Decision making is often necessary before performing an action. Traditionally, it has been assumed that decision making and motor control are independent, sequential processes. Ogasa et al. challenge this view, and demonstrate that the decision-making process significantly impacts on the formation and retrieval of motor memory by tagging it with the level of confidence.

In this study, we introduce a novel maze task designed to investigate naturalistic motor learning in bimanual coordination. We developed and validated an extended set of movement primitives tailored to capture the full spectrum of scenarios encountered in a maze game. Over a 3-day training period, we evaluated participants\' performance using these primitives and a custom-developed software, enabling precise quantification of performance. Our methodology integrated the primitives with in-depth kinematic analyses and thorough thumb pressure assessments, charting the trajectory of participants\' progression from novice to proficient stages. Results demonstrated consistent improvement in maze performance and significant adaptive changes in joint behaviors and strategic recalibrations in thumb pressure distribution. These findings highlight the central nervous system\'s adaptability in orchestrating sophisticated motor strategies and the crucial role of tactile feedback in precision tasks. The maze platform and setup emerge as a valuable foundation for future experiments, providing a tool for the exploration of motor learning and coordination dynamics. This research underscores the complexity of bimanual motor learning in naturalistic environments, enhancing our understanding of skill acquisition and task efficiency while emphasizing the necessity for further exploration and deeper investigation into these adaptive mechanisms.

UNASSIGNED: The acquisition of motor skills is a key element in many sports. A motor learning principle, which is frequently used to support skill acquisition is the application of different attentional foci. The effectiveness of different attentional foci on performance and the learning of motor skills has been investigated in various sports using randomised controlled trials. The aim of the present study was to investigate the effectiveness of different attentional foci (such as external (EFA) and internal attentional foci (IFA), but also holistic and switching foci) on the performance and learning of a sport-specific motor task in healthy individuals.
UNASSIGNED: This study was a systematic review with network meta-analysis. We followed the Prisma reporting guideline and the Cochrane handbook for systematic reviews. Cinahl, Embase, Medline and Cochrane Central were searched for eligible studies. Network meta-analyses were performed for the post-acquisition, retention and transfer test endpoints.
UNASSIGNED: Twelve studies were included in the review. At post-acquisition an EFA was the most effective intervention compared to the control intervention (SMD: 0.9855; 95% CI [0.4-1.57]; p: 0.001). At the retention and transfer test endpoints, a holistic focus of attention had the highest effectiveness compared to an IFA (SMD 0.75; 95% CI [-0.1 to 1.6]; p: 0.09) and (SMD 1.16; 95% CI [0.47-1.86]; p: 0.001).
UNASSIGNED: For all three endpoints, we analysed a greater effectiveness of an EFA and holistic focus compared to an IFA. Several promising different attentional focus interventions were identified. The largest effects were analysed for a holistic focus. However, only one study used this intervention and therefore there remains uncertainty about the effectiveness. With regard to the inconsistency observed, the analysis at post-acquisition should be interpreted with caution. Modified versions of the EFA were the imagined and the dynamic EFA. Both were only explored in single studies and should therefore be investigated in further follow-up studies that directly compare them.

Dual-task performance holds significant relevance in real-world scenarios. Implicit learning is a possible approach for improving dual-task performance. Analogy learning, utilizing a single metaphor to convey essential information about motor skills, has emerged as a practical method for fostering implicit learning. However, evidence supporting the effect of implicit learning on gait-cognitive dual-task performance is insufficient. This exploratory study aimed to examine the effects of implicit and explicit learning on dual-task performance in both gait and cognitive tasks. Tandem gait was employed on a treadmill to assess motor function, whereas serial seven subtraction tasks were used to gauge cognitive performance. Thirty healthy community-dwelling older individuals were randomly assigned to implicit or explicit learning groups. Each group learned the tandem gait task according to their individual learning styles. The implicit learning group showed a significant improvement in gait performance under the dual-task condition compared with the explicit learning group. Furthermore, the implicit learning group exhibited improved dual-task interference for both tasks. Our findings suggest that implicit learning may offer greater advantages than explicit learning in acquiring autonomous motor skills. Future research is needed to uncover the mechanisms underlying implicit learning and to harness its potential for gait-cognitive dual-task performance in clinical settings.

Previous research suggests that the neural processes underlying specification of movement direction and amplitude are independently represented in the nervous system. However, our understanding of acquisition and consolidation processes in the direction and distance learning remains limited. We designed a virtual air hockey task, in which the puck direction is determined by the hand direction at impact, while the puck distance is determined by the amplitude of the velocity. In two versions of this task, participants were required to either specify the direction or the distance of the puck, while the alternate variable did not contribute to task success. Separate groups of right-handed participants were recruited for each task. Each participant was randomly assigned to one of two groups with a counter-balanced arm practice sequence (right to left, or left to right). We examined acquisition and, after 24 h, we examined two aspects of consolidation: 1) same hand performance to test the durability and 2) the opposite hand to test the effector-independent consolidation (interlimb transfer) of learning. The distance task showed symmetry between hands in the extent of acquisition as well as in both aspects of consolidation. In contrast, the direction task showed asymmetry in both acquisition and consolidation: the dominant right arm showed faster and greater acquisition and greater transfer from the opposite arm training. The asymmetric acquisition and consolidation processes shown in the direction task might be explained by lateralized control and mapping of direction, an interpretation consistent with previous findings on motor adaptation paradigms.

OBJECTIVE: To evaluate the delivery of rehabilitation using implicit motor learning principles in an acute stroke setting.
METHODS: Pilot, assessor-blind, cluster randomised controlled trial with nested qualitative evaluation.
METHODS: Eight inpatient stroke units, UK.
METHODS: People within 14 days of stroke onset, presenting with lower limb hemiplegia.
METHODS: Participants at control clusters received usual care. Participants at intervention clusters received rehabilitation using an Implicit Learning Approach (ILA); primarily consisting of reduced frequency instructions/feedback, and promotion of an external focus of attention. Video recording was used to understand the ability of intervention site therapists to adhere to the implicit learning principles, and to compare differences between groups.
METHODS: Ability to recruit and retain clusters/participants; suitability and acceptability of data collection processes; appropriateness of fidelity monitoring methods; and appropriateness of chosen outcome measures.
RESULTS: Eight stroke units participated, with four assigned to each group (intervention/control). Fifty-one participants were enrolled (intervention group 21; control group 30). Mean time since stroke was 6 days (SD 3.42; 0-14); mean age was 73 years (SD 14, 25-94). Of those approached to take part, 72% agreed. We found clear differences between groups with respect to the frequency and type of instructional statement. The ILA was acceptable to both patients and therapists.
CONCLUSIONS: It is feasible to evaluate the application and effectiveness of motor learning principles within acute stroke rehabilitation, using a cluster randomised design. A larger study is required to evaluate the benefits of each approach; we provide a range of sample size estimates required for this.

Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development of sophisticated models designed to elucidate the mechanisms of implicit sensorimotor learning. In this review, we argue for a broader perspective, emphasizing the contribution of explicit strategies to sensorimotor learning tasks. Furthermore, we propose a theoretical framework for motor learning that consists of three fundamental processes: reasoning, the process of understanding action-outcome relationships; refinement, the process of optimizing sensorimotor and cognitive parameters to achieve motor goals; and retrieval, the process of inferring the context and recalling a control policy. We anticipate that this \'3R\' framework for understanding how complex movements are learned will open exciting avenues for future research at the intersection between cognition and action.

During visuomotor learning, improvements in motor performance accompany changes in how people use vision. However, the dependencies between altered visual reliance and improvements in motor skill is unclear. The present studies used an online sequence learning task to quantify how changing the availability of visual information affected motor skill learning (Study One) and how changing motor skill affected visual reliance (Study Two). Participants used their keyboard to respond to targets falling vertically down a game screen. In Study One (n=49), the availability of visual information was altered by manipulating where the targets were visible on the screen. Three experimental groups practiced the task during full or limited vision conditions (when the targets were only visible in specific areas). We hypothesized that limiting visual information would reduce motor learning (i.e. the rate of improvement during training trial blocks). Instead, while participants performed worse during limited vision trials (p<0.001), there was no difference in learning rate (p=0.87). In Study Two (n=119), all participants practiced the task with full vision and their visual reliance (i.e., their performance change between full and limited vision conditions) was quantified before and after training. We hypothesized that with motor learning, visual reliance on future targets would increase, while visual reliance on the current targets would decrease. The results of Study Two partially support our hypotheses with visual reliance decreasing for all visual areas (p<0.001). Together, the results suggest changing motor skill alters how people use vision, but changing visual availability does not affect motor learning.

Implicit sensorimotor adaptation keeps our movements well-calibrated amid changes in the body and environment. We have recently postulated that implicit adaptation is driven by a perceptual error: the difference between the desired and perceived movement outcome. According to this perceptual re-alignment model, implicit adaptation ceases when the perceived movement outcome - a multimodal percept determined by a prior belief conveying the intended action, the motor command, and feedback from proprioception and vision - is aligned with the desired movement outcome. Here, we examined the role of proprioception in implicit motor adaptation and perceived movement outcome by examining individuals who experience deafferentation (i.e., individuals with impaired proprioception and touch). We used a modified visuomotor rotation task designed to isolate implicit adaptation and probe perceived movement outcome throughout the experiment. Surprisingly, both implicit adaptation and perceived movement outcome were minimally impacted by chronic deafferentation, posing a challenge to the perceptual re-alignment model of implicit adaptation.

Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effectors, leading to limiting impracticalities: (1) researchers must rely on two different platforms and (2) biomechanical effectors are not generally differentiable, constraining researchers to reinforcement learning algorithms despite the existence and potential biological relevance of faster training methods. To address these limitations, we developed MotorNet, an open-source Python toolbox for creating arbitrarily complex, differentiable, and biomechanically realistic effectors that can be trained on user-defined motor tasks using ANNs. MotorNet is designed to meet several goals: ease of installation, ease of use, a high-level user-friendly application programming interface, and a modular architecture to allow for flexibility in model building. MotorNet requires no dependencies outside Python, making it easy to get started with. For instance, it allows training ANNs on typically used motor control models such as a two joint, six muscle, planar arm within minutes on a typical desktop computer. MotorNet is built on PyTorch and therefore can implement any network architecture that is possible using the PyTorch framework. Consequently, it will immediately benefit from advances in artificial intelligence through PyTorch updates. Finally, it is open source, enabling users to create and share their own improvements, such as new effector and network architectures or custom task designs. MotorNet\'s focus on higher-order model and task design will alleviate overhead cost to initiate computational projects for new researchers by providing a standalone, ready-to-go framework, and speed up efforts of established computational teams by enabling a focus on concepts and ideas over implementation.