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.

Evidence in animals and humans indicates that there are sensitive periods during development, times when experience or stimulation has a greater influence on behavior and brain structure. Sensitive periods are the result of an interaction between maturational processes and experience-dependent plasticity mechanisms. Previous work from our laboratory has shown that adult musicians who begin training before the age of 7 show enhancements in behavior and white matter structure compared with those who begin later. Plastic changes in white matter and gray matter are hypothesized to co-occur; therefore, the current study investigated possible differences in gray matter structure between early-trained (ET; <7) and late-trained (LT; >7) musicians, matched for years of experience. Gray matter structure was assessed using voxel-wise analysis techniques (optimized voxel-based morphometry, traditional voxel-based morphometry, and deformation-based morphometry) and surface-based measures (cortical thickness, surface area and mean curvature). Deformation-based morphometry analyses identified group differences between ET and LT musicians in right ventral premotor cortex (vPMC), which correlated with performance on an auditory motor synchronization task and with age of onset of musical training. In addition, cortical surface area in vPMC was greater for ET musicians. These results are consistent with evidence that premotor cortex shows greatest maturational change between the ages of 6–9 years and that this region is important for integrating auditory and motor information. We propose that the auditory and motor interactions required by musical practice drive plasticity in vPMC and that this plasticity is greatest when maturation is near its peak.

Humans are able to find and tap to the beat of musical rhythms varying in complexity from children's songs to modern jazz. Musical beat has no one-to-one relationship with auditory features—it is an abstract perceptual representation that emerges from the interaction between sensory cues and higher-level cognitive organization. Previous investigations have examined the neural basis of beat processing but have not tested the core phenomenon of finding and tapping to the musical beat. To test this, we used fMRI and had musicians find and tap to the beat of rhythms that varied from metrically simple to metrically complex—thus from a strong to a weak beat. Unlike most previous studies, we measured beat tapping performance during scanning and controlled for possible effects of scanner noise on beat perception. Results showed that beat finding and tapping recruited largely overlapping brain regions, including the superior temporal gyrus (STG), premotor cortex, and ventrolateral PFC (VLPFC). Beat tapping activity in STG and VLPFC was correlated with both perception and performance, suggesting that they are important for retrieving, selecting, and maintaining the musical beat. In contrast BG activity was similar in all conditions and was not correlated with either perception or production, suggesting that it may be involved in detecting auditory temporal regularity or in associating auditory stimuli with a motor response. Importantly, functional connectivity analyses showed that these systems interact, indicating that more basic sensorimotor mechanisms instantiated in the BG work in tandem with higher-order cognitive mechanisms in PFC.

Music performance requires control of two sequential structures: the ordering of pitches and the temporal intervals between successive pitches. Whether pitch and temporal structures are processed as separate or integrated features remains unclear. A repetition suppression paradigm compared neural and behavioral correlates of mapping pitch sequences and temporal sequences to motor movements in music performance. Fourteen pianists listened to and performed novel melodies on an MR-compatible piano keyboard during fMRI scanning. The pitch or temporal patterns in the melodies either changed or repeated (remained the same) across consecutive trials. We expected decreased neural response to the patterns (pitch or temporal) that repeated across trials relative to patterns that changed. Pitch and temporal accuracy were high, and pitch accuracy improved when either pitch or temporal sequences repeated over trials. Repetition of either pitch or temporal sequences was associated with linear BOLD decrease in frontal–parietal brain regions including dorsal and ventral premotor cortex, pre-SMA, and superior parietal cortex. Pitch sequence repetition (in contrast to temporal sequence repetition) was associated with linear BOLD decrease in the intraparietal sulcus (IPS) while pianists listened to melodies they were about to perform. Decreased BOLD response in IPS also predicted increase in pitch accuracy only when pitch sequences repeated. Thus, behavioral performance and neural response in sensorimotor mapping networks were sensitive to both pitch and temporal structure, suggesting that pitch and temporal structure are largely integrated in auditory–motor transformations. IPS may be involved in transforming pitch sequences into spatial coordinates for accurate piano performance.

Much is known about the motor system and its role in simple movement execution. However, little is understood about the neural systems underlying auditory-motor integration in the context of musical rhythm, or the enhanced ability of musicians to execute precisely timed sequences. Using functional magnetic resonance imaging, we investigated how performance and neural activity were modulated as musicians and nonmusicians tapped in synchrony with progressively more complex and less metrically structured auditory rhythms. A functionally connected network was implicated in extracting higher-order features of a rhythm's temporal structure, with the dorsal premotor cortex mediating these auditory-motor interactions. In contrast to past studies, musicians recruited the prefrontal cortex to a greater degree than nonmusicians, whereas secondary motor regions were recruited to the same extent. We argue that the superior ability of musicians to deconstruct and organize a rhythm's temporal structure relates to the greater involvement of the prefrontal cortex mediating working memory.