Voluntary muscle coactivation in quiet standing elicits reciprocal rather than coactive agonist-antagonist control of reactive balance.

Muscle coactivation increases in challenging balance conditions as well as with advanced age and mobility impairments. Increased muscle coactivation can occur both in anticipation of (feedforward) and in reaction to (feedback) perturbations, however, the causal relationship between feedforward and feedback muscle coactivation remains elusive. Here, we hypothesized that feedforward muscle coactivation would increase both the body's initial mechanical resistance due to muscle intrinsic properties and the later feedback-mediated muscle coactivation in response to postural perturbations. Young adults voluntarily increased leg muscle coactivation using visual biofeedback before support-surface perturbations. In contrast to our hypothesis, feedforward muscle coactivation did not increase the body's initial intrinsic resistance to perturbations, nor did it increase feedback muscle coactivation. Rather, perturbations with feedforward muscle coactivation elicited a medium- to long-latency increase of feedback-mediated agonist activity but a decrease of feedback-mediated antagonist activity. This reciprocal rather than coactivation effect on ankle agonist and antagonist muscles enabled faster reactive ankle torque generation, reduced ankle dorsiflexion, and reduced center of mass (CoM) motion. We conclude that in young adults, voluntary feedforward muscle coactivation can be independently modulated with respect to feedback-mediated muscle coactivation. Furthermore, our findings suggest feedforward muscle coactivation may be useful for enabling quicker joint torque generation through reciprocal, rather than coactivated, agonist-antagonist feedback muscle activity. As such our results suggest that behavioral context is critical to whether muscle coactivation functions to increase agility versus stability.NEW & NOTEWORTHY Feedforward and feedback muscle coactivation are commonly observed in older and mobility impaired adults and are considered strategies to improve stability by increasing body stiffness prior to and in response to perturbations. In young adults, voluntary feedforward coactivation does not necessarily increase feedback coactivation in response to perturbations. Instead, feedforward coactivation enabled faster ankle torques through reciprocal agonist-antagonist muscle activity. As such, coactivation may promote either agility or stability depending on the behavioral context.

"Tell me what is 'better'!" How medical students experience feedback, through the lens of self-regulatory learning.

INTRODUCTION: While feedback aims to support learning, students frequently struggle to use it. In studying feedback responses there is a gap in explaining them in relation to learning theory. This study explores how feedback experiences influence medical students' self-regulation of learning. METHODS: Final-year medical students across three campuses (Ireland, Bahrain and Malaysia) were invited to share experiences of feedback in individual semi-structured interviews. The data were thematically analysed and explored through the lens of self-regulatory learning theory (SRL). RESULTS: Feedback interacts with learners' knowledge and beliefs about themselves and about learning. They use feedback to change both their cognitive and behavioural learning strategies, but how they choose which feedback to implement is complex. They struggle to generate learning strategies and expect teachers to make sense of the "how" in addition to the "what"" in planning future learning. Even when not actioned, learners spend time with feedback and it influences future learning. CONCLUSION: By exploring our findings through the lens of self-regulation learning, we advance conceptual understanding of feedback responses. Learners' ability to generate "next steps" may be overestimated. When feedback causes negative emotions, energy is diverted from learning to processing distress. Perceived non-implementation of feedback should not be confused with ignoring it; feedback that is not actioned often impacts learning.

Self-regulatory learning theory as a lens on how undergraduate and postgraduate learners respond to feedback: A BEME scoping review: BEME Guide No. 66.

INTRODUCTION: Little is known of processes by which feedback affects learners to influence achievement. This review maps what is known of how learners interact with feedback, to better understand how feedback affects learning strategies, and to explore enhancing and inhibiting factors. METHODS: Pilot searching indicated a wide range of interpretations of feedback and study designs, prompting the use of scoping methodology. Inclusion criteria comprised: (i) learners (undergraduate, postgraduate, continuing education) who regularly receive feedback, and (ii) studies that associated feedback with subsequent learner reaction. The screening was performed independently in duplicate. Data extraction and synthesis occurred via an iterative consensus approach. Self-regulatory learning theory (SRL) was used as the conceptual framework. RESULTS: Of 4253 abstracts reviewed, 232 were included in the final synthesis. Understandings of feedback are diverse; a minority adopt recognised definitions. Distinct learner responses to feedback can be categorized as cognitive, behavioural, affective, and contextual with complex, overlapping interactions. Importantly emotional responses are commonplace; factors mediating them are pivotal in learner recipience. CONCLUSION: Feedback benefits learners most when focussed on learner needs, via engagement in bi-directional dialogue. Learner emotions must be supported, with the construction of positive learner-teacher relationships. A developmental agenda is key to learner's acceptance of feedback and enhancing future learning.

Time course of changes in the long-latency feedback response parallels the fast process of short-term motor adaptation.

Adapting to novel dynamics involves modifying both feedforward and feedback control. We investigated whether the motor system alters feedback responses during adaptation to a novel force field in a manner similar to adjustments in feedforward control. We simultaneously tracked the time course of both feedforward and feedback systems via independent probes during a force field adaptation task. Participants (n = 35) grasped the handle of a robotic manipulandum and performed reaches to a visual target while the hand and arm were occluded. We introduced an abrupt counterclockwise velocity-dependent force field during a block of reaching trials. We measured movement kinematics and shoulder and elbow muscle activity with surface EMG electrodes. We tracked the feedback stretch response throughout the task. Using force channel trials, we measured overall learning, which was later decomposed into a fast and slow process. We found that the long-latency feedback response (LLFR) was upregulated in the early stages of learning and was correlated with the fast component of feedforward adaptation. The change in feedback response was specific to the long-latency epoch (50-100 ms after muscle stretch) and was observed only in the triceps muscle, which was the muscle required to counter the force field during adaptation. The similarity in time course for the LLFR and the estimated time course of the fast process suggests both are supported by common neural circuits. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.NEW & NOTEWORTHY We investigated whether changes in the feedback stretch response were related to the proposed fast and slow processes of motor adaptation. We found that the long-latency component of the feedback stretch response was upregulated in the early stages of learning and the time course was correlated with the fast process. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.

1α,25(OH)2 D3 alleviates high glucose-induced lipid accumulation in rat renal tubular epithelial cells by inhibiting SREBPs.

Lipid accumulation is a vital event in the progression of diabetic nephropathy. 1,25-Dihydroxyvitamin D3 (1α,25(OH)2 D3 ) is considered to have a protective effect on diabetic nephropathy. However, it remains unclear whether 1α,25(OH)2 D3 can inhibit lipid accumulation, and the potential mechanisms responsible for lipid metabolism are incompletely understood. In this study, we evaluated the effects of 1α,25(OH)2 D3 on lipid metabolism in high glucose-exposed rat renal tubular epithelial NRK-52E cells. Results indicated that high glucose-enhanced lipid accumulation in NRK-52E cells and 1α,25(OH)2 D3 can remarkably decrease high glucose-induced lipid accumulation. Western blot showed that 1α,25(OH)2 D3 alleviated high glucose-induced upregulation of sterol regulatory element-binding protein-1c (SREBP-1c) and SREBP2, along with their established target genes fatty acid synthase (FASN) and hydroxymethylglutaryl CoA reductases (HMGCR). Overall, these findings suggest that 1α,25(OH)2 D3 downregulated the expressions of SREBPs to inhibit high glucose-induced lipid accumulation, which provides new sights into the protective effects of 1α,25(OH)2 D3 on diabetic nephropathy.

The Neural Feedback Response to Error As a Teaching Signal for the Motor Learning System.

UNLABELLED: When we experience an error during a movement, we update our motor commands to partially correct for this error on the next trial. How does experience of error produce the improvement in the subsequent motor commands? During the course of an erroneous reaching movement, proprioceptive and visual sensory pathways not only sense the error, but also engage feedback mechanisms, resulting in corrective motor responses that continue until the hand arrives at its goal. One possibility is that this feedback response is co-opted by the learning system and used as a template to improve performance on the next attempt. Here we used electromyography (EMG) to compare neural correlates of learning and feedback to test the hypothesis that the feedback response to error acts as a template for learning. We designed a task in which mixtures of error-clamp and force-field perturbation trials were used to deconstruct EMG time courses into error-feedback and learning components. We observed that the error-feedback response was composed of excitation of some muscles, and inhibition of others, producing a complex activation/deactivation pattern during the reach. Despite this complexity, across muscles the learning response was consistently a scaled version of the error-feedback response, but shifted 125 ms earlier in time. Across people, individuals who produced a greater feedback response to error, also learned more from error. This suggests that the feedback response to error serves as a teaching signal for the brain. Individuals who learn faster have a better teacher in their feedback control system. SIGNIFICANCE STATEMENT: Our sensory organs transduce errors in behavior. To improve performance, we must generate better motor commands. How does the nervous system transform an error in sensory coordinates into better motor commands in muscle coordinates? Here we show that when an error occurs during a movement, the reflexes transform the sensory representation of error into motor commands. To learn from error, the nervous system scales this feedback response and then shifts it earlier in time, adding it to the previously generated motor commands. This addition serves as an update to the motor commands, constituting the learning signal. Therefore, by providing a coordinate transformation, the feedback system generates a template for learning from error.

Nanoconfined Electrochemical Sensing of Single Silver Nanoparticles with a Wireless Nanopore Electrode.

Single entity electrochemistry (SEE) has emerged as a promising method for precise measurement and fundamental understanding of the heterogeneity of single entities. Herein, we propose the dual responsive SEE sensing of the silver nanoparticles (AgNPs) collisions through a wireless nanopore electrode (WNE). Given the high temporal resolution and low background noise features, the Faradaic and capacitive currents provide the AgNPs' collision response. The electron transfer between the AgNPs and the electrode surface is identified under a bipolar electrochemical mechanism. Compared to the ultramicroelectrode, multistep oxidation of 30 nm AgNPs is observed due to the decreased interaction of the nanoparticles to the electrode. Moreover, the nanoconfinement of WNE plays a vital role in the repeated capturing of nanoparticles from the nontunneling region into the tunneling region until a complete oxidation. As a comparison, the collision of 5 nm AgNPs with higher interaction at the electrode surface shows great decrease in the multistep events. Thus, we propose a nanoconfined interaction based SEE method which could be used for simultaneously capturing the Faradaic and capacitive response. The nanoconfined interaction based SEE method holds great promise in the better understanding of heterogeneity of single particles.

Time-to-Target Simplifies Optimal Control of Visuomotor Feedback Responses.

Visuomotor feedback responses vary in intensity throughout a reach, commonly explained by optimal control. Here, we show that the optimal control for a range of movements with the same goal can be simplified to a time-to-target dependent control scheme. We measure our human participants' visuomotor responses in five reaching conditions, each with different hand or cursor kinematics. Participants only produced different feedback responses when these kinematic changes resulted in different times-to-target. We complement our experimental data with a range of finite and non-finite horizon optimal feedback control (OFC) models, finding that the model with time-to-target as one of the input parameters best replicates the experimental data. Overall, this suggests that time-to-target is a critical control parameter in online feedback control. Moreover, we propose that for a specific task and known dynamics, humans can instantly produce a control signal without any additional online computation allowing rapid response onset and close to optimal control.