Hippocampal sclerosis affects fMR-adaptation of lyrics and melodies in songs

Songs constitute a natural combination of lyrics and melodies, but it is unclear whether and how these two song components are integrated during the emergence of a memory trace. Network theories of memory suggest a prominent role of the hippocampus, together with unimodal sensory areas, in the build-up of conjunctive representations. The present study tested the modulatory influence of the hippocampus on neural adaptation to songs in lateral temporal areas. Patients with unilateral hippocampal sclerosis and healthy matched controls were presented with blocks of short songs in which lyrics and/or melodies were varied or repeated in a crossed factorial design. Neural adaptation effects were taken as correlates of incidental emergent memory traces. We hypothesized that hippocampal lesions, particularly in the left hemisphere, would weaken adaptation effects, especially the integration of lyrics and melodies. Results revealed that lateral temporal lobe regions showed weaker adaptation to repeated lyrics as well as a reduced interaction of the adaptation effects for lyrics and melodies in patients with left hippocampal sclerosis. This suggests a deficient build-up of a sensory memory trace for lyrics and a reduced integration of lyrics with melodies, compared to healthy controls. Patients with right hippocampal sclerosis showed a similar profile of results although the effects did not reach significance in this population. We highlight the finding that the integrated representation of lyrics and melodies typically shown in healthy participants is likely tied to the integrity of the left medial temporal lobe. This novel finding provides the first neuroimaging evidence for the role of the hippocampus during repetitive exposure to lyrics and melodies and their integration into a song

Harmonia, Melos and Rhytmos. Aristotle on Musical Education

In this paper, I reconstruct the reasons why Aristotle thinks that musical education is important for moral education. Musical education teaches us to enjoy appropriately and to recognize perceptually fine melodies and rhythms. Fine melodies and rhythms are similar to the kind of movements fine actions consist in and fine characters display. By teaching us to enjoy and recognise fine melodies and rhythms, musical education can train us to recognize and to take pleasure in fine actions and characters. Thus, musical education can, up to a point, lead us toward the actions and character dispositions a virtuous life requires

Extending a network-of-elaborations representation to polyphonic music: Schenker and species counterpoint.

A system of representing melodies as a network of elaborations has been developed, and used as the basis for software which generates melodies in response to the movements of a dancer. This paper examines the issues of extending this representation system to polyphonic music, and of deriving a structural representation of this kind from a musical score. The theories of Heinrich Schenker and of Species Counterpoint are proposed as potentially fruitful bases

A new approach to onset detection: towards an empirical grounding of theoretical and speculative ideologies of musical performance

This article assesses aspects of the current state of a project which aims, with the help of computers and computer software, to segment soundfiles of vocal melodies into their component notes, identifying precisely when the onset of each note occurs, and then tracking the pitch trajectory of each note, especially in melodies employing a variety of non-standard temperaments, in which musical intervals smaller than 100 cents are ubiquitous. From there, we may proceed further, to describe many other “micro-features” of each of the notes, but for now our focus is on the onset times and pitch trajectories

The Lost Melody Phenomenon

A typical phenomenon for machine models of transfinite computations is the existence of so-called lost melodies, i.e. real numbers $x$ such that the characteristic function of the set $\{x\}$ is computable while $x$ itself is not (a real having the first property is called recognizable). This was first observed by J. D. Hamkins and A. Lewis for infinite time Turing machine, then demonstrated by P. Koepke and the author for $ITRM$s. We prove that, for unresetting infinite time register machines introduced by P. Koepke, recognizability equals computability, i.e. the lost melody phenomenon does not occur. Then, we give an overview on our results on the behaviour of recognizable reals for $ITRM$s. We show that there are no lost melodies for ordinal Turing machines or ordinal register machines without parameters and that this is, under the assumption that $0^{\sharp}$ exists, independent of $ZFC$. Then, we introduce the notions of resetting and unresetting $\alpha$-register machines and give some information on the question for which of these machines there are lost melodies

Spectral pitch distance and microtonal melodies

We present an experiment designed to test the effectiveness of spectral pitch distance at modeling the degree of “affinity” or “fit” of pairs of successively played tones or chords (spectral pitch distance is the cosine distance between salience-weighted, Gaussian-smoothed, pitch domain embeddings of spectral pitches—typically the first eight to ten partials of a tone). The results of a previously conducted experiment, which collected ratings of the perceived similarity and fit of root-position major and minor triads, suggest the model works well for pairs of triads in standard 12-tone equal temperament tunings. The new experiment has been designed to test the effectiveness of spectral pitch distance at modeling the affinity of tones in microtonal melodies where the partials of the tones can be variably tempered between being perfectly harmonic and perfectly matched to the underlying microtonal tuning. The use of microtonal tunings helps to disambiguate innate perceptual (psychoacoustical) responses from learned (cultural) responses. Participants are presented with a software synthesizer containing two unlabeled controls: one adjusts the precise tuning of the tones; the other adjusts the extent to which the spectrum is tempered to match the tuning (as set by the first control). A selection of microtonal melodies are played in different tunings, and the participants adjust one, or both, controls until they find a “sweet spot” at which the music sounds most “in-tune” and the notes best “fit” together. The results of these experiments will be presented and discussed

A Planning-based Approach for Music Composition

. Automatic music composition is a fascinating field within computational creativity. While different Artificial Intelligence techniques have been used for tackling this task, Planning – an approach for solving complex combinatorial problems which can count on a large number of high-performance systems and an expressive language for describing problems – has never been exploited. In this paper, we propose two different techniques that rely on automated planning for generating musical structures. The structures are then filled from the bottom with “raw” musical materials, and turned into melodies. Music experts evaluated the creative output of the system, acknowledging an overall human-enjoyable trait of the melodies produced, which showed a solid hierarchical structure and a strong musical directionality. The techniques proposed not only have high relevance for the musical domain, but also suggest unexplored ways of using planning for dealing with non-deterministic creative domains