Testing a Spectral Model of Tonal Affinity with Microtonal Melodies and Inharmonic Spectra

Tonal affinity is the perceived goodness of fit of successive tones. It is important because a preference for certain intervals over others would likely influence preferences for, and prevalences of, “higher-order” musical structures such as scales and chord progressions. We hypothesize that two psychoacoustic (spectral) factors—harmonicity and spectral pitch similarity—have an impact on affinity. The harmonicity of a single tone is the extent to which its partials (frequency components) correspond to those of a harmonic complex tone (whose partials are a multiple of a single fundamental frequency). The spectral pitch similarity of two tones is the extent to which they have partials with corresponding, or close, frequencies. To ascertain the unique effect sizes of harmonicity and spectral pitch similarity, we constructed a computational model to numerically quantify them. The model was tested against data obtained from 44 participants who ranked the overall affinity of tones in melodies played in a variety of tunings (some microtonal) with a variety of spectra (some inharmonic). The data indicate the two factors have similar, but independent, effect sizes: in combination, they explain a sizeable portion of the variance in the data (the model-data squared correlation is r2 = .64). Neither harmonicity nor spectral pitch similarity require prior knowledge of musical structure, so they provide a potentially universal bottom-up explanation for tonal affinity. We show how the model—as optimized to these data—can explain scale structures commonly found in music, both historical and contemporary, and we discuss its implications for experimental microtonal and spectral music

Music cognition as mental time travel.

As we experience a temporal flux of events our expectations of future events change. Such expectations seem to be central to our perception of affect in music, but we have little understanding of how expectations change as recent information is integrated. When music establishes a pitch centre (tonality), we rapidly learn to anticipate its continuation. What happens when anticipations are challenged by new events? Here we show that providing a melodic challenge to an established tonality leads to progressive changes in the impact of the features of the stimulus on listeners' expectations. The results demonstrate that retrospective analysis of recent events can establish new patterns of expectation that converge towards probabilistic interpretations of the temporal stream. These studies point to wider applications of understanding the impact of information flow on future prediction and its behavioural utility

Data-driven, memory-based computational models of human segmentation of musical melody

When listening to a piece of music, listeners often identify distinct sections or segments within the piece. Music segmentation is recognised as an important process in the abstraction of musical contents and researchers have attempted to explain how listeners perceive and identify the boundaries of these segments.The present study seeks the development of a system that is capable of performing melodic segmentation in an unsupervised way, by learning from non-annotated musical data. Probabilistic learning methods have been widely used to acquire regularities in large sets of data, with many successful applications in language and speech processing. Some of these applications have found their counterparts in music research and have been used for music prediction and generation, music retrieval or music analysis, but seldom to model perceptual and cognitive aspects of music listening.We present some preliminary experiments on melodic segmentation, which highlight the importance of memory and the role of learning in music listening. These experiments have motivated the development of a computational model for melodic segmentation based on a probabilistic learning paradigm.The model uses a Mixed-memory Markov Model to estimate sequence probabilities from pitch and time-based parametric descriptions of melodic data. We follow the assumption that listeners' perception of feature salience in melodies is strongly related to expectation. Moreover, we conjecture that outstanding entropy variations of certain melodic features coincide with segmentation boundaries as indicated by listeners.Model segmentation predictions are compared with results of a listening study on melodic segmentation carried out with real listeners. Overall results show that changes in prediction entropy along the pieces exhibit significant correspondence with the listeners' segmentation boundaries.Although the model relies only on information theoretic principles to make predictions on the location of segmentation boundaries, it was found that most predicted segments can be matched with boundaries of groupings usually attributed to Gestalt rules.These results question previous research supporting a separation between learningbased and innate bottom-up processes of melodic grouping, and suggesting that some of these latter processes can emerge from acquired regularities in melodic data

Perception of affect in unfamiliar music

This thesis comprises a body of work that investigates affect perception of unfamiliar music, with a focus on both the role of potentially culture-independent psychoacoustic features that are intrinsic to a musical signal (e.g. roughness, harmonicity, spectral entropy, and average pitch) and extrinsic culture-dependent features (e.g. familiarity through exposure and evaluative conditioning). Much previous research in music perception has suggested that extrinsic features are of more importance than intrinsic features, but has not systematically tested the impact of intrinsic features on responses to unfamiliar music. The thesis discusses four experiments conducted to test the role of the above mentioned features using musical stimuli that are unfamiliar to participants. By using musical stimuli that are unfamiliar to participants, additional evidence can be provided for the cultural- independence of the tested intrinsic features. In order to achieve this unfamiliarity, two approaches were used. The first approach examined affective responses to chords from the unfamiliar microtonal Bohlen-Pierce system in Western listeners, the second approach tested affective responses to Western musical harmony in remote villages in Papua New Guinea, with varying levels of familiarity with Western music. The results of the listening experiments using Bohlen-Pierce suggest that the tested underlying culture-independent psychoacoustic features consistently impact affective rat- ings more strongly than do the experimentally manipulated culture-dependent factors of familiarity and evaluative conditioning. The results from the cross-cultural experiment suggest a strong role of familiarity on valence ratings of Western cadences and melodies. In summary, by using unfamiliar music (through the use of an unfamiliar microtonal system or through cross-cultural research) we can show that, in addition to extrinsic culture-dependent features, intrinsic features are fundamental for affect perception in music

Information distribution within musical segments

In the research on word recognition, it has been shown that word beginnings have higher information content for word identification than word endings; this asymmetric information distribution within words has been argued to be due to the communicative pressure to allow words in speech to be recognized as early as possible. Through entropy analysis using two representative datasets from Wikifonia and the Essen folksong corpus respectively, here we show that musical segments also have higher information content (i.e., higher entropy) in segment beginnings than endings. Nevertheless, this asymmetry was not as dramatic as that found within words, and the highest information content was observed in the middle of the segments (i.e., an inverted-U pattern). This effect may be because the first and last notes of a musical segment tend to be tonally stable, with more flexibility in the first note for providing the initial context. The asymmetric information distribution within words has been shown to be an important factor accounting for various asymmetric effects in word reading, such as the left-biased preferred viewing location and optimal viewing position effects. Similarly, the asymmetric information distribution within musical segments is a potential factor that can modulate music reading behavior and should not be overlooked.published_or_final_versio

When Does the Influencer Matter?

The purpose of this research is to identify what factors contribute to the effectiveness of social media influencers’ posts. The first phase of this project studied people’s initial feelings towards social media influencers using a focus group. The results indicated that social media influencers are in fact effective and influential. The second phase of this study tested what factors increase and decrease the effectiveness of a social media influencers post, and what factors will get them the most engagement. This was tested through sixteen experimental conditions with different variations of a fake social media influencer post. Five dependent variables were tested, willingness to share the post, willingness to buy, attitude toward the brand, attitude towards the ad, and attitude towards the influencer. Four independent variables were also measured, size of the influencer (micro or macro), picture (present or not), discount (present or not), and level of purchase involvement (high or low), as well as several contributing variables about personality. The results contended that the presence of a picture in a social media influencers ad was had a positive effect on willingness to share the post, willingness to buy, attitude toward the brand, and attitude towards the ad. Discount also was significant to consumers’ attitudes towards the brand and the ad. Level of involvement and size of the influencer only proved to be statistically significant towards the effectiveness of the post when interaction effects were found between one or more of those variables. The research and analysis conducted will provide valuable information regarding the effectiveness of social media influencers and the relevance of them pertaining to technological shifts and advancements in the marketing field

A Cognitive Information Theory of Music: A Computational Memetics Approach

This thesis offers an account of music cognition based on information theory and memetics. My research strategy is to split the memetic modelling into four layers: Data, Information, Psychology and Application. Multiple cognitive models are proposed for the Information and Psychology layers, and the MDL best-fit models with published human data are selected. Then, for the Psychology layer only, new experiments are conducted to validate the best-fit models. In the information chapter, an information-theoretic model of musical memory is proposed, along with two competing models. The proposed model exhibited a better fit with human data than the competing models. Higher-level psychological theories are then built on top of this information layer. In the similarity chapter, I proposed three competing models of musical similarity, and conducted a new experiment to validate the best-fit model. In the fitness chapter, I again proposed three competing models of musical fitness, and conducted a new experiment to validate the best-fit model. In both cases, the correlations with human data are statistically significant. All in all, my research has shown that the memetic strategy is sound, and the modelling results are encouraging. Implications of this research are discussed

Predictive cognition in dementia: the case of music

The clinical complexity and pathological diversity of neurodegenerative diseases impose immense challenges for diagnosis and the design of rational interventions. To address these challenges, there is a need to identify new paradigms and biomarkers that capture shared pathophysiological processes and can be applied across a range of diseases. One core paradigm of brain function is predictive coding: the processes by which the brain establishes predictions and uses them to minimise prediction errors represented as the difference between predictions and actual sensory inputs. The processes involved in processing unexpected events and responding appropriately are vulnerable in common dementias but difficult to characterise. In my PhD work, I have exploited key properties of music – its universality, ecological relevance and structural regularity – to model and assess predictive cognition in patients representing major syndromes of frontotemporal dementia – non-fluent variant PPA (nfvPPA), semantic-variant PPA (svPPA) and behavioural-variant FTD (bvFTD) - and Alzheimer’s disease relative to healthy older individuals. In my first experiment, I presented patients with well-known melodies containing no deviants or one of three types of deviant - acoustic (white-noise burst), syntactic (key-violating pitch change) or semantic (key-preserving pitch change). I assessed accuracy detecting melodic deviants and simultaneously-recorded pupillary responses to these deviants. I used voxel-based morphometry to define neuroanatomical substrates for the behavioural and autonomic processing of these different types of deviants, and identified a posterior temporo-parietal network for detection of basic acoustic deviants and a more anterior fronto-temporo-striatal network for detection of syntactic pitch deviants. In my second chapter, I investigated the ability of patients to track the statistical structure of the same musical stimuli, using a computational model of the information dynamics of music to calculate the information-content of deviants (unexpectedness) and entropy of melodies (uncertainty). I related these information-theoretic metrics to performance for detection of deviants and to ‘evoked’ and ‘integrative’ pupil reactivity to deviants and melodies respectively and found neuroanatomical correlates in bilateral dorsal and ventral striatum, hippocampus, superior temporal gyri, right temporal pole and left inferior frontal gyrus. Together, chapters 3 and 4 revealed new hypotheses about the way FTD and AD pathologies disrupt the integration of predictive errors with predictions: a retained ability of AD patients to detect deviants at all levels of the hierarchy with a preserved autonomic sensitivity to information-theoretic properties of musical stimuli; a generalized impairment of surprise detection and statistical tracking of musical information at both a cognitive and autonomic levels for svPPA patients underlying a diminished precision of predictions; the exact mirror profile of svPPA patients in nfvPPA patients with an abnormally high rate of false-alarms with up-regulated pupillary reactivity to deviants, interpreted as over-precise or inflexible predictions accompanied with normal cognitive and autonomic probabilistic tracking of information; an impaired behavioural and autonomic reactivity to unexpected events with a retained reactivity to environmental uncertainty in bvFTD patients. Chapters 5 and 6 assessed the status of reward prediction error processing and updating via actions in bvFTD. I created pleasant and aversive musical stimuli by manipulating chord progressions and used a classic reinforcement-learning paradigm which asked participants to choose the visual cue with the highest probability of obtaining a musical ‘reward’. bvFTD patients showed reduced sensitivity to the consequence of an action and lower learning rate in response to aversive stimuli compared to reward. These results correlated with neuroanatomical substrates in ventral and dorsal attention networks, dorsal striatum, parahippocampal gyrus and temporo-parietal junction. Deficits were governed by the level of environmental uncertainty with normal learning dynamics in a structured and binarized environment but exacerbated deficits in noisier environments. Impaired choice accuracy in noisy environments correlated with measures of ritualistic and compulsive behavioural changes and abnormally reduced learning dynamics correlated with behavioural changes related to empathy and theory-of-mind. Together, these experiments represent the most comprehensive attempt to date to define the way neurodegenerative pathologies disrupts the perceptual, behavioural and physiological encoding of unexpected events in predictive coding terms

Preferred music listening is associated with perceptual learning enhancement at the expense of self-focused attention

Can preferred music listening improve following attentional and learning performances? Here we suggest that this may be the case. In Experiment 1, following preferred and non-preferred musical-piece listening, we recorded electrophysiological responses to an auditory roving-paradigm. We computed the mismatch negativity (MMN – the difference between responses to novel and repeated stimulation), as an index of perceptual learning, and we measured the correlation between trial-by-trial EEG responses and the fluctuations in Bayesian Surprise, as a quantification of the neural attunement with stimulus informational value. Furthermore, during music listening, we recorded oscillatory cortical activity. MMN and trial-by-trial correlation with Bayesian surprise were significantly larger after subjectively preferred versus non-preferred music, indicating the enhancement of perceptual learning. The analysis on oscillatory activity during music listening showed a selective alpha power increased in response to preferred music, an effect often related to cognitive enhancements. In Experiment 2, we explored whether this learning improvement was realized at the expense of self-focused attention. Therefore, after preferred versus non-preferred music listening, we collected Heart-Beat Detection (HBD) accuracy, as a measure of the attentional focus toward the self. HBD was significantly lowered following preferred music listening. Overall, our results suggest the presence of a specific neural mechanism that, in response to aesthetically pleasing stimuli, and through the modulation of alpha oscillatory activity, redirects neural resources away from the self and toward the environment. This attentional up-weighting of external stimuli might be fruitfully exploited in a wide area of human learning activities, including education, neurorehabilitation and therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.3758/s13423-022-02127-8