Rhythm and Music-Based Interventions in Motor Rehabilitation: Current Evidence and Future Perspectives

Research in basic and clinical neuroscience of music conducted over the past decades has begun to uncover music’s high potential as a tool for rehabilitation. Advances in our understanding of how music engages parallel brain networks underpinning sensory and motor processes, arousal, reward, and affective regulation, have laid a sound neuroscientific foundation for the development of theory-driven music interventions that have been systematically tested in clinical settings. Of particular significance in the context of motor rehabilitation is the notion that musical rhythms can entrain movement patterns in patients with movement-related disorders, serving as a continuous time reference that can help regulate movement timing and pace. To date, a significant number of clinical and experimental studies have tested the application of rhythm- and music-based interventions to improve motor functions following central nervous injury and/or degeneration. The goal of this review is to appraise the current state of knowledge on the effectiveness of music and rhythm to modulate movement spatiotemporal patterns and restore motor function. By organizing and providing a critical appraisal of a large body of research, we hope to provide a revised framework for future research on the effectiveness of rhythm- and music-based interventions to restore and (re)train motor function.

Synaptic Encoding of Vestibular Sensation Regulates Movement Timing and Coordination

Vertebrate vestibular circuits use sensory signals derived from the inner ear to guide both corrective and volitional movements. A major challenge in the neuroscience of balance is to link the synaptic and cellular substrates that encode body tilts to specific behaviors that stabilize posture and enable efficient locomotion. Here we address this problem by measuring the development, synaptic architecture, and behavioral contributions of vestibulospinal neurons in the larval zebrafish. First, we find that vestibulospinal neurons are born and are functionally mature before larvae swim freely, allowing them to act as a substrate for postural regulation. Next, we map the synaptic inputs to vestibulospinal neurons that allow them to encode posture. Further, we find that this synaptic architecture allows them to respond to linear acceleration in a directionally-tuned and utricle-dependent manner; they are thus poised to guide corrective movements. After loss of vestibulospinal neurons, larvae adopted eccentric postures with disrupted movement timing and weaker corrective kinematics. We used a generative model of swimming to demonstrate that together these disruptions can account for the increased postural variability. Finally, we observed that lesions disrupt vestibular-dependent coordination between the fins and trunk during vertical swimming, linking vestibulospinal neurons to navigation. We conclude that vestibulospinal neurons turn synaptic representations of body tilt into defined corrective behaviors and coordinated movements. As the need for stable locomotion is common and the vestibulospinal circuit is highly conserved our findings reveal general mechanisms for neuronal control of balance.

Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision

Human movements with or without vision exhibit timing (i.e. speed and duration) and variability characteristics which are not well captured by existing computational models. Here, we introduce a stochastic optimal feedforward-feedback control (SFFC) model that can predict the nominal timing and trial-by-trial variability of self-paced arm reaching movements carried out with or without online visual feedback of the hand. In SFFC, movement timing results from the minimization of the intrinsic factors of effort and variance due to constant and signal-dependent motor noise, and movement variability depends on the integration of visual feedback. Reaching arm movements data are used to examine the effect of online vision on movement timing and variability, and test the model. This modelling suggests that the central nervous system predicts the effects of sensorimotor noise to generate an optimal feedforward motor command, and triggers optimal feedback corrections to task-related errors based on the available limb state estimate.

Dense movement with embedded sparse action-type representations in the output layer of motor cortex

Motor cortex generates output necessary for the execution of a wide range of motor behaviours. Although neural representations of movement have been described throughout motor cortex, how population activity in output layers relates to the execution of distinct motor actions is less well explored. To address this, we imaged layer 5B population activity in mice performing a two-action forelimb task. We found most neurons convey a generalised movement signal, with action-type-specific signalling restricted to relatively small, spatially intermingled subpopulations of neurons. Deep layer population dynamics largely reflect dense, action-invariant signals that correlate with movement timing, while embedded sparse action-type representations reflect distinct forelimb actions. We suggest that sparse coding of action-type enhances the number of possible output configurations necessary for behavioural flexibility and the execution of a wide repertoire of behavioural actions.

Dynamic dopaminergic activity controls the timing of self-timed movement

SUMMARYDeciding when to initiate action is essential to survival. Insights from movement disorders and pharmacological studies implicate the neurotransmitter dopamine as a regulator of movement timing, but the underlying neural mechanisms are not understood. Here we show dynamic dopaminergic signaling over seconds-long timescales controls movement timing in mice. Animals were trained to initiate licking after a self-timed interval following a start-timing cue. Surprisingly, dopaminergic signals ramped-up slowly between the start-timing cue and the self-timed movement, with the slope predicting the movement time on single trials. Steeply rising signals preceded early lick-initiation, whereas slowly rising signals preceded later initiation, reminiscent of a ramp-to-threshold process. Higher baseline activity also predicted earlier self-timed movements. Optogenetic activation of dopamine neurons during self-timing caused systematic early-shifting of movement initiation, whereas inhibition caused late-shifting. These results reveal a causal role for dynamic dopaminergic signaling unfolding over seconds in controlling the moment-by-moment decision of when to move.

Coordination: Support for an alternative approach II

Two key features of the current AP/TD coupled-oscillator approach to movement coordination are that 1) coordination among gestures is treated as relative timing control, accomplished via planning-oscillator phase relationships, rather than coordination based on spatial information or absolute timing, and 2) coordination is based on the (relative) timing of movement onsets, rather than the timing of target achievement. Evidence bearing on both of these issues suggests that 1) patterns of relative timing do not necessarily require implementation via oscillator phase relationships, and 2) coordination is often based on the part of movement most closely related to the goal (often the endpoint), rather than on movement onsets (as proposed in recent versions of AP/TD). This chapter includes a discussion of alternative, i.e. non-oscillator-based, mechanisms that can model both the coordination of movements for synchronous target achievement, and the planning of movement timing when targets are sequential.