From locomotion to dance and back : exploring rhythmic sensorimotor synchronization

Le rythme est un aspect important du mouvement et de la perception de l’environnement. Lorsque l’on danse, la pulsation musicale induit une activité neurale oscillatoire qui permet au système nerveux d’anticiper les évènements musicaux à venir. Le système moteur peut alors s’y synchroniser. Cette thèse développe de nouvelles techniques d’investigation des rythmes neuraux non strictement périodiques, tels que ceux qui régulent le tempo naturellement variable de la marche ou la perception rythmes musicaux. Elle étudie des réponses neurales reflétant la discordance entre ce que le système nerveux anticipe et ce qu’il perçoit, et qui sont nécessaire pour adapter la synchronisation de mouvements à un environnement variable. Elle montre aussi comment l’activité neurale évoquée par un rythme musical complexe est renforcée par les mouvements qui y sont synchronisés. Enfin, elle s’intéresse à ces rythmes neuraux chez des patients ayant des troubles de la marche ou de la conscience.Rhythms are central in human behaviours spanning from locomotion to music performance. In dance, self-sustaining and dynamically adapting neural oscillations entrain to the regular auditory inputs that is the musical beat. This entrainment leads to anticipation of forthcoming sensory events, which in turn allows synchronization of movements to the perceived environment. This dissertation develops novel technical approaches to investigate neural rhythms that are not strictly periodic, such as naturally tempo-varying locomotion movements and rhythms of music. It studies neural responses reflecting the discordance between what the nervous system anticipates and the actual timing of events, and that are critical for synchronizing movements to a changing environment. It also shows how the neural activity elicited by a musical rhythm is shaped by how we move. Finally, it investigates such neural rhythms in patient with gait or consciousness disorders

From locomotion to dance and back : exploring rhythmic sensorimotor synchronization

Rhythms are central in human behaviors spanning from locomotion to music performance. In dance, self-sustaining and dynamically adapting neural oscillations entrain to the regular auditory inputs that is the musical beat. This entrainment leads to anticipation of forthcoming sensory events, which in turn allows synchronization of movements to the perceived environment. This dissertation develops novel technical approaches to investigate neural rhythms that are not strictly periodic, such as naturally tempo-varying locomotion movements and rhythms of music. It studies neural responses reflecting the discordance between what the nervous system anticipates and the actual timing of events, that are critical for synchronizing movements to a changing environment. It also shows how the neural activity elicited by a musical rhythm is shaped by how we move. Finally, it investigates such neural rhythms in patient with gait or consciousness disorders.(MED - Sciences médicales) -- UCL, 202

Body Movement Selectively Shapes the Neural Representation of Musical Rhythms.

It is increasingly recognized that motor routines dynamically shape the processing of sensory inflow (e.g., when hand movements are used to feel a texture or identify an object). In the present research, we captured the shaping of auditory perception by movement in humans by taking advantage of a specific context: music. Participants listened to a repeated rhythmical sequence before and after moving their bodies to this rhythm in a specific meter. We found that the brain responses to the rhythm (as recorded with electroencephalography) after body movement were significantly enhanced at frequencies related to the meter to which the participants had moved. These results provide evidence that body movement can selectively shape the subsequent internal representation of auditory rhythms

A Time-Warping method for not-so-steady-state evoked-potentials

Electroencephalographic (EEG) responses that are locked to periodic events can be identified in the frequency spectrum of the EEG signal as Steady-State Evoked-Potentials (SS-EPs). By doing so, it is easy to measure the amplitude of the response and to differentiate it from other neural processes occurring at distinct frequencies. However, many repetitive ecological activities such as the synchronization of finger tapping to a musical beat are not strictly isochronous. Actually, the period of those activities fluctuates along time. This results in a spectral leakage of the SS-EPs, rendering it difficult to isolate and measure in the EEG spectrum. Here, we introduce a new method to concentrate the EEG responses of nearly isochronous activities in the frequency domain

TRACKING TIME VARYING ACOUSTIC RHYTHM: an EEG frequency-tagging approach of dynamic attending.

When participants listen to a rhythm produced by a human performer, they are able to “follow” the rhythm even though it can contain relatively large fluctuations in periodicity. This is due to the fact that autocorrelated temporal fluctuations contain relevant information for beat expectation: the occurrence of the upcoming beat is predicted by the occurrences of the preceding beats1. The Dynamic Attending Theory2 proposes that the entrainment to nearly-periodic rhythms emerges from the dynamics of interaction between neural systems acting as “internal oscillators”. The internal oscillators are coupled by their anatomical connexions and, therefore, are able to mutually adjust their synchronization, even after the perturbation of one of the oscillators. Importantly, the internal oscillators generate a repetitive time window within which the system is expecting to receive a stimulation. The auditory events of an autocorrelated rhythm match those expectational windows better than those on an non-correlated, random, rhythm. Therefore, the autocorrelated rhythm would reinforce the neural oscillations, yielding a better neural entrainment than a randomly fluctuating rhythm. In this study, we recorded the EEG activity elicited by auditory beats with autocorrelated fluctuations versus non-correlated fluctuations, in order to provide a direct electrophysiological measure of dynamic attending in healthy human participants

EEG time-warping to study non-strictly-periodic EEG signals related to the production of rhythmic movements.

Many sensorimotor functions are intrinsically rhythmic, and are underlined by neural processes that are functionally distinct from neural responses related to the processing of transient events. EEG frequency tagging is a technique that is increasingly used in neuroscience to study these processes. It relies on the fact that perceiving and/or producing rhythms generates periodic neural activity that translates into periodic variations of the EEG signal. In the EEG spectrum, those variations appear as peaks localized at the frequency of the rhythm and its harmonics. Many natural rhythms, such as music or dance, are not strictly periodic and, instead, show fluctuations of their period over time. Here, we introduce a time-warping method to identify non-strictly-periodic EEG activities in the frequency domain. EEG time-warping can be used to characterize the sensorimotor activity related to the performance of self-paced rhythmic finger movements. Furthermore, the EEG time-warping method can disentangle auditory- and movement-related EEG activity produced when participants perform rhythmic movements synchronized to an acoustic rhythm. This is possible because the movement-related activity has different period fluctuations than the auditory-related activity. With the classic frequency-tagging approach, rhythm fluctuations result in a spreading of the peaks to neighboring frequencies, to the point that they cannot be distinguished from background noise. The proposed time-warping procedure is as a simple and effective mean to study natural non-strictly-periodic rhythmic neural processes such as rhythmic movement production, acoustic rhythm perception and sensorimotor synchronization

pH-Responsive Properties of Asymmetric Nanopapers of Nanofibrillated Cellulose

Inspired by plant movements driven by the arrangement of cellulose, we have fabricated nanopapers of nanofibrillated cellulose (NFC) showing actuation under pH changes. Bending was achieved by a concentration gradient of charged groups along the film thickness. Hence, the resulting nanopapers contained higher concentration of charged groups on one side of the film than on the opposite side, so that pH changes resulted in charge-dependent asymmetric deprotonation of the two layers. Electrostatic repulsions separate the nanofibers in the nanopaper, thus facilitating an asymmetric swelling and the subsequent expanding that results in bending. Nanofibrillated cellulose was modified by 2,2,6,6-tetramethylpiperidin-1-yloxyl radical (TEMPO) oxidation at two reaction times to get different surface concentrations of carboxylic acid groups. TEMPO-oxidized NFC was further chemically transformed into amine-modified NFC by amidation. The formation of graded nanopapers was accomplished by successive filtration of NFC dispersions with varying charge nature and/or concentration. The extent of bending was controlled by the charge concentration and the nanopaper thickness. The direction of bending was tuned by the layer composition (carboxylic acid or amine groups). In all cases, a steady-state was achieved within less than 25 s. This work opens new routes for the use of cellulosic materials as actuators

A Time-Warping Method for the Concentration of Nearly Periodic Signals in EEG Spectrum

Measuring the amplitude of specific frequencies in the spectrum of the EEG signal is a technique that is increasingly used to study the cortical activities related to rhythmic activities, such as the processing of acoustic rhythms, or the performance of periodic movements (i.e. 1) : the periodic activities appear as clear peaks that can be easily distinguished from background noise. However, many rhythms are not strictly periodic and rather have a period that fluctuates over time. The nearly periodic activities are blurred in the EEG spectrum, as the peaks are spread out to neighboring frequencies and add up to the background noise. Here, we introduce a time-warping method to align nearly-periodic EEG signals on a constant period and therefore concentrate the signal in the frequency spectrum

Body Movement Shapes Selectively the Neural Representation of Musical Rhythms

It is increasingly recognized that motor routines dynamically shape the processing of sensory inflow (e.g. hand movements to feel a texture or identify an object). These exploratory movements are often rhythmic, and it has been suggested that movement-perception shaping could be supported by movement-induced neural entrainment. In auditory perception, the shaping of perception by movement has been reported in humans using behavioral methods, but neurophysiological evidence is lacking. To fill this gap, we took advantage of a specific context, music. Participants listened to a cyclical rhythm before and after moving the body on this rhythm according to a specific meter. We found that the brain responses to the rhythm as recorded with EEG after body movement was significantly enhanced at meter frequencies to which participants had moved. These results provide evidence that body movement can shape selectively the subsequent perception and neural representation of auditory rhythms