Context changes judgments of liking and predictability for melodies.

Predictability plays an important role in the experience of musical pleasure. By leveraging expectations, music induces pleasure through tension and surprise. However, musical predictions draw on both prior knowledge and immediate context. Similarly, musical pleasure, which has been shown to depend on predictability, may also vary relative to the individual and context. Although research has demonstrated the influence of both long-term knowledge and stimulus features in influencing expectations, it is unclear how perceptions of a melody are influenced by comparisons to other music pieces heard in the same context. To examine the effects of context we compared how listeners' judgments of two distinct sets of stimuli differed when they were presented alone or in combination. Stimuli were excerpts from a repertoire of Western music and a set of experimenter created melodies. Separate groups of participants rated liking and predictability for each set of stimuli alone and in combination. We found that when heard together, the Repertoire stimuli were more liked and rated as less predictable than if they were heard alone, with the opposite pattern being observed for the Experimental stimuli. This effect was driven by a change in ratings between the Alone and Combined conditions for each stimulus set. These findings demonstrate a context-based shift of predictability ratings and derived pleasure, suggesting that judgments stem not only from the physical properties of the stimulus, but also vary relative to other options available in the immediate context.

Using cortico-cerebellar structural patterns to classify early- and late-trained musicians.

A body of current evidence suggests that there is a sensitive period for musical training: people who begin training before the age of seven show better performance on tests of musical skill, and also show differences in brain structure-especially in motor cortical and cerebellar regions-compared with those who start later. We used support vector machine models-a subtype of supervised machine learning-to investigate distributed patterns of structural differences between early-trained (ET) and late-trained (LT) musicians and to better understand the age boundaries of the sensitive period for early musicianship. After selecting regions of interest from the cerebellum and cortical sensorimotor regions, we applied recursive feature elimination with cross-validation to produce a model which optimally and accurately classified ET and LT musicians. This model identified a combination of 17 regions, including 9 cerebellar and 8 sensorimotor regions, and maintained a high accuracy and sensitivity (true positives, i.e., ET musicians) without sacrificing specificity (true negatives, i.e., LT musicians). Critically, this model-which defined ET musicians as those who began their training before the age of 7-outperformed all other models in which age of start was earlier or later (between ages 5-10). Our model's ability to accurately classify ET and LT musicians provides additional evidence that musical training before age 7 affects cortico-cerebellar structure in adulthood, and is consistent with the hypothesis that connected brain regions interact during development to reciprocally influence brain and behavioral maturation.

Early musical training shapes cortico-cerebellar structural covariation.

Adult abilities in complex cognitive domains such as music appear to depend critically on the age at which training or experience begins, and relevant experience has greater long-term effects during periods of peak maturational change. Previous work has shown that early trained musicians (ET; < age 7) out-perform later-trained musicians (LT; > age 7) on tests of musical skill, and also have larger volumes of the ventral premotor cortex (vPMC) and smaller volumes of the cerebellum. These cortico-cerebellar networks mature and function in relation to one another, suggesting that early training may promote coordinated developmental plasticity. To test this hypothesis, we examined structural covariation between cerebellar volume and cortical thickness (CT) in sensorimotor regions in ET and LT musicians and non-musicians (NMs). Results show that ETs have smaller volumes in cerebellar lobules connected to sensorimotor cortices, while both musician groups had greater cortical thickness in right pre-supplementary motor area (SMA) and right PMC compared to NMs. Importantly, early musical training had a specific effect on structural covariance between the cerebellum and cortex: NMs showed negative correlations between left lobule VI and right pre-SMA and PMC, but this relationship was reduced in ET musicians. ETs instead showed a significant negative correlation between vermal IV and right pre-SMA and dPMC. Together, these results suggest that early musical training has differential impacts on the maturation of cortico-cerebellar networks important for optimizing sensorimotor performance. This conclusion is consistent with the hypothesis that connected brain regions interact during development to reciprocally influence brain and behavioral maturation.

Understanding Sensitive Period Effects in Musical Training.

Adult ability in complex cognitive domains, including music, is commonly thought of as the product of gene-environment interactions, where genetic predispositions influence and are modulated by experience, resulting in the final phenotypic expression. Recently, however, the important contribution of maturation to gene-environment interactions has become better understood. Thus, the timing of exposure to specific experience, such as music training, has been shown to produce long-term impacts on adult behaviour and the brain. Work from our lab and others shows that musical training before the ages of 7-9 enhances performance on musical tasks and modifies brain structure and function, sometimes in unexpected ways. The goal of this paper is to present current evidence for sensitive period effects for musical training in the context of what is known about brain maturation and to present a framework that integrates genetic, environmental and maturational influences on the development of musical skill. We believe that this framework can also be applied more broadly to understanding how predispositions, brain development and experience interact.

Effector-independent brain network for auditory-motor integration: fMRI evidence from singing and cello playing.

Many everyday tasks share high-level sensory goals but differ in the movements used to accomplish them. One example of this is musical pitch regulation, where the same notes can be produced using the vocal system or a musical instrument controlled by the hands. Cello playing has previously been shown to rely on brain structures within the singing network for performance of single notes, except in areas related to primary motor control, suggesting that the brain networks for auditory feedback processing and sensorimotor integration may be shared (Segado et al. 2018). However, research has shown that singers and cellists alike can continue singing/playing in tune even in the absence of auditory feedback (Chen et al. 2013, Kleber et al. 2013), so different paradigms are required to test feedback monitoring and control mechanisms. In singing, auditory pitch feedback perturbation paradigms have been used to show that singers engage a network of brain regions including anterior cingulate cortex (ACC), anterior insula (aINS), and intraparietal sulcus (IPS) when compensating for altered pitch feedback, and posterior superior temporal gyrus (pSTG) and supramarginal gyrus (SMG) when ignoring it (Zarate et al. 2005, 2008). To determine whether the brain networks for cello playing and singing directly overlap in these sensory-motor integration areas, in the present study expert cellists were asked to compensate for or ignore introduced pitch perturbations when singing/playing during fMRI scanning. We found that cellists were able to sing/play target tones, and compensate for and ignore introduced feedback perturbations equally well. Brain activity overlapped for singing and playing in IPS and SMG when compensating, and pSTG and dPMC when ignoring; differences between singing/playing across all three conditions were most prominent in M1, centered on the relevant motor effectors (hand, larynx). These findings support the hypothesis that pitch regulation during cello playing relies on structures within the singing network and suggests that differences arise primarily at the level of forward motor control.

The sensation of groove engages motor and reward networks.

The sensation of groove has been defined as the pleasurable desire to move to music, suggesting that both motor timing and reward processes are involved in this experience. Although many studies have investigated rhythmic timing and musical reward separately, none have examined whether the associated cortical and subcortical networks are engaged while participants listen to groove-based music. In the current study, musicians and non-musicians listened to and rated experimentally controlled groove-based stimuli while undergoing functional magnetic resonance imaging. Medium complexity rhythms elicited higher ratings of pleasure and wanting to move and were associated with activity in regions linked to beat perception and reward, as well as prefrontal and parietal regions implicated in generating and updating stimuli-based expectations. Activity in basal ganglia regions of interest, including the nucleus accumbens, caudate and putamen, was associated with ratings of pleasure and wanting to move, supporting their important role in the sensation of groove. We propose a model in which different cortico-striatal circuits interact to support the mechanisms underlying groove, including internal generation of the beat, beat-based expectations, and expectation-based affect. These results show that the sensation of groove is supported by motor and reward networks in the brain and, along with our proposed model, suggest that the basal ganglia are crucial nodes in networks that interact to generate this powerful response to music.

The descending motor tracts are different in dancers and musicians.

Long-term motor training, such as dance or gymnastics, has been associated with increased diffusivity and reduced fiber coherence in regions including the corticospinal tract. Comparisons between different types of motor experts suggest that experience might result in specific structural changes related to the trained effectors (e.g., hands or feet). However, previous studies have not segregated the descending motor pathways from different body-part representations in motor cortex (M1). Further, most previous diffusion tensor imaging studies used whole-brain analyses based on a single tensor, which provide poor information about regions where multiple white matter (WM) tracts cross. Here, we used multi-tensor probabilistic tractography to investigate the specific components of the descending motor pathways in well-matched groups of dancers, musicians and controls. To this aim, we developed a procedure to identify the WM regions below the motor representations of the head, hand, trunk and leg that served as seeds for tractography. Dancers showed increased radial diffusivity (RD) in comparison with musicians, in descending motor pathways from all the regions, particularly in the right hemisphere, whereas musicians had increased fractional anisotropy (FA) in the hand and the trunk/arm motor tracts. Further, dancers showed larger volumes compared to both other groups. Finally, we found negative correlations between RD and FA with the age of start of dance or music training, respectively, and between RD and performance on a melody task, and positive correlations between RD and volume with performance on a whole-body dance task. These findings suggest that different types of training might have different effects on brain structure, likely because dancers must coordinate movements of the entire body, whereas musicians focus on fewer effectors.

Rhythm and time in the premotor cortex.

Many animals can encode temporal intervals and use them to plan their actions, but only humans can flexibly extract a regular beat from complex patterns, such as musical rhythms. Beat-based timing is hypothesized to rely on the integration of sensory information with temporal information encoded in motor regions such as the medial premotor cortex (MPC), but how beat-based timing might be encoded in neuronal populations is mostly unknown. Gámez and colleagues show that the MPC encodes temporal information via a population code visible as circular trajectories in state space; these patterns may represent precursors to more-complex skills such as beat-based timing.

Contributions of age of start, cognitive abilities and practice to musical task performance in childhood.

Studies with adult musicians show that beginning lessons before age seven is associated with better performance on musical tasks and enhancement in auditory and motor brain regions. It is hypothesized that early training interacts with periods of heightened neural development to promote greater plasticity and better learning and performance later in life. However, we do not know whether such effects can be observed in childhood. Moreover, we do not know the degree to which such effects are related to training, or whether early training has different effects on particular musical skills depending on their cognitive, perceptual or motor requirements. To address these questions, we compared groups of child musicians who had started lessons earlier or later on age-normed tests of rhythm synchronization and melody discrimination. We also matched for age, years of experience, working memory and global cognitive ability. Results showed that children who started early performed better on simple melody discrimination and that scores on this task were predicted by both age of start (AoS) and cognitive ability. There was no effect of AoS for the more complex rhythm or transposed melody tasks, but these scores were significantly predicted by working memory ability, and for transposed melodies, by hours of weekly practice. These findings provide the first evidence that earlier AoS for music training in childhood results in enhancement of specific musical skills. Integrating these results with those for adult musicians, we hypothesize that early training has an immediate impact on simple melody discrimination skills that develop early, while more complex abilities, like synchronization and transposition require both further maturation and additional training.

The sensation of groove is affected by the interaction of rhythmic and harmonic complexity.

The pleasurable desire to move to music, also known as groove, is modulated by rhythmic complexity. How the sensation of groove is influenced by other musical features, such as the harmonic complexity of individual chords, is less clear. To address this, we asked people with a range of musical experience to rate stimuli that varied in both rhythmic and harmonic complexity. Rhythm showed an inverted U-shaped relationship with ratings of pleasure and wanting to move, whereas medium and low complexity chords were rated similarly. Pleasure mediated the effect of harmony on wanting to move and high complexity chords attenuated the effect of rhythm on pleasure. We suggest that while rhythmic complexity is the primary driver, harmony, by altering emotional valence, modulates the attentional and temporal prediction processes that underlie rhythm perception. Investigation of the effects of musical training with both regression and group comparison showed that training increased the inverted U effect for harmony and rhythm, respectively. Taken together, this work provides important new information about how the prediction and entrainment processes involved in rhythm perception interact with musical pleasure.

Structural Covariance Analysis Reveals Differences Between Dancers and Untrained Controls.

Dancers and musicians differ in brain structure from untrained individuals. Structural covariance (SC) analysis can provide further insight into training-associated brain plasticity by evaluating interregional relationships in gray matter (GM) structure. The objectives of the present study were to compare SC of cortical thickness (CT) between expert dancers, expert musicians and untrained controls, as well as to examine the relationship between SC and performance on dance- and music-related tasks. A reduced correlation between CT in the left dorsolateral prefrontal cortex (DLPFC) and mean CT across the whole brain was found in the dancers compared to the controls, and a reduced correlation between these two CT measures was associated with higher performance on a dance video game task. This suggests that the left DLPFC is structurally decoupled in dancers and may be more strongly affected by local training-related factors than global factors in this group. This work provides a better understanding of structural brain connectivity and training-induced brain plasticity, as well as their interaction with behavior in dance and music.

Efficacy of Auditory versus Motor Learning for Skilled and Novice Performers.

Humans must learn a variety of sensorimotor skills, yet the relative contributions of sensory and motor information to skill acquisition remain unclear. Here we compare the behavioral and neural contributions of perceptual learning to that of motor learning, and we test whether these contributions depend on the expertise of the learner. Pianists and nonmusicians learned to perform novel melodies on a piano during fMRI scanning in four learning conditions: listening (auditory learning), performing without auditory feedback (motor learning), performing with auditory feedback (auditory-motor learning), or observing visual cues without performing or listening (cue-only learning). Visual cues were present in every learning condition and consisted of musical notation for pianists and spatial cues for nonmusicians. Melodies were performed from memory with no visual cues and with auditory feedback (recall) five times during learning. Pianists showed greater improvements in pitch and rhythm accuracy at recall during auditory learning compared with motor learning. Nonmusicians demonstrated greater rhythm improvements at recall during auditory learning compared with all other learning conditions. Pianists showed greater primary motor response at recall during auditory learning compared with motor learning, and response in this region during auditory learning correlated with pitch accuracy at recall and with auditory-premotor network response during auditory learning. Nonmusicians showed greater inferior parietal response during auditory compared with auditory-motor learning, and response in this region correlated with pitch accuracy at recall. Results suggest an advantage for perceptual learning compared with motor learning that is both general and expertise-dependent. This advantage is hypothesized to depend on feedforward motor control systems that can be used during learning to transform sensory information into motor production.

Auditory prediction cues motor preparation in the absence of movements.

There is increasing evidence for integrated representation of sensory and motor information in the brain, and that seeing or hearing action-related stimuli may automatically cue the movements required to respond to or produce them. In this study we tested whether anticipation of tones in a known melody automatically activates corresponding motor representations in a predictive way, in preparation for potential upcoming movements. Therefore, we trained 20 non-musicians (8 men, 12 women) to play a simple melody. Then, while they passively listened to the learned or unlearned melodies, we applied single pulse transcranial magnetic stimulation (TMS) over M1 to measure motor evoked potentials from the associated finger muscle either preceding or following the onset of individual tones. Our results show that listening to the learned melody increased corticospinal excitability for specific finger muscles before tone onset. This demonstrates that predictable auditory information can activate motor representations in an anticipatory muscle-specific manner, even in the absence of intention to move. This suggests that the motor system is involved in the prediction of sensory events, likely based on auditory-parietal-prefrontal feedforward/feedback loops that automatically prepare predictable sound-related actions independent of actual execution and the associated auditory feedback. Overall, we propose that multimodal forward models of upcoming sounds and actions support motor preparation, facilitate error detection and correction, and guide perception.

Dance and music share gray matter structural correlates.

Intensive practise of sensorimotor skills, such as music and dance, is associated with brain structural plasticity. While the neural correlates of music have been well-investigated, less is known about the neural correlates of dance. Additionally, the gray matter structural correlates of dance versus music training have not yet been directly compared. The objectives of the present study were to compare gray matter structure as measured by surface- and voxel-based morphometry between expert dancers, expert musicians and untrained controls, as well as to correlate gray matter structure with performance on dance- and music-related tasks. Dancers and musicians were found to have increased cortical thickness compared to controls in superior temporal regions. Gray matter structure in the superior temporal gyrus was also correlated with performance on dance imitation, rhythm synchronization and melody discrimination tasks. These results suggest that superior temporal regions are important in both dance- and music-related skills and may be affected similarly by both types of long-term intensive training. This work advances knowledge of the neural correlates of dance and music, as well as training-associated brain plasticity in general.

The Impact of Instrument-Specific Musical Training on Rhythm Perception and Production.

Studies comparing musicians and non-musicians have shown that musical training can improve rhythmic perception and production. These findings tell us that training can result in rhythm processing advantages, but they do not tell us whether practicing a particular instrument could lead to specific effects on rhythm perception or production. The current study used a battery of four rhythm perception and production tasks that were designed to test both higher- and lower-level aspects of rhythm processing. Four groups of musicians (drummers, singers, pianists, string players) and a control group of non-musicians were tested. Within-task differences in performance showed that factors such as meter, metrical complexity, tempo, and beat phase significantly affected the ability to perceive and synchronize taps to a rhythm or beat. Musicians showed better performance on all rhythm tasks compared to non-musicians. Interestingly, our results revealed no significant differences between musician groups for the vast majority of task measures. This was despite the fact that all musicians were selected to have the majority of their training on the target instrument, had on average more than 10 years of experience on their instrument, and were currently practicing. These results suggest that general musical experience is more important than specialized musical experience with regards to perception and production of rhythms.

Sensorimotor integration is enhanced in dancers and musicians.

Studying individuals with specialized training, such as dancers and musicians, provides an opportunity to investigate how intensive practice of sensorimotor skills affects behavioural performance across various domains. While several studies have found that musicians have improved motor, perceptual and sensorimotor integration skills compared to untrained controls, fewer studies have examined the effect of dance training on such skills. Moreover, no study has specifically compared the effects of dance versus music training on perceptual or sensorimotor performance. To this aim, in the present study, expert dancers, expert musicians and untrained controls were tested on a range of perceptual and sensorimotor tasks designed to discriminate performance profiles across groups. Dancers performed better than musicians and controls on a dance imitation task (involving whole-body movement), but musicians performed better than dancers and controls on a musical melody discrimination task as well as on a rhythm synchronization task (involving finger tapping). These results indicate that long-term intensive dance and music training are associated with distinct enhancements in sensorimotor skills. This novel work advances knowledge of the effects of long-term dance versus music training and has potential applications in therapies for motor disorders.

Dance and the brain: a review.

Dance is a universal form of human expression that offers a rich source for scientific study. Dance provides a unique opportunity to investigate brain plasticity and its interaction with behavior. Several studies have investigated the behavioral correlates of dance, but less is known about the brain basis of dance. Studies on dance observation suggest that long- and short-term dance training affect brain activity in the action observation and simulation networks. Despite methodological challenges, the feasibility of conducting neuroimaging while dancing has been demonstrated, and several brain regions have been implicated in dance execution. Preliminary work from our laboratory suggests that long-term dance training changes both gray and white matter structure. This article provides a critical summary of work investigating the neural correlates of dance. It covers functional neuroimaging studies of dance observation and performance as well as structural neuroimaging studies of expert dancers. To stimulate ongoing dialogue between dance and science, future directions in dance and brain research as well as implications are discussed. Research on the neuroscience of dance will lead to a better understanding of brain-behavior relationships and brain plasticity in experts and nonexperts and can be applied to the development of dance-based therapy programs.

Expert music performance: cognitive, neural, and developmental bases.

In this chapter, we explore what happens in the brain of an expert musician during performance. Understanding expert music performance is interesting to cognitive neuroscientists not only because it tests the limits of human memory and movement, but also because studying expert musicianship can help us understand skilled human behavior in general. In this chapter, we outline important facets of our current understanding of the cognitive and neural basis for music performance, and developmental factors that may underlie musical ability. We address three main questions. (1) What is expert performance? (2) How do musicians achieve expert-level performance? (3) How does expert performance come about? We address the first question by describing musicians' ability to remember, plan, execute, and monitor their performances in order to perform music accurately and expressively. We address the second question by reviewing evidence for possible cognitive and neural mechanisms that may underlie or contribute to expert music performance, including the integration of sound and movement, feedforward and feedback motor control processes, expectancy, and imagery. We further discuss how neural circuits in auditory, motor, parietal, subcortical, and frontal cortex all contribute to different facets of musical expertise. Finally, we address the third question by reviewing evidence for the heritability of musical expertise and for how expertise develops through training and practice. We end by discussing outlooks for future work.

Effects of age and cognitive load on response reprogramming.

A dual-task paradigm was used to examine the effect of cognitive load on motor reprogramming. We propose that in the face of conflict, both executive control and motor control mechanisms become more interconnected in the process of reprogramming motor behaviors. If so, one would expect a concurrent cognitive load to compromise younger adults' (YAs) motor reprogramming ability and further exacerbate the response reprogramming ability of older adults (OAs). Nineteen YAs and 14 OAs overlearned a sequence of key presses. Deviations of the practiced sequence were introduced to assess motor reprogramming ability. A Serial Sevens Test was used as the cognitive load. A 3D motion capture system was used to parse finger movements into planning and motor execution times. Global response time analysis revealed that under single-task conditions, during prepotent transitions, OAs responded as quickly as YAs, but they were disproportionately worse than YAs during conflict transitions. Under dual-task conditions, YAs performance became more similar to that of OAs. Movement data were decomposed into planning and movement time, revealing that under single-task conditions, when responding to conflicting stimuli YAs reduced their movement time in order to compensate for delayed planning time; however, additional cognitive load prevented them from exhibiting this compensatory hastening on conflict transitions. We propose that age-related declines in response reprogramming may be linked to reduced cognitive capacity. Current findings suggest that cognitive capacity, reduced in the case of OAs or YAs under divided attention conditions, influences the ability to flexibly adapt to conflicting conditions.