The Structure and Acquisition of Sensorimotor Maps.

One of the puzzles of learning to talk or play a musical instrument is how we learn which movement produces a particular sound: an audiomotor map. Existing research has used mappings that are already well learned such as controlling a cursor using a computer mouse. By contrast, the acquisition of novel sensorimotor maps was studied by having participants learn arm movements to auditory targets. These sounds did not come from different directions but, like speech, were only distinguished by their frequencies. It is shown that learning involves forming not one but two maps: a point map connecting sensory targets with motor commands and an error map linking sensory errors to motor corrections. Learning a point map is possible even when targets never repeat. Thus, although participants make errors, there is no opportunity to correct them because the target is different on every trial, and therefore learning cannot be driven by error correction. Furthermore, when the opportunity for error correction is provided, it is seen that acquiring error correction is itself a learning process that changes over time and results in an error map. In principle, the error map could be derived from the point map, but instead, these two maps are independently acquired and jointly enable sensorimotor control and learning. A computational model shows that this dual encoding is optimal and simulations based on this architecture predict that learning the two maps results in performance improvements comparable with those observed empirically.

Error-related Persistence of Motor Activity in Resting-state Networks.

The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing increased activations for larger movement error, comprising the cerebellum, parietal, visual, somatosensory, and cortical motor areas, and the other being more activated for movements with lower error, comprising the ventral putamen and the OFC. After learning, changes in brain connectivity at rest were found predominantly in areas that had shown increased activation for larger error during task, specifically the cerebellum and its connections with motor, visual, and somatosensory cortex. The findings indicate that, although both errors and accurate movements are important during the active stage of motor learning, the changes in brain activity observed at rest primarily reflect networks that process errors. This suggests that error-related networks are represented in the initial stages of motor memory formation.

Somatosensory working memory in human reinforcement-based motor learning.

Recent studies using visuomotor adaptation and sequence learning tasks have assessed the involvement of working memory in the visuospatial domain. The capacity to maintain previously performed movements in working memory is perhaps even more important in reinforcement-based learning to repeat accurate movements and avoid mistakes. Using this kind of task in the present work, we tested the relationship between somatosensory working memory and motor learning. The first experiment involved separate memory and motor learning tasks. In the memory task, the participant's arm was displaced in different directions by a robotic arm, and the participant was asked to judge whether a subsequent test direction was one of the previously presented directions. In the motor learning task, participants made reaching movements to a hidden visual target and were provided with positive feedback as reinforcement when the movement ended in the target zone. It was found that participants that had better somatosensory working memory showed greater motor learning. In a second experiment, we designed a new task in which learning and working memory trials were interleaved, allowing us to study participants' memory for movements they performed as part of learning. As in the first experiment, we found that participants with better somatosensory working memory also learned more. Moreover, memory performance for successful movements was better than for movements that failed to reach the target. These results suggest that somatosensory working memory is involved in reinforcement motor learning and that this memory preferentially keeps track of reinforced movements. NEW & NOTEWORTHY The present work examined somatosensory working memory in reinforcement-based motor learning. Working memory performance was reliably correlated with the extent of learning. With the use of a paradigm in which learning and memory trials were interleaved, memory was assessed for movements performed during learning. Movements that received positive feedback were better remembered than movements that did not. Thus working memory does not track all movements equally but is biased to retain movements that were rewarded.

Tap Arduino: An Arduino microcontroller for low-latency auditory feedback in sensorimotor synchronization experiments.

Timing abilities are often measured by having participants tap their finger along with a metronome and presenting tap-triggered auditory feedback. These experiments predominantly use electronic percussion pads combined with software (e.g., FTAP or Max/MSP) that records responses and delivers auditory feedback. However, these setups involve unknown latencies between tap onset and auditory feedback and can sometimes miss responses or record multiple, superfluous responses for a single tap. These issues may distort measurements of tapping performance or affect the performance of the individual. We present an alternative setup using an Arduino microcontroller that addresses these issues and delivers low-latency auditory feedback. We validated our setup by having participants (N = 6) tap on a force-sensitive resistor pad connected to the Arduino and on an electronic percussion pad with various levels of force and tempi. The Arduino delivered auditory feedback through a pulse-width modulation (PWM) pin connected to a headphone jack or a wave shield component. The Arduino's PWM (M = 0.6 ms, SD = 0.3) and wave shield (M = 2.6 ms, SD = 0.3) demonstrated significantly lower auditory feedback latencies than the percussion pad (M = 9.1 ms, SD = 2.0), FTAP (M = 14.6 ms, SD = 2.8), and Max/MSP (M = 15.8 ms, SD = 3.4). The PWM and wave shield latencies were also significantly less variable than those from FTAP and Max/MSP. The Arduino missed significantly fewer taps, and recorded fewer superfluous responses, than the percussion pad. The Arduino captured all responses, whereas at lower tapping forces, the percussion pad missed more taps. Regardless of tapping force, the Arduino outperformed the percussion pad. Overall, the Arduino is a high-precision, low-latency, portable, and affordable tool for auditory experiments.

Playing beautifully when you have to be fast: spatial and temporal symmetries of movement patterns in skilled piano performance at different tempi.

Humans are capable of learning a variety of motor skills such as playing the piano. Performance of these skills is subject to multiple constraints, such as musical phrasing or speed requirements, and these constraints vary from one context to another. In order to understand how the brain controls highly skilled movements, we investigated pianists playing musical scales with their left or right hand at various speeds. Pianists showed systematic temporal deviations away from regularity. At slow tempi, pianists slowed down at the beginning and end of the movement (which we call phrasal template). At fast tempi, temporal deviation traces consisted of three peak delays caused by a thumb-under manoeuvre (which we call neuromuscular template). Intermediate tempi were a linear combination trade-off between these two. We introduce and cross-validate a simple four-parameter model that predicted the timing deviation of each individual note across tempi (R(2) = 0.70). The model can be fitted on the data of individual pianists, providing a novel quantification of expert performance. The present study shows that the motor system can generate complex movements through a dynamic combination of simple movement templates. This provides insight into how the motor system flexibly adapts to varying contextual constraints.

Subtle Patterns of Altered Responsiveness to Delayed Auditory Feedback during Finger Tapping in People Who Stutter.

Differences in sensorimotor integration mechanisms have been observed between people who stutter (PWS) and controls who do not. Delayed auditory feedback (DAF) introduces timing discrepancies between perception and action, disrupting sequence production in verbal and non-verbal domains. While DAF consistently enhances speech fluency in PWS, its impact on non-verbal sensorimotor synchronization abilities remains unexplored. A total of 11 PWS and 13 matched controls completed five tasks: (1) unpaced tapping; (2) synchronization-continuation task (SCT) without auditory feedback; (3) SCT with DAF, with instruction either to align the sound in time with the metronome; or (4) to ignore the sound and align their physical tap to the metronome. Additionally, we measured participants' sensitivity to detecting delayed feedback using a (5) delay discrimination task. Results showed that DAF significantly affected performance in controls as a function of delay duration, despite being irrelevant to the task. Conversely, PWS performance remained stable across delays. When auditory feedback was absent, no differences were found between PWS and controls. Moreover, PWS were less able to detect delays in speech and tapping tasks. These findings show subtle differences in non-verbal sensorimotor performance between PWS and controls, specifically when action-perception loops are disrupted by delays, contributing to models of sensorimotor integration in stuttering.

Effects of dopaminergic and subthalamic stimulation on musical performance.

Although subthalamic-deep brain stimulation (STN-DBS) is an efficient treatment for Parkinson's disease (PD), its effects on fine motor functions are not clear. We present the case of a professional violinist with PD treated with STN-DBS. DBS improved musical articulation, intonation and emotional expression and worsened timing relative to a timekeeper (metronome). The same effects were found for dopaminergic treatment. These results suggest that STN-DBS, mimicking the effects of dopaminergic stimulation, improves fine-tuned motor behaviour whilst impairing timing precision.

Recognition memory for human motor learning.

Motor skill retention is typically measured by asking participants to reproduce previously learned movements from memory. The analog of this retention test (recall memory) in human verbal memory is known to underestimate how much learning is actually retained. Here we asked whether information about previously learned movements, which can no longer be reproduced, is also retained. Following visuomotor adaptation, we used tests of recall that involved reproduction of previously learned movements and tests of recognition in which participants were asked whether a candidate limb displacement, produced by a robot arm held by the subject, corresponded to a movement direction that was experienced during active training. The main finding was that 24 h after training, estimates of recognition memory were about twice as accurate as those of recall memory. Thus, there is information about previously learned movements that is not retrieved using recall testing but can be accessed in tests of recognition. We conducted additional tests to assess whether, 24 h after learning, recall for previously learned movements could be improved by presenting passive movements as retrieval cues. These tests were conducted immediately prior to recall testing and involved the passive playback of a small number of movements, which were spread across the workspace and included both adapted and baseline movements, without being marked as such. This technique restored recall memory for movements to levels close to those of recognition memory performance. Thus, somatic information may enable retrieval of otherwise inaccessible motor memories.

From known to unknown: moving to unvisited locations in a novel sensorimotor map.

Sensorimotor learning requires knowledge of the relationship between movements and sensory effects: a sensorimotor map. Generally, these mappings are not innate but have to be learned. During learning, the challenge is to build a continuous map from a set of discrete observations, that is, predict locations of novel targets. One hypothesis is that the learner linearly interpolates among discrete observations that are already in the map. Here, this hypothesis is tested by exposing human subjects to a novel mapping between arm movements and sounds. Participants were passively moved to the edges of the workspace receiving the corresponding sounds and then were presented intermediate sounds and asked to make movements to locations they thought corresponded to those sounds. It is observed that average movements roughly match linear interpolation of the space. However, the actual distribution of participants' movements is best described by a bimodal reaching strategy in which they move to one of two locations near the workspace edge where they had prior exposure to the sound-movement pairing. These results suggest that interpolation happens to a limited extent only and that the acquisition of sensorimotor maps may not be driven by interpolation but instead relies on a flexible recombination of instance-based learning.

Auditory feedback in error-based learning of motor regularity.

Music and speech are skills that require high temporal precision of motor output. A key question is how humans achieve this timing precision given the poor temporal resolution of somatosensory feedback, which is classically considered to drive motor learning. We hypothesise that auditory feedback critically contributes to learn timing, and that, similarly to visuo-spatial learning models, learning proceeds by correcting a proportion of perceived timing errors. Thirty-six participants learned to tap a sequence regularly in time. For participants in the synchronous-sound group, a tone was presented simultaneously with every keystroke. For the jittered-sound group, the tone was presented after a random delay of 10-190 ms following the keystroke, thus degrading the temporal information that the sound provided about the movement. For the mute group, no keystroke-triggered sound was presented. In line with the model predictions, participants in the synchronous-sound group were able to improve tapping regularity, whereas the jittered-sound and mute group were not. The improved tapping regularity of the synchronous-sound group also transferred to a novel sequence and was maintained when sound was subsequently removed. The present findings provide evidence that humans engage in auditory feedback error-based learning to improve movement quality (here reduce variability in sequence tapping). We thus elucidate the mechanism by which high temporal precision of movement can be achieved through sound in a way that may not be possible with less temporally precise somatosensory modalities. Furthermore, the finding that sound-supported learning generalises to novel sequences suggests potential rehabilitation applications.

Thresholds of auditory-motor coupling measured with a simple task in musicians and non-musicians: was the sound simultaneous to the key press?

The human brain is able to predict the sensory effects of its actions. But how precise are these predictions? The present research proposes a tool to measure thresholds between a simple action (keystroke) and a resulting sound. On each trial, participants were required to press a key. Upon each keystroke, a woodblock sound was presented. In some trials, the sound came immediately with the downward keystroke; at other times, it was delayed by a varying amount of time. Participants were asked to verbally report whether the sound came immediately or was delayed. Participants' delay detection thresholds (in msec) were measured with a staircase-like procedure. We hypothesised that musicians would have a lower threshold than non-musicians. Comparing pianists and brass players, we furthermore hypothesised that, as a result of a sharper attack of the timbre of their instrument, pianists might have lower thresholds than brass players. Our results show that non-musicians exhibited higher thresholds for delay detection (180 ± 104 ms) than the two groups of musicians (102 ±65 ms), but there were no differences between pianists and brass players. The variance in delay detection thresholds could be explained by variance i n sensorimotor synchronisation capacities as well as variance in a purely auditory temporal irregularity detection measure. This suggests that the brain's capacity to generate temporal predictions of sensory consequences can be decomposed into general temporal prediction capacities together with auditory-motor coupling. These findings indicate that the brain has a relatively large window of integration within which an action and its resulting effect are judged as simultaneous. Furthermore, musical expertise may narrow this window down, potentially due to a more refined temporal prediction. This novel paradigm provides a simple test to estimate the temporal precision of auditory-motor action-effect coupling, and the paradigm can readily be incorporated in studies investigating both healthy and patient populations.

Music-supported motor training after stroke reveals no superiority of synchronization in group therapy.

BACKGROUND: Music-supported therapy has been shown to be an effective tool for rehabilitation of motor deficits after stroke. A unique feature of music performance is that it is inherently social: music can be played together in synchrony. AIM: The present study explored the potential of synchronized music playing during therapy, asking whether synchronized playing could improve fine motor rehabilitation and mood. METHOD: Twenty-eight patients in neurological early rehabilitation after stroke with no substantial previous musical training were included. Patients learned to play simple finger exercises and familiar children's songs on the piano for 10 sessions of half an hour. Patients first received three individual therapy sessions and then continued in pairs. The patient pairs were divided into two groups. Patients in one group played synchronously (together group) whereas the patients in the other group played one after the other (in-turn group). To assess fine motor skill recovery the patients performed standard clinical tests such as the nine-hole-pegboard test (9HPT) and index finger-tapping speed and regularity, and metronome-paced finger tapping. Patients' mood was established using the Profile of Mood States (POMS). RESULTS: Both groups showed improvements in fine motor control. In metronome-paced finger tapping, patients in both groups improved significantly. Mood tests revealed reductions in depression and fatigue in both groups. During therapy, patients in the in-turn group rated their partner as more sympathetic than the together-group in a visual-analog scale. CONCLUSIONS: Our results suggest that music-supported stroke rehabilitation can improve fine motor control and mood not only individually but also in patient pairs. Patients who were playing in turn rather than simultaneously tended to reveal greater improvement in fine motor skill. We speculate that patients in the former group may benefit from the opportunity to learn from observation.

Basic timing abilities stay intact in patients with musician's dystonia.

Task-specific focal dystonia is a movement disorder that is characterized by the loss of voluntary motor control in extensively trained movements. Musician's dystonia is a type of task-specific dystonia that is elicited in professional musicians during instrumental playing. The disorder has been associated with deficits in timing. In order to test the hypothesis that basic timing abilities are affected by musician's dystonia, we investigated a group of patients (N = 15) and a matched control group (N = 15) on a battery of sensory and sensorimotor synchronization tasks. Results did not show any deficits in auditory-motor processing for patients relative to controls. Both groups benefited from a pacing sequence that adapted to their timing (in a sensorimotor synchronization task at a stable tempo). In a purely perceptual task, both groups were able to detect a misaligned metronome when it was late rather than early relative to a musical beat. Overall, the results suggest that basic timing abilities stay intact in patients with musician's dystonia. This supports the idea that musician's dystonia is a highly task-specific movement disorder in which patients are mostly impaired in tasks closely related to the demands of actually playing their instrument.

The influence of chronotype on making music: circadian fluctuations in pianists' fine motor skills.

Making music on a professional level requires a maximum of sensorimotor precision. Chronotype-dependent fluctuations of sensorimotor precision in the course of the day may prove a challenge for musicians because public performances or recordings are usually scheduled at fixed times of the day. We investigated pianists' sensorimotor timing precision in a scale playing task performed in the morning and in the evening. Participants' chronotype was established through the Munich Chrono-Type Questionnaire, where mid-sleep time served as a marker for the individual chronotypes. Twenty-one piano students were included in the study. Timing precision was decomposed into consistent within-trial variability (irregularity) and residual, between-trial variability (instability). The timing patterns of late chronotype pianists were more stable in the evening than in the morning, whereas early chronotype pianists did not show a difference between the two recording timepoints. In sum, the present results indicate that even highly complex sensorimotor tasks such as music playing are affected by interactions between chronotype and the time of day. Thus, even long-term, massed practice of these expert musicians has not been able to wash out circadian fluctuations in performance.

Response trajectories reveal conflict phase in image-word mismatch.

In the present study, response trajectories were used in a picture­word conflict task to determine the timing of intermediate processing stages that are relatively inaccessible to response time measures. A marker was placed above or below the word ABOVE or BELOW so that its location was congruent or in conflict with the word's meaning. To report either word location(above or below the marker) or word meaning, participants moved a mouse upward toward the appropriate top left or right answer corner on the display screen.Their response trajectories showed a number of distinctive features: First, at about 200 ms after stimulus onset(the "decision moment"), the trajectory abruptly began to arc toward the appropriate answer corner; second,when the word's meaning and position were in conflict,the trajectory showed an interruption that continued until the conflict was resolved. By varying the SOA of the word and marker onsets, we found that the word meaning and word position became available at approximately 325 ms and 251 ms, respectively, after their onsets, and that the delay to resolve conflicts was about 138 ms. The timing of these response trajectory events was more stable than any extracted from the final response times, demonstrating the power of response trajectories to reveal processing stages that are only poorly resolved, if at all, by response time measures [added].