Concept: Motor control
Hand coordination can allow humans to have dexterous control with many degrees of freedom to perform various tasks in daily living. An important contributing factor to this important ability is the complex biomechanical architecture of the human hand. However, drawing a clear functional link between biomechanical architecture and hand coordination is challenging. It is not understood which biomechanical characteristics are responsible for hand coordination and what specific effect each biomechanical characteristic has. To explore this link, we first inspected the characteristics of hand coordination during daily tasks through a statistical analysis of the kinematic data, which were collected from thirty right-handed subjects during a multitude of grasping tasks. Then, the functional link between biomechanical architecture and hand coordination was drawn by establishing the clear corresponding causality between the tendinous connective characteristics of the human hand and the coordinated characteristics during daily grasping activities. The explicit functional link indicates that the biomechanical characteristic of tendinous connective architecture between muscles and articulations is the proper design by the Creator to perform a multitude of daily tasks in a comfortable way. The clear link between the structure and the function of the human hand also suggests that the design of a multifunctional robotic hand should be able to better imitate such basic architecture.
Influential theories of imitation have proposed that humans inherit a neural mechanism - an “active intermodal matching ” (AIM) mechanism or a mirror neuron system - that functions from birth to automatically match sensory input from others' actions to motor programs for performing those same actions, and thus produces imitation. To test these proposals, 160 1- to 2½-year-old toddlers were asked to imitate two simple movements- bending the arm to make an elbow, and moving the bent elbow laterally. Both behaviors were almost certain to be in each child’s repertoire, and the lateral movement was goal-directed (used to hit a plastic cup). Thus, one or both behaviors should have been imitable by toddlers with a functioning AIM or mirror neuron system. Each child saw the two behaviors repeated 18 times, and was encouraged to imitate. Children were also asked to locate their own elbows. Almost no children below age 2 imitated either behavior. Instead, younger children gave clear evidence of a developmental progression, from reproducing only the outcome of the models' movements (hitting the object), through trying (but failing) to reproduce the model’s arm posture and/or the arm-cup relations they had seen, to accurate imitation of arm bending by age 2 and of both movements by age 2½. Across age levels, almost all children who knew the word ‘elbow’ imitated both behaviors: very few who did not know the word imitated either behavior. The evidence is most consistent with a view of early imitation as the product of a complex system of language, cognitive, social, and motor competencies that develop in infancy. The findings do not rule out a role for an inherited neural mechanism, but they suggest that such a system would not by itself be sufficient to explain imitation at any age.
In sports such as golf and darts it is important that one can produce ballistic movements of an object towards a goal location with as little variability as possible. A factor that influences this variability is the extent to which motor planning is updated from movement to movement based on observed errors. Previous work has shown that for reaching movements, our motor system uses the learning rate (the proportion of an error that is corrected for in the planning of the next movement) that is optimal for minimizing the endpoint variability. Here we examined whether the learning rate is hard-wired and therefore automatically optimal, or whether it is optimized through experience. We compared the performance of experienced dart players and beginners in a dart task. A hallmark of the optimal learning rate is that the lag-1 autocorrelation of movement endpoints is zero. We found that the lag-1 autocorrelation of experienced dart players was near zero, implying a near-optimal learning rate, whereas it was negative for beginners, suggesting a larger than optimal learning rate. We conclude that learning rates for trial-by-trial motor learning are optimized through experience. This study also highlights the usefulness of the lag-1 autocorrelation as an index of performance in studying motor-skill learning.
Tendinopathy can be resistant to treatment and often recurs, implying that current treatment approaches are suboptimal. Rehabilitation programmes that have been successful in terms of pain reduction and return to sport outcomes usually include strength training. Muscle activation can induce analgesia, improving self-efficacy associated with reducing one’s own pain. Furthermore, strength training is beneficial for tendon matrix structure, muscle properties and limb biomechanics. However, current tendon rehabilitation may not adequately address the corticospinal control of the muscle, which may result in altered control of muscle recruitment and the consequent tendon load, and this may contribute to recalcitrance or symptom recurrence. Outcomes of interest include the effect of strength training on tendon pain, corticospinal excitability and short interval cortical inhibition. The aims of this concept paper are to: (1) review what is known about changes to the primary motor cortex and motor control in tendinopathy, (2) identify the parameters shown to induce neuroplasticity in strength training and (3) align these principles with tendon rehabilitation loading protocols to introduce a combination approach termed as tendon neuroplastic training. Strength training is a powerful modulator of the central nervous system. In particular, corticospinal inputs are essential for motor unit recruitment and activation; however, specific strength training parameters are important for neuroplasticity. Strength training that is externally paced and akin to a skilled movement task has been shown to not only reduce tendon pain, but modulate excitatory and inhibitory control of the muscle and therefore, potentially tendon load. An improved understanding of the methods that maximise the opportunity for neuroplasticity may be an important progression in how we prescribe exercise-based rehabilitation in tendinopathy for pain modulation and potentially restoration of the corticospinal control of the muscle-tendon complex.
Purpose: The aim of this case study was to examine the individual effects of an adapted physical activity, animal-assisted intervention (APA-AAI) with the family dog on motor skills, physical activity, and quality of life of a child with cerebral palsy (CP). Method: This study used an A-B-A single-subject design. The assessment phase (phase A) occurred pre- and post-intervention. This consisted of standardized assessments of motor skills, quality of life questionnaires, physical activity (measured using the GT3X+ accelerometer) and the human-animal bond. The intervention (phase B) lasted 8 weeks and consisted of adapted physical activities performed with the family dog once a week for 60 min in a lab setting. In addition, the participant had at-home daily activities to complete with the family dog. Results: Visual analysis was used to analyze the data. Motor skill performance, physical activity, quality of life and human animal interaction gains were observed in each case. Conclusions: These preliminary results provided initial evidence that the family-dog can play a role in healthy lifestyles through APA-AAI in children with CP.
To cope with the exceptional computational complexity that is involved in the control of its hyper-redundant arms , the octopus has adopted unique motor control strategies in which the central brain activates rather autonomous motor programs in the elaborated peripheral nervous system of the arms [2, 3]. How octopuses coordinate their eight long and flexible arms in locomotion is still unknown. Here, we present the first detailed kinematic analysis of octopus arm coordination in crawling. The results are surprising in several respects: (1) despite its bilaterally symmetrical body, the octopus can crawl in any direction relative to its body orientation; (2) body and crawling orientation are monotonically and independently controlled; and (3) contrasting known animal locomotion, octopus crawling lacks any apparent rhythmical patterns in limb coordination, suggesting a unique non-rhythmical output of the octopus central controller. We show that this uncommon maneuverability is derived from the radial symmetry of the arms around the body and the simple pushing-by-elongation mechanism by which the arms create the crawling thrust. These two together enable a mechanism whereby the central controller chooses in a moment-to-moment fashion which arms to recruit for pushing the body in an instantaneous direction. Our findings suggest that the soft molluscan body has affected in an embodied way [4, 5] the emergence of the adaptive motor behavior of the octopus.
The dorsal Anterior Cingulate Cortex (dACC) and the Supplementary Motor Area (SMA) are known to interact during motor coordination behavior. We previously discovered that the directional influences underlying this interaction in a visuo-motor coordination task are asymmetric, with the dACC→SMA influence being significantly greater than that in the reverse direction. To assess the specificity of this effect, here we undertook an analysis of the interaction between dACC and SMA in two distinct contexts. In addition to the motor coordination task, we also assessed these effects during a (n-back) working memory task. We applied directed functional connectivity analysis to these two task paradigms, and also to the rest condition of each paradigm, in which rest blocks were interspersed with task blocks. We report here that the previously known asymmetric interaction between dACC and SMA, with dACC→SMA dominating, was significantly larger in the motor coordination task than the memory task. Moreover the asymmetry between dACC and SMA was reversed during the rest condition of the motor coordination task, but not of the working memory task. In sum, the dACC→SMA influence was significantly greater in the motor task than the memory task condition, and the SMA→dACC influence was significantly greater in the motor rest than the memory rest condition. We interpret these results as suggesting that the potentiation of motor sub-networks during the motor rest condition supports the motor control of SMA by dACC during the active motor task condition.
To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brain-machine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects' internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. We then used the internal models to characterize how the neural population activity changes during BMI learning. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output.
Recent investigations into the neural basis of elite sporting performance have focused on whether cortical activity might characterize individual differences in ability. However, very little is understood about how changes in brain structure might contribute to individual differences in expert motor control. We compared the behavior and brain structure of healthy controls with a group of karate black belts, an expert group who are able to perform rapid, complex movements that require years of training. Using 3D motion tracking, we investigated whether the ability to control ballistic arm movements was associated with differences in white matter microstructure. We found that karate experts are better able than novices to coordinate the timing of inter-segmental joint velocities. Diffusion tensor imaging revealed significant differences between the groups in the microstructure of white matter in the superior cerebellar peduncles (SCPs) and primary motor cortex-brain regions that are critical to the voluntary control of movement. Motor coordination, the amount of experience, and the age at which training began were all associated with individual differences in white matter integrity in the cerebellum within the karate groups. These findings suggest a role for the white matter pathways of the SCPs in motor expertise.
Exercise interventions in individuals with Parkinson’s disease incorporate goal-based motor skill training to engage cognitive circuitry important in motor learning. With this exercise approach, physical therapy helps with learning through instruction and feedback (reinforcement) and encouragement to perform beyond self-perceived capability. Individuals with Parkinson’s disease become more cognitively engaged with the practice and learning of movements and skills that were previously automatic and unconscious. Aerobic exercise, regarded as important for improvement of blood flow and facilitation of neuroplasticity in elderly people, might also have a role in improvement of behavioural function in individuals with Parkinson’s disease. Exercises that incorporate goal-based training and aerobic activity have the potential to improve both cognitive and automatic components of motor control in individuals with mild to moderate disease through experience-dependent neuroplasticity. Basic research in animal models of Parkinson’s disease is beginning to show exercise-induced neuroplastic effects at the level of synaptic connections and circuits.