Neural dynamics of predictive timing and motor engagement in music listening.

Why do humans spontaneously dance to music? To test the hypothesis that motor dynamics reflect predictive timing during music listening, we created melodies with varying degrees of rhythmic predictability (syncopation) and asked participants to rate their wanting-to-move (groove) experience. Degree of syncopation and groove ratings are quadratically correlated. Magnetoencephalography data showed that, while auditory regions track the rhythm of melodies, beat-related 2-hertz activity and neural dynamics at delta (1.4 hertz) and beta (20 to 30 hertz) rates in the dorsal auditory pathway code for the experience of groove. Critically, the left sensorimotor cortex coordinates these groove-related delta and beta activities. These findings align with the predictions of a neurodynamic model, suggesting that oscillatory motor engagement during music listening reflects predictive timing and is effected by interaction of neural dynamics along the dorsal auditory pathway.

Testing a computational model for aural detection of aircraft in ambient noise.

Computational models are used to predict the performance of human listeners for carefully specified signal and noise conditions. However, there may be substantial discrepancies between the conditions under which listeners are tested and those used for model predictions. Thus, models may predict better performance than exhibited by the listeners, or they may "fail" to capture the ability of the listener to respond to subtle stimulus conditions. This study tested a computational model devised to predict a listener's ability to detect an aircraft in various soundscapes. The model and listeners processed the same sound recordings under carefully specified testing conditions. Details of signal and masker calibration were carefully matched, and the model was tested using the same adaptive tracking paradigm. Perhaps most importantly, the behavioral results were not available to the modeler before the model predictions were presented. Recordings from three different aircraft were used as the target signals. Maskers were derived from recordings obtained at nine locations ranging from very quiet rural environments to suburban and urban settings. Overall, with a few exceptions, model predictions matched the performance of the listeners very well. Discussion focuses on those differences and possible reasons for their occurrence.

Hebbian learning with elasticity explains how the spontaneous motor tempo affects music performance synchronization.

A musician's spontaneous rate of movement, called spontaneous motor tempo (SMT), can be measured while spontaneously playing a simple melody. Data shows that the SMT influences the musician's tempo and synchronization. In this study we present a model that captures these phenomena. We review the results from three previously-published studies: solo musical performance with a pacing metronome tempo that is different from the SMT, solo musical performance without a metronome at a tempo that is faster or slower than the SMT, and duet musical performance between musicians with matching or mismatching SMTs. These studies showed, respectively, that the asynchrony between the pacing metronome and the musician's tempo grew as a function of the difference between the metronome tempo and the musician's SMT, musicians drifted away from the initial tempo toward the SMT, and the absolute asynchronies were smaller if musicians had matching SMTs. We hypothesize that the SMT constantly acts as a pulling force affecting musical actions at a tempo different from a musician's SMT. To test our hypothesis, we developed a model consisting of a non-linear oscillator with Hebbian tempo learning and a pulling force to the model's spontaneous frequency. While the model's spontaneous frequency emulates the SMT, elastic Hebbian learning allows for frequency learning to match a stimulus' frequency. To test our hypothesis, we first fit model parameters to match the data in the first of the three studies and asked whether this same model would explain the data the remaining two studies without further tuning. Results showed that the model's dynamics allowed it to explain all three experiments with the same set of parameters. Our theory offers a dynamical-systems explanation of how an individual's SMT affects synchronization in realistic music performance settings, and the model also enables predictions about performance settings not yet tested.

Dynamic models for musical rhythm perception and coordination.

Rhythmicity permeates large parts of human experience. Humans generate various motor and brain rhythms spanning a range of frequencies. We also experience and synchronize to externally imposed rhythmicity, for example from music and song or from the 24-h light-dark cycles of the sun. In the context of music, humans have the ability to perceive, generate, and anticipate rhythmic structures, for example, "the beat." Experimental and behavioral studies offer clues about the biophysical and neural mechanisms that underlie our rhythmic abilities, and about different brain areas that are involved but many open questions remain. In this paper, we review several theoretical and computational approaches, each centered at different levels of description, that address specific aspects of musical rhythmic generation, perception, attention, perception-action coordination, and learning. We survey methods and results from applications of dynamical systems theory, neuro-mechanistic modeling, and Bayesian inference. Some frameworks rely on synchronization of intrinsic brain rhythms that span the relevant frequency range; some formulations involve real-time adaptation schemes for error-correction to align the phase and frequency of a dedicated circuit; others involve learning and dynamically adjusting expectations to make rhythm tracking predictions. Each of the approaches, while initially designed to answer specific questions, offers the possibility of being integrated into a larger framework that provides insights into our ability to perceive and generate rhythmic patterns.

Adeno-associated virus receptor complexes and implications for adeno-associated virus immune neutralization.

Adeno-associated viruses (AAV) are among the foremost vectors for in vivo gene therapy. A number of monoclonal antibodies against several serotypes of AAV have previously been prepared. Many are neutralizing, and the predominant mechanisms have been reported as the inhibition of binding to extracellular glycan receptors or interference with some post-entry step. The identification of a protein receptor and recent structural characterization of its interactions with AAV compel reconsideration of this tenet. AAVs can be divided into two families based on which domain of the receptor is strongly bound. Neighboring domains, unseen in the high-resolution electron microscopy structures have now been located by electron tomography, pointing away from the virus. The epitopes of neutralizing antibodies, previously characterized, are now compared to the distinct protein receptor footprints of the two families of AAV. Comparative structural analysis suggests that antibody interference with protein receptor binding might be the more prevalent mechanism than interference with glycan attachment. Limited competitive binding assays give some support to the hypothesis that inhibition of binding to the protein receptor has been an overlooked mechanism of neutralization. More extensive testing is warranted.

Neural Entrainment to Musical Pulse in Naturalistic Music Is Preserved in Aging: Implications for Music-Based Interventions.

Neural entrainment to musical rhythm is thought to underlie the perception and production of music. In aging populations, the strength of neural entrainment to rhythm has been found to be attenuated, particularly during attentive listening to auditory streams. However, previous studies on neural entrainment to rhythm and aging have often employed artificial auditory rhythms or limited pieces of recorded, naturalistic music, failing to account for the diversity of rhythmic structures found in natural music. As part of larger project assessing a novel music-based intervention for healthy aging, we investigated neural entrainment to musical rhythms in the electroencephalogram (EEG) while participants listened to self-selected musical recordings across a sample of younger and older adults. We specifically measured neural entrainment to the level of musical pulse-quantified here as the phase-locking value (PLV)-after normalizing the PLVs to each musical recording's detected pulse frequency. As predicted, we observed strong neural phase-locking to musical pulse, and to the sub-harmonic and harmonic levels of musical meter. Overall, PLVs were not significantly different between older and younger adults. This preserved neural entrainment to musical pulse and rhythm could support the design of music-based interventions that aim to modulate endogenous brain activity via self-selected music for healthy cognitive aging.

Cross-Species Permissivity: Structure of a Goat Adeno-Associated Virus and Its Complex with the Human Receptor AAVR.

Adeno-associated virus (AAV) is a small ssDNA satellite virus of high interest (in recombinant form) as a safe and effective gene therapy vector. AAV's human cell entry receptor (AAVR) contains polycystic kidney disease (PKD) domains bound by AAV. Seeking understanding of the spectrum of interactions, goat AAVGo.1 is investigated, because its host is the species most distant from human with reciprocal cross-species cell susceptibility. The structure of AAVGo.1, solved by cryo-EM to 2.9 Å resolution, is most similar to AAV5. Through ELISA (enzyme-linked immunosorbent assay) studies, it is shown that AAVGo.1 binds to human AAVR more strongly than do AAV2 or AAV5, and that it joins AAV5 in a class that binds exclusively to PKD domain 1 (PKD1), in contrast to other AAVs that interact primarily with PKD2. The AAVGo.1 cryo-EM structure of a complex with a PKD12 fragment of AAVR at 2.4 Å resolution shows PKD1 bound with minimal change in virus structure. There are only minor conformational adaptations in AAVR, but there is a near-rigid rotation of PKD1 with maximal displacement of the receptor domain by ~1 Å compared to PKD1 bound to AAV5. AAVGo.1 joins AAV5 as the second member of an emerging class of AAVs whose mode of receptor-binding is completely different from other AAVs, typified by AAV2. IMPORTANCE Adeno-associated virus (AAV) is a small ssDNA satellite parvovirus. As a recombinant vector with a protein shell encapsidating a transgene, recombinant AAV (rAAV) is a leading delivery vehicle for gene therapy, with two FDA-approved treatments and 150 clinical trials for 30 diseases. The human entry receptor AAVR has five PKD domains. To date, all serotypes, except AAV5, have interacted primarily with the second PKD domain, PKD2. Goat is the AAV host most distant from human with cross-species cell infectivity. AAVGo.1 is similar in structure to AAV5, the two forming a class with a distinct mode of receptor-binding. Within the two classes, binding interactions are mostly conserved, giving an indication of the latitude available in modulating delivery vectors.

Collective dynamics support group drumming, reduce variability, and stabilize tempo drift.

Humans are social animals who engage in a variety of collective activities requiring coordinated action. Among these, music is a defining and ancient aspect of human sociality. Human social interaction has largely been addressed in dyadic paradigms, and it is yet to be determined whether the ensuing conclusions generalize to larger groups. Studied more extensively in non-human animal behavior, the presence of multiple agents engaged in the same task space creates different constraints and possibilities than in simpler dyadic interactions. We addressed whether collective dynamics play a role in human circle drumming. The task was to synchronize in a group with an initial reference pattern and then maintain synchronization after it was muted. We varied the number of drummers from solo to dyad, quartet, and octet. The observed lower variability, lack of speeding up, smoother individual dynamics, and leader-less inter-personal coordination indicated that stability increased as group size increased, a sort of temporal wisdom of crowds. We propose a hybrid continuous-discrete Kuramoto model for emergent group synchronization with a pulse-based coupling that exhibits a mean field positive feedback loop. This research suggests that collective phenomena are among the factors that play a role in social cognition.

The relationship between entrainment dynamics and reading fluency assessed by sensorimotor perturbation.

A consistent relationship has been found between rhythmic processing and reading skills. Impairment of the ability to entrain movements to an auditory rhythm in clinical populations with language-related deficits, such as children with developmental dyslexia, has been found in both behavioral and neural studies. In this study, we explored the relationship between rhythmic entrainment, behavioral synchronization, reading fluency, and reading comprehension in neurotypical English- and Mandarin-speaking adults. First, we examined entrainment stability by asking participants to coordinate taps with an auditory metronome in which unpredictable perturbations were introduced to disrupt entrainment. Next, we assessed behavioral synchronization by asking participants to coordinate taps with the syllables they produced while reading sentences as naturally as possible (tap to syllable task). Finally, we measured reading fluency and reading comprehension for native English and native Mandarin speakers. Stability of entrainment correlated strongly with tap to syllable task performance and with reading fluency, and both findings generalized across English and Mandarin speakers.

A Dynamical, Radically Embodied, and Ecological Theory of Rhythm Development.

Musical rhythm abilities-the perception of and coordinated action to the rhythmic structure of music-undergo remarkable change over human development. In the current paper, we introduce a theoretical framework for modeling the development of musical rhythm. The framework, based on Neural Resonance Theory (NRT), explains rhythm development in terms of resonance and attunement, which are formalized using a general theory that includes non-linear resonance and Hebbian plasticity. First, we review the developmental literature on musical rhythm, highlighting several developmental processes related to rhythm perception and action. Next, we offer an exposition of Neural Resonance Theory and argue that elements of the theory are consistent with dynamical, radically embodied (i.e., non-representational) and ecological approaches to cognition and development. We then discuss how dynamical models, implemented as self-organizing networks of neural oscillations with Hebbian plasticity, predict key features of music development. We conclude by illustrating how the notions of dynamical embodiment, resonance, and attunement provide a conceptual language for characterizing musical rhythm development, and, when formalized in physiologically informed dynamical models, provide a theoretical framework for generating testable empirical predictions about musical rhythm development, such as the kinds of native and non-native rhythmic structures infants and children can learn, steady-state evoked potentials to native and non-native musical rhythms, and the effects of short-term (e.g., infant bouncing, infant music classes), long-term (e.g., perceptual narrowing to musical rhythm), and very-long term (e.g., music enculturation, musical training) learning on music perception-action.

Integrating music-based interventions with Gamma-frequency stimulation: Implications for healthy ageing.

In recent years, music-based interventions (MBIs) have risen in popularity as a non-invasive, sustainable form of care for treating dementia-related disorders, such as Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). Despite their clinical potential, evidence regarding the efficacy of MBIs on patient outcomes is mixed. Recently, a line of related research has begun to investigate the clinical impact of non-invasive Gamma-frequency (e.g., 40 Hz) sensory stimulation on dementia. Current work, using non-human-animal models of AD, suggests that non-invasive Gamma-frequency stimulation can remediate multiple pathophysiologies of dementia at the molecular, cellular and neural-systems scales, and, importantly, improve cognitive functioning. These findings suggest that the efficacy of MBIs could, in theory, be enhanced by incorporating Gamma-frequency stimulation into current MBI protocols. In the current review, we propose a novel clinical framework for non-invasively treating dementia-related disorders that combines previous MBIs with current approaches employing Gamma-frequency sensory stimulation. We theorize that combining MBIs with Gamma-frequency stimulation could increase the therapeutic power of MBIs by simultaneously targeting multiple biomarkers of dementia, restoring neural activity that underlies learning and memory (e.g., Gamma-frequency neural activity, Theta-Gamma coupling), and actively engaging auditory and reward networks in the brain to promote behavioural change.

Wide-Range Motion Recognition Through Insole Sensor Using Multi-Walled Carbon Nanotubes and Polydimethylsiloxane Composites.

High linearity/sensitivity and a wide dynamic sensing range are the most desirable features for pressure sensors to accurately detect and respond to external pressure stimuli. Even though a number of recent studies have demonstrated a low-cost pressure sensing device for a smart insole system by using scalable and deformable conductive materials, they still lack stretchability and desirable properties such as high sensitivity, hysteresis, linearity, and fast response time to obtain accurate and reliable data. To resolve this issue, a flexible and stretchable piezoresistive pressure sensor with high linear response over a wide pressure range is developed and integrated in a wearable insole system. The sensor uses multi-walled carbon nanotubes and polydimethylsiloxane (MWCNT/PDMS) composites with gradient density double-stacked configuration as well as randomly distributed surface microstructure (RDSM). The randomly distributed surface of the MWCNT/PDMS composite is easily and non-artificially generated by the evaporation of residual IPA solvent during a composite curing process. Due to two functional features consisting of the double-stacked composite configuration with different gradient MWCNT density and RDSM, the pressure sensor shows high linear sensitivity (∼82.5 kPa) and a pressure range of 0-1 MPa, providing extensive potential applications in monitoring human motions. Moreover, for a practical wearable application detecting the user's real-time motions, a custom-designed output signal acquisition system has been developed and integrated with the insole pressure sensor. As a result, the insole sensor can successfully detect walking, running, and jumping movements and can be used in daily life to monitor gait patterns by virtue of its long-term stability.

Adeno-Associated Virus (AAV) Gene Delivery: Dissecting Molecular Interactions upon Cell Entry.

Human gene therapy has advanced from twentieth-century conception to twenty-first-century reality. The recombinant Adeno-Associated Virus (rAAV) is a major gene therapy vector. Research continues to improve rAAV safety and efficacy using a variety of AAV capsid modification strategies. Significant factors influencing rAAV transduction efficiency include neutralizing antibodies, attachment factor interactions and receptor binding. Advances in understanding the molecular interactions during rAAV cell entry combined with improved capsid modulation strategies will help guide the design and engineering of safer and more efficient rAAV gene therapy vectors.

Bouncing the network: A dynamical systems model of auditory-vestibular interactions underlying infants' perception of musical rhythm.

Previous work suggests that auditory-vestibular interactions, which emerge during bodily movement to music, can influence the perception of musical rhythm. In a seminal study on the ontogeny of musical rhythm, Phillips-Silver and Trainor (2005) found that bouncing infants to an unaccented rhythm influenced infants' perceptual preferences for accented rhythms that matched the rate of bouncing. In the current study, we ask whether nascent, diffuse coupling between auditory and motor systems is sufficient to bootstrap short-term Hebbian plasticity in the auditory system and explain infants' preferences for accented rhythms thought to arise from auditory-vestibular interactions. First, we specify a nonlinear, dynamical system in which two oscillatory neural networks, representing developmentally nascent auditory and motor systems, interact through weak, non-specific coupling. The auditory network was equipped with short-term Hebbian plasticity, allowing the auditory network to tune its intrinsic resonant properties. Next, we simulate the effect of vestibular input (e.g., infant bouncing) on infants' perceptual preferences for accented rhythms. We found that simultaneous auditory-vestibular training shaped the model's response to musical rhythm, enhancing vestibular-related frequencies in auditory-network activity. Moreover, simultaneous auditory-vestibular training, relative to auditory- or vestibular-only training, facilitated short-term auditory plasticity in the model, producing stronger oscillator connections in the auditory network. Finally, when tested on a musical rhythm, models which received simultaneous auditory-vestibular training, but not models that received auditory- or vestibular-only training, resonated strongly at frequencies related to their "bouncing," a finding qualitatively similar to infants' preferences for accented rhythms that matched the rate of infant bouncing.

Multifrequency Hebbian plasticity in coupled neural oscillators.

We study multifrequency Hebbian plasticity by analyzing phenomenological models of weakly connected neural networks. We start with an analysis of a model for single-frequency networks previously shown to learn and memorize phase differences between component oscillators. We then study a model for gradient frequency neural networks (GrFNNs) which extends the single-frequency model by introducing frequency detuning and nonlinear coupling terms for multifrequency interactions. Our analysis focuses on models of two coupled oscillators and examines the dynamics of steady-state behaviors in multiple parameter regimes available to the models. We find that the model for two distinct frequencies shares essential dynamical properties with the single-frequency model and that Hebbian learning results in stronger connections for simple frequency ratios than for complex ratios. We then compare the analysis of the two-frequency model with numerical simulations of the GrFNN model and show that Hebbian plasticity in the latter is locally dominated by a nonlinear resonance captured by the two-frequency model.

The Structure of an AAV5-AAVR Complex at 2.5 Å Resolution: Implications for Cellular Entry and Immune Neutralization of AAV Gene Therapy Vectors.

Adeno-Associated Virus is the leading vector for gene therapy. Although it is the vector for all in vivo gene therapies approved for clinical use by the US Food and Drug Administration, its biology is still not yet fully understood. It has been shown that different serotypes of AAV bind to their cellular receptor, AAVR, in different ways. Previously we have reported a 2.4Å structure of AAV2 bound to AAVR that shows ordered structure for only one of the two AAVR domains with which AAV2 interacts. In this study we present a 2.5Å resolution structure of AAV5 bound to AAVR. AAV5 binds to the first polycystic kidney disease (PKD) domain of AAVR that was not ordered in the AAV2 structure. Interactions of AAV5 with AAVR are analyzed in detail, and the implications for AAV2 binding are explored through molecular modeling. Moreover, we find that binding sites for the antibodies ADK5a, ADK5b, and 3C5 on AAV5 overlap with the binding site of AAVR. These insights provide a structural foundation for development of gene therapy agents to better evade immune neutralization without disrupting cellular entry.

Expression and Purification of Adeno-associated Virus Virus-like Particles in a Baculovirus System and AAVR Ectodomain Constructs in E. coli.

Adeno-associated virus (AAV) is a promising gene therapy vector and the biophysical characterization of its interactions with host proteins is a critical foundation for engineering tissue targeting and immune escape. Presented here are protocols for the production of: (a) the outer protein shells (virus-like particles or VLPs) for serotype 2 (AAV-2) and (b) two fragments from the binding ectodomain of AAV's cellular receptor, AAVR. His6PKD1-2 comprises the first two polycystic kidney disease (PKD) domains, the minimal required for efficient binding of AAV, expressed with an N-terminal histidine tag. MBP-PKD1-5 is a fusion of the maltose binding protein with all five of the PKD domains of the AAVR receptor. Presented are the expression and purification of milligram quantities, ample for in vitro analyses. For AAV-2, the protocol offers an alternative to the use of (infectious) wild-type virus or transducing vectors. One of the methods for producing transducing vector is in Sf9 cells, and the production of VLPs is based on this. For AAVR, the protocols enable biochemical and biophysical characterization of virus-binding. The minimal two-domain construct allows more saturated binding to symmetry-equivalent sites on the virus, while the larger construct might be better expected to reflect the native receptor.

Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach.

Dancing and playing music require people to coordinate actions with auditory rhythms. In laboratory perception-action coordination tasks, people are asked to synchronize taps with a metronome. When synchronizing with a metronome, people tend to anticipate stimulus onsets, tapping slightly before the stimulus. The anticipation tendency increases with longer stimulus periods of up to 3500ms, but is less pronounced in trained individuals like musicians compared to non-musicians. Furthermore, external factors influence the timing of tapping. These factors include the presence of auditory feedback from one's own taps, the presence of a partner performing coordinated joint tapping, and transmission latencies (TLs) between coordinating partners. Phenomena like the anticipation tendency can be explained by delay-coupled systems, which may be inherent to the sensorimotor system during perception-action coordination. Here we tested whether a dynamical systems model based on this hypothesis reproduces observed patterns of human synchronization. We simulated behavior with a model consisting of an oscillator receiving its own delayed activity as input. Three simulation experiments were conducted using previously-published behavioral data from 1) simple tapping, 2) two-person alternating beat-tapping, and 3) two-person alternating rhythm-clapping in the presence of a range of constant auditory TLs. In Experiment 1, our model replicated the larger anticipation observed for longer stimulus intervals and adjusting the amplitude of the delayed feedback reproduced the difference between musicians and non-musicians. In Experiment 2, by connecting two models we replicated the smaller anticipation observed in human joint tapping with bi-directional auditory feedback compared to joint tapping without feedback. In Experiment 3, we varied TLs between two models alternately receiving signals from one another. Results showed reciprocal lags at points of alternation, consistent with behavioral patterns. Overall, our model explains various anticipatory behaviors, and has potential to inform theories of adaptive human synchronization.

A canonical oscillator model of cochlear dynamics.

Nonlinear responses to acoustic signals arise through active processes in the cochlea, which has an exquisite sensitivity and wide dynamic range that can be explained by critical nonlinear oscillations of outer hair cells. Here we ask how the interaction of critical nonlinearities with the basilar membrane and other organ of Corti components could determine tuning properties of the mammalian cochlea. We propose a canonical oscillator model that captures the dynamics of the interaction between the basilar membrane and organ of Corti, using a pair of coupled oscillators for each place along the cochlea. We analyze two models in which a linear oscillator, representing basilar membrane dynamics, is coupled to a nonlinear oscillator poised at a Hopf instability. The coupling in the first model is unidirectional, and that of the second is bidirectional. Parameters are determined by fitting 496 auditory-nerve (AN) tuning curves of macaque monkeys. We find that the unidirectionally and bidirectionally coupled models account equally well for threshold tuning. In addition, however, the bidirectionally coupled model exhibits low-amplitude, spontaneous oscillation in the absence of stimulation, predicting that phase locking will occur before a significant increase in firing frequency, in accordance with well known empirical observations. This leads us to a canonical oscillator cochlear model based on the fundamental principles of critical nonlinear oscillation and coupling dynamics. The model is more biologically realistic than widely used linear or nonlinear filter-based models, yet parsimoniously displays key features of nonlinear mechanistic models. It is efficient enough for computational studies of auditory perception and auditory physiology.

Modeling infants' perceptual narrowing to musical rhythms: neural oscillation and Hebbian plasticity.

Previous research suggests that infants' perception of musical rhythm is fine-tuned to culture-specific rhythmic structures over the first postnatal year of human life. To date, however, little is known about the neurobiological principles that may underlie this process. In the current study, we used a dynamical systems model featuring neural oscillation and Hebbian plasticity to simulate infants' perceptual learning of culture-specific musical rhythms. First, we demonstrate that oscillatory activity in an untrained network reflects the rhythmic structure of either a Western or a Balkan training rhythm in a veridical fashion. Next, during a period of unsupervised learning, we show that the network learns the rhythmic structure of either a Western or a Balkan training rhythm through the self-organization of network connections. Finally, we demonstrate that the learned connections affect the networks' response to violations to the metrical structure of native and nonnative rhythms, a pattern of findings that mirrors the behavioral data on infants' perceptual narrowing to musical rhythms.