Exploring the neural entrainment to musical rhythms and meter : a steady-state evoked potential approach

Thèse de doctorat réalisé en cotutelle avec l'Université catholique de Louvain, Belgique (Faculté de médecine, Institut de Neuroscience)Percevoir et synchroniser ses mouvements à une pulsation régulière en musique est une capacité largement répandue chez l’Homme, et fondamentale aux comportements musicaux. La pulsation et la métrique en musique désignent généralement une organisation temporelle périodique perçue à partir de stimuli acoustiques complexes, et cette organisation perceptuelle implique souvent une mise en mouvement périodique spontanée du corps. Cependant, les mécanismes neuraux sous-tendant cette perception sont à l’heure actuelle encore méconnus. Le présent travail a donc eu pour objectif de développer une nouvelle approche expérimentale, inspirée par l’approche électrophysiologique des potentiels évoqués stationnaires, afin d’explorer les corrélats neuraux à la base de notre perception de la pulsation et de la métrique induite à l’écoute de rythmes musicaux. L’activité neurale évoquée en relation avec la perception d’une pulsation a été enregistrée par électroencéphalographie (EEG) chez des individus sains, dans divers contextes : (1) dans un contexte d’imagerie mentale d’une métrique appliquée de manière endogène sur un stimulus auditif, (2) dans un contexte d’induction spontanée d’une pulsation à l’écoute de patterns rythmiques musicaux, (3) dans un contexte d’interaction multisensorielle, et (4) dans un contexte de synchronisation sensorimotrice. Pris dans leur ensemble, les résultats de ces études corroborent l’hypothèse selon laquelle la perception de la pulsation en musique est sous-tendue par des processus de synchronisation et de résonance de l’activité neurale dans le cerveau humain. De plus, ces résultats suggèrent que l’approche développée dans le présent travail pourrait apporter un éclairage significatif pour comprendre les mécanismes neuraux de la perception de la pulsation et des rythmes musicaux, et, dans une perspective plus générale, pour explorer les mécanismes de synchronisation neurale.The ability to perceive a regular beat in music and synchronize to it is a widespread human skill. Fundamental to musical behavior, beat and meter refer to the perception of periodicities while listening to musical rhythms, and usually involve spontaneous entrainment to move on these periodicities. However, the neural mechanisms underlying entrainment to beat and meter in Humans remain unclear. The present work tests a novel experimental approach, inspired by the steady-state evoked potential method, to explore the neural dynamics supporting the perception of rhythmic inputs. Using human electroencephalography (EEG), neural responses to beat and meter were recorded in various contexts: (1) mental imagery of meter, (2) spontaneous induction of a beat from rhythmic patterns, (3) multisensory integration, and (4) sensorimotor synchronization. Our results support the view that entrainment and resonance phenomena subtend the processing of musical rhythms in the human brain. Furthermore, our results suggest that this novel approach could help investigating the link between the phenomenology of musical beat and meter and neurophysiological evidence of a bias towards periodicities arising under certain circumstances in the nervous system. Hence, entrainment to music provides an original framework to explore general entrainment phenomena occurring at various levels, from the inter-neural to the inter-individual level

Embodied Cognitive Science of Music. Modeling Experience and Behavior in Musical Contexts

Recently, the role of corporeal interaction has gained wide recognition within cognitive musicology. This thesis reviews evidence from different directions in music research supporting the importance of body-based processes for the understanding of music-related experience and behaviour. Stressing the synthetic focus of cognitive science, cognitive science of music is discussed as a modeling approach that takes these processes into account and may theoretically be embedded within the theory of dynamic systems. In particular, arguments are presented for the use of robotic devices as tools for the investigation of processes underlying human music-related capabilities (musical robotics)

Beat Construal, Tempo, Metric Dissonance, and Transgressing the Groove in Heavy Metal

This dissertation explores the relationship between the metric practices of heavy metal and the elements and processes of the musical quality known as “groove.” Although heavy metal is not often expressly associated with groove per se, it occupies a historical position within the stylistic milieu for which groove music has established the primary, referential conditions. In order to uncover this connection, then, I begin with an analysis of groove in relation to established groove-music styles, defining it as an embodied and encultured knowledge of a set of cognitive, social, kinetic, aesthetic, and musical behaviors extending in practice from African-American popular-music styles of (mostly) the twentieth century and continuing into the present. Groove operates around a series of interactive musical cues that act to initiate and regulate an aesthetic sensibility characterized by musical dialogue, antiphonal musical structures, and a heightened, consonant mutual awareness among performers and audiences. Moreover, through an active physical entrainment and participatory kinesthetic knowledge of groove structures—such as the backbeat motive, the consonant weight profile of the basic rock beat, stylistically consistent uses of metric dissonance, and the collective negotiations of an isochronous beat and metric grid—participants, including musicians and listeners, define and signify upon the most important metric features of particular grooves at any given time. I conclude that, because metal musicians are often concerned with generating a consonant emotional and physical relation between themselves, the music, and its audiences, and because they do so in ways that are demonstrably responsive to groove structures, they are fundamentally connected with groove as defined. Complicating this relationship is that metal artists as often signify upon the metric practices associated with groove styles as confirm them. More specifically, I argue, they appropriate certain facets of groove, while deviating from one or more of these facets in order to create a relation between the listener and the sounding music that is often characterized by its fans and critics as transgressive. This complication can be witnessed when viewing the multiple and sometimes drastic physical responses exhibited by listeners. Heavy metal’s metric deviations in the domains of groove arguably form a stylistic signifier for metal music as a whole and help define the parameters for experimentation in “extreme” genres of metal, such as grindcore, doom, black, and varieties of progressive metal. This “extremfication” is a process that can be described, following Ronald Bogue (2003), as moving from quantitative to qualitative modes of expression. This dissertation concludes with an analysis of four heavy metal tracks that occupy a mediating position within this process. These tracks, while they exhibit deference to the consonant values of groove aesthetics and groove structures, also use these parameters and the bodily affordances they provide as bases for a multiplicity of metric and kinesthetic responses to their musical unfolding

Proceedings of the 7th Sound and Music Computing Conference

Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010

Understanding and Decoding Imagined Speech using Electrocorticographic Recordings in Humans

Certain brain disorders, resulting from brainstem infarcts, traumatic brain injury, stroke and amyotrophic lateral sclerosis, limit verbal communication despite the patient being fully aware. People that cannot communicate due to neurological disorders would benefit from a system that can infer internal speech directly from brain signals. Investigating how the human cortex encodes imagined speech remains a difficult challenge, due to the lack of behavioral and observable measures. As a consequence, the fine temporal properties of speech cannot be synchronized precisely with brain signals during internal subjective experiences, like imagined speech. This thesis aims at understanding and decoding the neural correlates of imagined speech (also called internal speech or covert speech), for targeting speech neuroprostheses. In this exploratory work, various imagined speech features, such as acoustic sound features, phonetic representations, and individual words were investigated and decoded from electrocorticographic signals recorded in epileptic patients in three different studies. This recording technique provides high spatiotemporal resolution, via electrodes placed beneath the skull, but without penetrating the cortex In the first study, we reconstructed continuous spectrotemporal acoustic features from brain signals recorded during imagined speech using cross-condition linear regression. Using this technique, we showed that significant acoustic features of imagined speech could be reconstructed in seven patients. In the second study, we decoded continuous phoneme sequences from brain signals recorded during imagined speech using hidden Markov models. This technique allowed incorporating a language model that defined phoneme transitions probabilities. In this preliminary study, decoding accuracy was significant across eight phonemes in one patients. In the third study, we classified individual words from brain signals recorded during an imagined speech word repetition task, using support-vector machines. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the classification framework. Classification accuracy was significant across five patients. In order to compare speech representations across conditions and integrate imagined speech into the general speech network, we investigated imagined speech in parallel with overt speech production and/or speech perception. Results shared across the three studies showed partial overlapping between imagined speech and speech perception/production in speech areas, such as superior temporal lobe, anterior frontal gyrus and sensorimotor cortex. In an attempt to understanding higher-level cognitive processing of auditory processes, we also investigated the neural encoding of acoustic features during music imagery using linear regression. Despite this study was not directly related to speech representations, it provided a unique opportunity to quantitatively study features of inner subjective experiences, similar to speech imagery. These studies demonstrated the potential of using predictive models for basic decoding of speech features. Despite low performance, results show the feasibility for direct decoding of natural speech. In this respect, we highlighted numerous challenges that were encountered, and suggested new avenues to improve performances