. Results suggest that memory is significantly enhanced and prolonged by the addition of surface features. Furthermore, harmony that most resembles culturally familiar compositional practices also provides a memory boost when compared to random or somewhat ambiguous sequences. In Chapter 5, the implications of these results are explored with regards to the general memory models discussed in Chapter 1. Results support standard models of memory and my proposed cognitive system, as demonstrated by following the processing of my experimental musical stimuli from sound to executive function. This project suggests that more complex and musically realistic stimuli produce a significant memory boost. This puts into question traditional practices in music analysis which separate surface features into hierarchically less important positions when, in fact, the musical surface may be vital to our processing of auditory stimuli.

Music preference research seeks to explain the relationship between music listeners and their music. An important task of such research is to describe differences between types of music. Musical genres are often chosen to address this task. But they are inadequate as they require subjective interpretation by both participants and researchers, making results difficult to decipher. This thesis provides foundational work to establish Music acoustic features (MAFs). MAFs are intended to provide a reliable method of music classification and description for experimental research. First, a labelled set of 4800 musical stimuli representing six MAFs of varying levels were systematically produced. A program tool, Essentia, was then used to identify low-level audio features within the musical stimuli that correlate with MAF manipulations. The Essentia features (EFs) that best represented MAFs were identified and used to predict MAFs in 44 real-world music clips. An online study also collected ratings from participants (N = 43) for each of the 44 real-world clips. The results of MAFs predicted by EFs and MAFs rated by participants were compared for consistency. The MAF Tempo correlated strongest between predicted and rated MAFs in real-world music, followed by Dynamic, Texture, Articulation, Register, and Timbre. Based on the outlined process, MAFs were to shown to be manipulable for experimental analysis, measurable within real-world stimuli, and readily perceivable by music listeners. These three criteria firmly establish MAFs as a reliable method of music classification and description for use in experimental research. Furthermore, the process outlined here can easily be adapted to validate other potential MAFs that may exist in music. MAFs will improve future research by increasing the robustness and clarity of conclusions, and thus provide greater insight into how and why people listen to certain types of music. Thesis Master of Science (MSc) This thesis aims to increase our understanding of music preference by helping us more accurately describe differences in music. Previous research has defined differences in music by genre categories, such as Classical or Dance music. However, genres are often subjective, and even arbitrary, in their descriptions. Instead of genre, this thesis proposes that a new method of categorization is used: Music Acoustic Features. These features are not subjectively defined, they can actually be measured within a piece of music. Furthermore, these features can be modified and tested in experiments to see how listeners respond. Such future experiments will provide us with a better understanding of what kind of music people like and why.

Using a large dataset of digital music downloads, this thesis examines the extent to which cognitive-psychology research can generate and predict user behaviours relevant to the distinct fields of computer science and music perception. Three distinct topics are explored. Topic one describes the current difficulties with using large digital music resources for cognitive research and provides a solution by linking metadata through a complex validation process. Topic two uses this enriched information to explore the extent to which extracted acoustic features influence genre preferences considering personality, and mood research; analysis suggests acoustic features which are pronounced in an individual's preferred genre influence choice when selecting less-preferred genres. Topic three examines whether metrics of music listening behaviour can be derived and validated by social psychological research; results support the notion that user behaviours can be derived and validated using an informed psychological background, and may be more useful than acoustic features for a variety of computational music tasks. A primary motivation for this thesis was to approach interdisciplinary music research in two ways: (1) utilize a shared understanding of statistical learning as a theoretical framework underpinning for prediction and interpretation; and (2) by providing resources, and approaches to analysis of "big data" which are experimentally valid, and psychologically useful. The unique strengths of this interdisciplinary approach, and the weaknesses that remain, are then addressed by discussing refined analyses and future directions. Thesis Master of Science (MSc) This thesis examines whether research from cognitive psychology can be used to inform and predict behaviours germane to computational music analysis including genre choice, music feature preference, and consumption patterns from data provided by digital-music platforms. Specific topics of focus include: information integrity and consistency of large datasets, whether signal processing algorithms can be used to assess music preference across multiple genres, and the degree to which consumption behaviours can be derived and validated using more traditional experimental paradigms. Results suggest that psychologically motivated research can provide useful insights and metrics in the computationally focused area of global music consumption behaviour and digital music analysis. Limitations that remain within this interdisciplinary approach are addressed by providing refined analysis techniques for future work.

Includes an exploration of working memory models from a musical standpoint. A musical key can only be retained in memory for approximately 20 seconds. However, other factors may be influencing the strength of this retention. The current study tests the influence of time and number of events (chords) in an intervening key on the deterioration in memory of a nonadjacent key. Stimuli first established a major key using traditional harmonic rules, then modulated to an intervening key that was either 6 or 9 seconds in duration and formed from either 4 or 6 chords. Stimuli then returned to the original key in a probe cadence. Participants were asked to rate this cadence in terms of its sense of closure. It was revealed that there is a significant negative effect of time on the probe cadence though no effect of number of events was found. This suggests that spending more time in an intervening key, and not the number of intervening chords, diminishes the memory of the original key. However, it is unclear from this study where in memory the nonadjacent key relationship is processed. Relevant literature is examined to form a working hypothesis with the goal of strengthening future studies with a capable foundation in memory research and theories. Thesis Master of Science (MSc) We have a very short memory span for musical keys. Humans can only remember a key for approximately 20 seconds after it’s changed. However, it is unclear whether it is time spent away from the key that makes us forget or if it is the number of chords we heard in a second, interrupting key. The current study tests this distinction using nonadjacent key relationships—in which a key is established, a different key interrupts for a random amount of time and number of chords before returning to the original key for two target chords. Results confirmed previous findings as there was a significant effect of time on memory. However, there was no effect of number of chords, suggesting that it is the length of time spent away from a key, not number of chords that has an effect on memory.