Synergies are thought to be the building blocks of vertebrate movements. The inability to execute synergies in properly timed and graded fashion precludes adequate functional motor performance. In humans with stroke, abnormal synergies are a sign of persistent neurological deficit and result in loss of independent joint control, which disrupts the kinematics of voluntary movements. This study aimed at characterizing training-related changes in synergies apparent from movement kinematics and, specifically, at assessing: 1) the extent to which they characterize recovery and 2) whether they follow a pattern of augmentation of existing abnormal synergies or, conversely, are characterized by a process of extinction of the abnormal synergies. We used a robotic therapy device to train and analyze paretic arm movements of 117 persons with chronic stroke. In a task for which they received no training, subjects were better able to draw circles by discharge. Comparison with performance at admission on kinematic robot-derived metrics showed that subjects were able to execute shoulder and elbow joint movements with significantly greater independence or, using the clinical description, with more isolated control. We argue that the changes we observed in the proposed metrics reflect changes in synergies. We show that they capture a significant portion of the recovery process, as measured by the clinical Fugl-Meyer scale. A process of “tuning” or augmentation of existing abnormal synergies, not extinction of the abnormal synergies, appears to underlie recovery.

Both the American Heart Association and the VA/DoD endorse upper-extremity robot-mediated rehabilitation therapy for stroke care. However, we do not know yet how to optimize therapy for a particular patient's needs. Here, we explore whether we must train patients for each functional task that they must perform during their activities of daily living or alternatively capacitate patients to perform a class of tasks and have therapists assist them later in translating the observed gains into activities of daily living. The former implies that motor adaptation is a better model for motor recovery. The latter implies that motor learning (which allows for generalization) is a better model for motor recovery. We quantified trained and untrained movements performed by 158 recovering stroke patients via 13 metrics, including movement smoothness and submovements. Improvements were observed both in trained and untrained movements suggesting that generalization occurred. Our findings suggest that, as motor recovery progresses, an internal representation of the task is rebuilt by the brain in a process that better resembles motor learning than motor adaptation. Our findings highlight possible improvements for therapeutic algorithms design, suggesting sparse-activity-set training should suffice over exhaustive sets of task specific training.

Professional musicians (PMs) are at high risk of developing hearing loss (HL) and other audiological symptoms such as tinnitus, hyperacusis, and diplacusis. The aim of this systematic review is to (A) assess the risk of developing HL and audiological symptoms in PMs and (B) evaluate if different music genres (Pop/Rock Music—PR; Classical Music—CL) expose PMs to different levels of risk of developing such conditions. Forty-one articles including 4618 PMs were included in the study. HL was found in 38.6% PMs; prevalence was significantly higher among PR (63.5%) than CL (32.8%) PMs; HL mainly affected the high frequencies in the 3000-6000 Hz range and was symmetric in 68% PR PMs and in 44.5% CL PMs. Tinnitus was the most common audiological symptom, followed by hyperacusis and diplacusis. Tinnitus was almost equally distributed between PR and CL PMs; diplacusis was more common in CL than in PR PMs, while prevalence of hyperacusis was higher among PR PMs. Our review showed that PR musicians have a higher risk of developing HL compared to CL PMs; exposure to sounds of high frequency and intensity and absence of ear protection may justify these results. Difference in HL symmetry could be explained by the type of instruments used and consequent single-sided exposure.

The ability to control online motor corrections is key to dealing with unexpected changes arising in the environment with which we interact. How the CNS controls online motor corrections is poorly understood, but evidence has accumulated in favor of a submovement-based model in which apparently continuous movement is segmented into distinct submovements. Although most studies have focused on submovements' kinematic features, direct links with the underlying neural dynamics have not been extensively explored. This study sought to identify an electroencephalographic signature of submovements. We elicited kinematic submovements using a double-step displacement paradigm. Participants moved their wrist toward a target whose direction could shift mid-movement with a 50% probability. Movement kinematics and cortical activity were concurrently recorded with a low-friction robotic device and high-density electroencephalography. Analysis of spatiotemporal dynamics of brain activation and its correlation with movement kinematics showed that the production of each kinematic submovement was accompanied by (1) stereotyped topographic scalp maps and (2) frontoparietal ERPs time-locked to submovements. Positive ERP peaks from frontocentral areas contralateral to the moving wrist preceded kinematic submovement peaks by 220–250 msec and were followed by positive ERP peaks from contralateral parietal areas (140–250 msec latency, 0–80 msec before submovement peaks). Moreover, individual subject variability in the latency of frontoparietal ERP components following the target shift significantly predicted variability in the latency of the corrective submovement. Our results are in concordance with evidence for the intermittent nature of continuous movement and elucidate the timing and role of frontoparietal activations in the generation and control of corrective submovements.

A peripheral nerve stimulus can enhance or suppress the evoked response to transcranial magnetic stimulation (TMS) depending on the latency of the preceding peripheral nerve stimulation (PNS) pulse. Similarly, somatosensory afference from the passively moving limb can transiently alter corticomotor excitability, in a phase-dependent manner. The repeated association of PNS with TMS is known to modulate corticomotor excitability; however, it is unknown whether repeated passive-movement associative stimulation (MAS) has similar effects.