Contributions of exercise-induced fatigue versus intertrial tendon vibration on visual-proprioceptive weighting for goal-directed movement

Mountain Hiking: Prolonged Eccentric Muscle Contraction during Simulated Downhill Walking Perturbs Sensorimotor Control Loops Needed for Safe Dynamic Foot-Ground Interactions

Safe mountain hiking requires precise control of dynamic foot-ground interactions. In addition to vision and vestibular afferents, limb proprioception, sensorimotor control loops, and reflex responses are used to adapt to the specific nature of the ground contact. Diminished leg dexterity and balance during downhill walking is usually attributed to fatigue. We investigated the supplementary hypothesis that the eccentric contractions inherent to downhill walking can also disrupt muscle proprioception, as well as the sensorimotor control loops and reflex responses that depend on it. In this study, we measured leg dexterity (LD), anterior-posterior (AP) and medio-lateral (ML) bipedal balance, and maximal voluntary leg extension strength in young and healthy participants before and after 30 min of simulated downhill walking at a natural pace on a treadmill at a 20° decline. Post-pre comparisons of LD (p < 0.001) and AP balance (p = 0.001) revealed significant reductions in dynamic foot-ground interactions after eccentric exercise without an accompanying reduction in leg extension strength. We conclude that eccentric contractions during downhill walking can disrupt the control of dynamic foot-ground interactions independently of fatigue. We speculate that mountaineering safety could be improved by increasing conscious attention to compensate for unadjusted proprioception weighting, especially in the descent.

Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks

Humans learn movements naturally, but it takes a lot of time and training to achieve expert performance in motor skills. In this review, we show how modern technologies can support people in learning new motor skills. First, we introduce important concepts in motor control, motor learning and motor skill learning. We also give an overview about the rapid expansion of machine learning algorithms and sensor technologies for human motion analysis. The integration between motor learning principles, machine learning algorithms and recent sensor technologies has the potential to develop AI-guided assistance systems for motor skill training. We give our perspective on this integration of different fields to transition from motor learning research in laboratory settings to real world environments and real world motor tasks and propose a stepwise approach to facilitate this transition.

The effects of eccentric exercise-induced fatigue on position sense during goal-directed movement

We investigated the impairment of position sense associated with muscle fatigue. In Exp. 1, participants performed learned eccentric extension (22 °/s) movements of the elbow as the arm was pulled through the horizontal plane without vision of the arm. They opened their closed right hand when they judged it to be passing through a target. Dynamic position sense was assessed via accuracy of limb position to the target at time of hand opening. Eccentric movements were performed against a flexion load (10% of flexion MVC). We investigated performance under conditions with and without biceps vibration, as well as before and after eccentric exercise. In Exp. 2, a motor was used to extend the participant's limb passively. We compared conditions with and without vibration of the lengthening but passive biceps, before and after exercise. In Exp. 1, vibration of the active biceps resulted in participants opening their hand earlier ( [95% CI] -5.52° [-7.40, -3.63]) compared to without vibration. Exercise reduced flexion MVCs by ~44%, and participants undershot the target more (-5.51° [-9.31, -1.70]) in the post-exercise block during control trials. Exercise did not influence the persistence of the vibratory illusion. In Exp. 2, vibration resulted in greater undershooting (-2.99° [-3.99, -1.98]) compared to without vibration, before and after exercise. Although exercise reduced MVCs by ~50%, the passive task showed no effects of exercise. We suggest that the CNS continues to rely on muscle spindles for limb position sense, even when they reside in a muscle exposed to fatiguing eccentric contractions.

Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment

Multiple learning processes contribute to successful goal-directed actions in the face of changing physiological states, biomechanical constraints, and environmental contexts. Amongst these processes, implicit sensorimotor adaptation is of primary importance, ensuring that movements remain well-calibrated and accurate. A large body of work on reaching movements has emphasized how adaptation centers on an iterative process designed to minimize visual errors. The role of proprioception has been largely neglected, thought to play a passive role in which proprioception is affected by the visual error but does not directly contribute to adaptation. Here, we present an alternative to this visuo-centric framework, outlining a model in which implicit adaptation acts to minimize a proprioceptive error, the distance between the perceived hand position and its intended goal. This proprioceptive re-alignment model (PReMo) is consistent with many phenomena that have previously been interpreted in terms of learning from visual errors, and offers a parsimonious account of numerous unexplained phenomena. Cognizant that the evidence for PReMo rests on correlational studies, we highlight core predictions to be tested in future experiments, as well as note potential challenges for a proprioceptive-based perspective on implicit adaptation.

Detecting Endpoint Error of an Ongoing Reaching Movement: the Role of Vision, Proprioception, and Efference

Brief windows of vision presented during reaching movements contribute to endpoint error estimates. It is not clear whether such error detection processes depend on other sources of information (e.g., proprioception and efference). In the current study, participants were presented with a brief window of vision and then judged whether their movement endpoint under- or over-shot the target after: 1) performing an active reach; 2) being passively guided by a robotic arm; and 3) observing a fake hand moved by the robot arm. Participants were most accurate at estimating their endpoint error in the active movement conditions and least accurate in the action observation condition. Thus, both efferent and proprioceptive information significantly contribute to endpoint error detection processes even with brief visual feedback.

Measurement and Correction of Stooped Posture during Gait Using Wearable Sensors in Patients with Parkinsonism: A Preliminary Study

Stooped posture, which is usually aggravated during walking, is one of the typical postural deformities in patients with parkinsonism. However, the degree of stooped posture is difficult to quantitatively measure during walking. Furthermore, continuous feedback on posture is also difficult to provide. The purpose of this study is to measure the degree of stooped posture during gait and to investigate whether vibration feedback from sensor modules can improve a patient's posture. Parkinsonian patients with stooped posture were recruited for this study. Two wearable sensors with three-axis accelerometers were attached, one at the upper neck and the other just below the C7 spinous process of the patients. After being calibrated in the most upright posture, the sensors continuously recorded the sagittal angles at 20 Hz and averaged the data at every second during a 6 min walk test. In the control session, the patients walked with the sensors as usual. In the vibration session, sensory feedback was provided through vibrations from the neck sensor module when the sagittal angle exceeded a programmable threshold value. Data were collected and analyzed successfully in a total of 10 patients. The neck flexion and back flexion were slightly aggravated during gait, although the average change was <10° in most patients in both measurement sessions. Therefore, it was difficult to evaluate the effect of sensory feedback through vibration. However, some patients showed immediate response to the feedback and corrected their posture during gait. In conclusion, this preliminary study suggests that stooped posture could be quantitatively measured during gait by using wearable sensors in patients with parkinsonism. Sensory feedback through vibration from sensor modules may help in correcting posture during gait in selected patients.

Individual differences in proprioception predict the extent of implicit sensorimotor adaptation

Recent studies have revealed an upper bound in motor adaptation, beyond which other learning systems may be recruited. The factors determining this upper bound are poorly understood. The multisensory integration hypothesis states that this limit arises from opposing responses to visual and proprioceptive feedback. As individuals adapt to a visual perturbation, they experience an increasing proprioceptive error in the opposite direction, and the upper bound is the point where these two error signals reach an equilibrium. Assuming that visual and proprioceptive feedback are weighted according to their variability, there should be a correlation between proprioceptive variability and the limits of adaptation. Alternatively, the proprioceptive realignment hypothesis states that the upper bound arises when the (visually biased) sensed hand position realigns with the expected sensed position (target). When a visuo-proprioceptive discrepancy is introduced, the sensed hand position is biased toward the visual cursor, and the adaptive system counteracts this discrepancy by driving the hand away from the target. This hypothesis predicts a correlation between the size of the proprioceptive shift and the upper bound of adaptation. We tested these two hypotheses by considering natural variation in proprioception and motor adaptation across individuals. We observed a modest, yet reliable correlation between the upper bound of adaptation with both proprioceptive measures (variability and shift). Although the results do not clearly favor one hypothesis over the other, they underscore the critical role of proprioception in sensorimotor adaptation.NEW & NOTEWORTHY Although the sensorimotor system uses sensory feedback to remain calibrated, this learning process is constrained, limited by the maximum degree of plasticity. The factors determining this limit remain elusive. Guided by two hypotheses, we show that individual differences in the upper bound of adaptation in response to a visual perturbation can be predicted by the bias and variability in proprioception. These results underscore the critical, but often neglected role of proprioception in human motor learning.