Early motor skill development is essential for socioemotional development, cognitive development, and physical preparedness. However, children’s chances for sufficient motor stimulation have decreased in Indonesia due to shifting activity patterns and constrained play areas. A culturally grounded educational alternative that gives organic and comprehensive motor experiences is traditional Indonesian games. This study aims to summarize evidence on the potential of traditional games as inclusive and sustainable methods to support Indonesian children’s development. This study used a Systematic Literature Review (SLR) in accordance with PRISMA 2020, looking for articles published between 2015 and 2025 using Scopus, Web of Science, ScienceDirect, and Google Scholar. Ten of the 1,222 records that were found satisfied the requirements for inclusion following screening and quality evaluation using the JBI checklist. Research demonstrates that games like engklek, gobak sodor, bentengan, congklak, and bekel regularly improve hand-eye coordination, muscular strength, agility, balance, and coordination. Significant improvements were seen in both the gross and fine motor domains throughout interventions spanning 4–8 weeks with two–three weekly sessions. Additionally, traditional games promote sensorimotor learning, social interaction, and intrinsic drive. Traditional games are an efficient, affordable, and culturally appropriate way to assist preschool motor development, despite the fact that many studies used quasi-experimental techniques with small sample sizes. These findings offer compelling evidence for its incorporation into national curricular efforts and early childhood education practices.

This research is concerned with the effect of learning on movement activity to develop groundstroke (Forehand and backhand) tennis skills for 14 year age group female players at Diyala specialized Center of Baghdad. The study was conducted with two groups (experimental and control), one of which was taught using motor activity based instructional modules, while the other was taught through traditional teaching techniques. Analysis included before and after for each set of skills. The results showed that the experimental group was able to achieve a significantly better improvement in accuracy and consistency than the control group, thanks to variety of practice including immersion in practical experience. This made them even more motivated to learn the strokes and deepened their understanding of what is the base technical element of each smash and clear. Conversely, the control group was able to reduce EF through mere repetition. The findings of the study provide support for programs with structured progressive educational content that mesh practical and sensory-motor learning experience, expedite skill acquisition as well as maintain performance progression in young tennis players.

Modern robots face a challenge shared by biological systems: how to learn and adaptively express multiple sensorimotor skills. A key aspect of this is developing an internal model of expected sensorimotor experiences to detect and react to unexpected events, guiding self-preserving behaviors. Associative skill memories (ASMs) address this by linking movement primitives to sensory feedback, but existing implementations rely on hard-coded libraries of individual skills. A key unresolved problem is how a single neural network can learn a repertoire of skills while enabling integrated fault detection and context-aware execution. Here we introduce neural associative skill memories (neural ASMs), a framework that uses self-supervised temporal predictive coding to integrate skill learning and expression using biologically plausible local learning rules. Unlike traditional ASMs, which require explicit skill selection, neural ASMs implicitly recognize and express skills through contextual inference, enabling fault detection using "predictive surprise" across the entire learned repertoire. Compared to recurrent neural networks trained using backpropagation through time, our model achieves comparable qualitative performance in skill memory expression while using local learning rules and predicts a biologically relevant speed-versus-accuracy trade-off. By integrating fault detection, reactive control, and skill expression into a single energy-based architecture, neural ASMs contribute to safer, self-preserving robotics and provide a computational lens to study biological sensorimotor learning.

Abstract Background Extended reality (XR), encompassing virtual reality, augmented reality (AR), and mixed reality, is increasingly being used in neurorehabilitation to provide multisensory feedback and promote neural plasticity in sensorimotor networks. Objective This scoping review aimed to (1) examine how XR technologies are applied in motor neurorehabilitation, (2) explore how body representation and somatic embodiment are addressed, and (3) analyze the methodological designs of XR-based interventions. Methods This review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, with a comprehensive search across PubMed, Embase, Scopus, and Web of Science from inception to December 2023. Eligible studies included original research involving XR-based interventions explicitly targeting neurorehabilitation. Studies related to somatic embodiment and reporting data on implementation and user outcomes were considered without date restriction. Three independent reviewers conducted screening in Covidence. The following variables were extracted: study design, participant characteristics, XR devices and software, experimentation details, treatment approaches, and evaluation methods. Methodological quality of the included studies was assessed using the Newcastle-Ottawa Scale and the Murad Scale. Findings have been presented in tabular and narrative formats. Results Twenty-six studies met the inclusion criteria, and these were mainly clinical trials involving patients with neurological conditions, particularly poststroke status (n=6) and spinal cord injury (n=2). Several studies provided physiological data, including electroencephalography (n=12), electromyography (n=2), magnetic resonance imaging (n=1), galvanic skin response (n=1), electrodermal activity (n=1), and motor-evoked potential data (n=1). Two studies used noninvasive brain stimulation, and another two used eye tracking. Most studies (n=17) used built-in motion sensors; however, some (n=8) analyzed the data quantitatively. Unity 3D was the most frequently used development platform (n=8). First-person (n=20) and third-person (n=2) perspectives were used, and 4 studies combined both perspectives. Interventions mainly targeted sensorimotor deficits, with improvements in motor and cognitive performance. Sixteen studies addressed body perception, focusing on limb embodiment. Questionnaires were the most frequently used evaluation tools (n=18), and 3 studies used standardized tests. Some studies (n=7) investigated body ownership under visuomotor inconsistencies with or without visuotactile stimulation. XR was primarily applied to enhance sensorimotor recovery and assess device feasibility. Few studies directly measured embodiment (n=4), ownership (n=2), or self-location (n=2). The ability of XR platforms to deliver multisensory feedback appears to facilitate sensorimotor learning and support a more accurate body schema. Conclusions Evidence from the studies supports the usefulness of XR in enhancing reinforcement learning and facilitating recovery in neurorehabilitation. Tailored XR approaches, which are grounded in embodiment principles and patient-specific needs, show promise for improving outcomes in neurological rehabilitation programs. The AR paradigm, which could offer several advantages, was not explored in depth, perhaps due to its difficult implementation during the period considered.

The article focuses on reflecting on the experience in the museum setting through the prism of museum pedagogy, taking into account permanent historically - focused museum exhibitions, which constitute the dominant thematic profile in a wide range of local museum exhibitions. It aims to formulate the theoretical basis for presenting and working with exhibits, without overlooking the emotional and social aspects, in addition to supporting the development of cognitive and sensorimotor thinking and learning. Attitudes towards visitors and considering their experiences and emotions during a museum visit have changed, as have the approaches of museums to how they conceive their own presentation concepts and resources in the most appropriate (didactic) way, and how they convey the potential of collection items and their informative value to visitors in acceptable forms. These aspects are illustrated in the article by specific examples from museums and their permanent historically - focused exhibitions.

IntroductionPrism adaptation is a well-established paradigm for studying sensorimotor plasticity, known to produce not only motor after-effects but also changes in spatial cognition. Whether visuomotor rotation—a similar form of sensorimotor adaptation—elicits comparable cognitive transfer remains unclear.MethodsParticipants performed visuomotor rotation tasks involving either leftward or rightward 15° rotations. The perturbation was introduced either abruptly (within one trial) or gradually (over 34 trials). To assess potential cognitive transfer, participants completed a perceptual line bisection task before and after adaptation.ResultsNo condition (leftward/rightward or abrupt/gradual) induced measurable cognitive after-effects in line bisection performance, indicating an absence of transfer from sensorimotor to spatial-cognitive domains. However, a novel finding emerged: visuomotor rotation enhanced participants’ representational acuity, reflected in improved sensitivity when judging the midpoint of a line. This effect was most pronounced following gradual perturbations and persisted beyond the adaptation phase.DiscussionThese findings demonstrate a clear dissociation between the cognitive and perceptual consequences of visuomotor adaptation. Visuomotor rotation thus provides a reliable means to study sensorimotor plasticity without altering spatial representation—a methodological advantage for investigating populations with atypical spatial biases. The enhancement of representational acuity further suggests that sensorimotor learning can refine spatial discrimination independently of cognitive recalibration.

Respiration is a crucial metabolic process that converts macronutrients, carbohydrates and fats, and oxygen into energy and carbon dioxide to support motor actions. Moreover, the brain is a significant energy consumer, accounting for large portions of the body's total energy expenditure and relying primarily on carbohydrates for neural activity and plasticity. However, it is not known whether gas composition in breathing can serve as an indicator of neural activity and plasticity as they can for movement intensity. In human reaching movement tasks, we evaluated time-constants of sensorimotor learning during the recording of gas exchange. We computed the respiratory exchange ratio (RER), indicating whether carbohydrate or fat is used preferentially, and found that the RER was unaffected by the execution and learning of reaching movements and that it was stable within but varied across individuals. Interestingly, using computational modelling to identify short and long-time constants of sensorimotor learning, individual RER levels correlated with the estimated slow component of learning dynamics, suggesting a link between metabolic state and processes underlying long-term retention. To probe this further, we used glucose administration, known to increase RER by promoting carbohydrate utilisation, before training. Regression analysis indicated that glucose-induced RER increases during training were associated with enhanced estimated 24h retention at the intra-individual level. Together, RER is associated with processes underlying long-term memory acquisition and retention, and glucose administration shifted the physiological idling state for the processes. Unravelling the specific neurobiological pathway from these intriguing breathing metrics to brain function emerges as a compelling new research direction. KEY POINTS: The brain is a major energy consumer (20% of total energy from only 2% of body weight), primarily using carbohydrates for neural activity and plasticity. The respiratory exchange ratio (RER) in breath signals the body's balance of fat-carbohydrate fuel use; this study explored whether RER reflects neural processes in motor memory acquisition and retention. Individual RER, stable during reaching tasks but varying across participants, correlated with the computationally estimated slow component of learning dynamics, which is linked to long-term retention. Glucose administration, known to increase RER, was associated with improved estimated 24h motor memory retention at an individual level. The results suggest that RER indicates long-term motor memory processes and that manipulating RER via glucose may enhance motor memory, offering a new neurobiological pathway from these intriguing breathing metrics to memory function and potential practical implications for a simple but plausible intervention.

To navigate dynamic environments, animals must rapidly integrate sensory information and respond appropriately to gather rewards and avoid threats. It is well established that dopamine (DA) neurons in the ventral tegmental area (VTA) and substantia nigra (SNc) are key for creating associations between environmental stimuli (i.e., cues) and the outcomes they predict. Critically, it remains unclear how sensory information is integrated into DA pathways. The superior colliculus (SC) receives direct visual input and is positioned as a relay for DA neuron augmentation. We characterized the anatomy and functional impact of SC projections to the VTA/SNc in male and female rats. First, we show that neurons in the deep layers of SC synapse densely throughout the ventral midbrain, interfacing with projections to the striatum and ventral pallidum, and these SC projections excite DA and GABA neurons in the VTA/SNc in vivo. Despite this, cues predicting SC→VTA/SNc neuron activation did not reliably evoke behavior in an optogenetic pavlovian conditioning paradigm, and activation of SC→VTA/SNc neurons did not support primary reinforcement or produce place preference/avoidance. Instead, we find that stimulation of SC→VTA/SNc neurons evokes head turning. Focusing optogenetic activation solely onto DA neurons that receive input from the SC was sufficient to invigorate turning, but not reinforcement. Turning intensity increased with repeated stimulations, suggesting that this circuit may underlie sensorimotor learning for exploration and attentional switching. Together, our results show that collicular neurons contribute to cue-guided behaviors by controlling pose adjustments through interaction with DA neurons that preferentially engage movement instead of reward.

How individuals process and respond to uncertainty has important implications for cognition and mental health. Here, we use computational phenotyping to examine inter-individual differences in uncertainty processing in relation to neurometabolites and trait anxiety in humans. We introduce a categorical state-transition extension of the Hierarchical Gaussian Filter to model individuals’ evolving beliefs about transition probabilities in a four-choice probabilistic sensorimotor learning task with a reversal. Using 7-Tesla Magnetic Resonance Spectroscopy, we measure neurotransmitter levels in the primary motor cortex. Model-based results reveal dynamic belief updating in response to environmental changes. We further find region-specific relationships between baseline primary motor cortex glutamate+ glutamine levels and prediction errors and volatility beliefs. High trait anxiety is associated with faster post-reversal responses. This study establishes a direct neurochemical correlate of hierarchical belief updating, identifying motor cortex glutamate + glutamine as an important neural marker of inter-individual differences in uncertainty processing.

Transcranial alternating current stimulation (tACS) is a noninvasive neuromodulatory tool that is thought to entrain intrinsic neural oscillations by supplying low electric currents over the scalp. Recent work has demonstrated the efficacy of theta-gamma phase-amplitude coupled tACS over primary motor cortex to enhance motor skill acquisition and motor recovery after stroke. Here, we wished to assess the efficacy of tACS delivered with 75-Hz gamma coupled to the peak of a 6-Hz theta envelope (theta-gamma peak; TGP) at an intensity of 2 mA peak-to-peak to enhance sensorimotor learning during speech production. Sensorimotor learning was measured by shifting the formant frequency of vowels in real-time as speech is produced and measuring the adaptation to this altered feedback. The study was a between-subjects, single-blind, sham-controlled design. We hypothesised that participants who performed the speech task while receiving TGP tACS over the speech motor cortex (N = 30) would show greater adaptation to altered auditory feedback than those receiving sham stimulation (N = 31). Contrary to this hypothesis, there was no effect of TGP tACS on adaptation to the upwards F1 shift in auditory feedback in either the final 30 trials of the learning phase or in the first 15 trials of the after-effect phase. However, a trend emerged in the TGP tACS group for greater retention of the adapted state and slower return to baseline F1 values in the after-effect phase. This finding was not predicted, and highlights the need for further investigation to deepen our understanding of the effects of TGP tACS on speech motor learning.

Failure to replicate enhancement of speech adaptation using tDCS over motor cortex and cerebellum.

Integrative functional optical imaging approaches: Optics, microfluidics, and machine learning for neuroscience in organoids and small-animal models.

Complex cognitive and motivational deficits precede motor dysfunction in the zQ175 (190 CAG repeat) Huntington's disease model.

To navigate dynamic environments, animals must rapidly integrate sensory information and respond appropriately to gather rewards and avoid threats. It is well established that dopamine (DA) neurons in the ventral tegmental area (VTA) and substantia nigra (SNc) are key for creating associations between environmental stimuli (i.e., cues) and the outcomes they predict. Critically, it remains unclear how sensory information is integrated into dopamine pathways. The superior colliculus (SC) receives direct visual input and is positioned as a relay for dopamine neuron augmentation. We characterized the anatomical organization and functional impact of SC projections to the VTA and SNc in rats. First, we show that neurons in the deep layers of SC synapse densely throughout the ventral midbrain, interfacing with projections to the striatum and ventral pallidum, and these SC projections excite dopamine and GABA neurons in the VTA/SNc in vivo. Despite this, cues predicting SC→VTA/SNc neuron activation did not reliably evoke behavior in an optogenetic Pavlovian conditioning paradigm, and activation of SC→VTA/SNc neurons did not support primary reinforcement or produce place preference/avoidance. Instead, we find that stimulation of SC→VTA/SNc neurons evokes head turning. Focusing optogenetic activation solely onto dopamine neurons that receive input from the SC was sufficient to invigorate turning, but not reinforcement. Turning intensity increased with repeated stimulations, suggesting that this circuit may underlie sensorimotor learning for exploration and attentional switching. Together our results show that collicular neurons contribute to cue-guided behaviors by controlling pose adjustments through interaction with dopamine neurons that preferentially engage movement instead of reward.

SUMMARYThe dorsal striatum plays a critical role in action selection, movement, and sensorimotor learning. While action-specific striatal ensembles have been described, the mechanisms underlying their formation and evolution during motor learning remain poorly understood. Here, we employed longitudinal two-photon Ca2+ imaging of dorsal striatal neurons in head-fixed mice as they learned to self-initiate locomotion. We found that both direct- and indirect-pathway spiny projection neurons (dSPNs and iSPNs, respectively) exhibited robust activation during early locomotor bouts, with activity gradually diminishing across sessions. For dSPNs, action onset and offset ensembles progressively emerged from an initially broad population of nonspecific neurons. In contrast, iSPN ensembles originated from neurons responsive to opposing actions before refining into onset- or offset-specific populations. These findings demonstrate that striatal ensemble activity becomes more selective over time, with a reduction in nonspecific neuronal activation and an increase in the efficiency of striatal encoding for learned motor actions.

Across development, children must learn motor skills such as drawing with a crayon. Reinforcement learning, driven by success and failure, is fundamental to such sensorimotor learning. It typically requires a child to explore movement options along a continuum (grip location on a crayon) and learn from probabilistic rewards (whether the crayon draws or breaks). We studied the development of reinforcement motor learning using online motor tasks to engage children aged 3-17 years and adults (cross-sectional sample, N=385). Participants moved a cartoon penguin across a scene and were rewarded (animated cartoon clip) based on their final movement position. Learning followed a clear developmental trajectory when participants could choose to move anywhere along a continuum and the reward probability depended on the final movement position. Learning was incomplete or absent in 3-8 year-olds and gradually improved to adult-like levels by adolescence. A reinforcement learning model fit to each participant identified two age-dependent factors underlying improvement across development: an increasing amount of exploration after a failed movement and a decreasing level of motor noise. We predicted, and confirmed, that switching to discrete targets and deterministic reward would improve 3-8 year-olds' learning to adult-like levels by increasing exploration after failed movements. Overall, we show a robust developmental trajectory of reinforcement motor learning abilities under ecologically relevant conditions, that is, continuous movement options mapped to probabilistic reward. This learning may be limited by immature spatial processing and probabilistic reasoning abilities in young children and can be rescued by reducing task demands.

The sensorimotor system continuously uses error signals to remain precisely calibrated. We examined how attention influences this automatic and implicit learning process in humans (male and female). Focusing first on spatial attention, we compared conditions in which attention was oriented either toward or away from the visual feedback that defined the error signal. Surprisingly, this manipulation had no effect on the rate of sensorimotor adaptation. Using dual-task methods, we next examined the influence of attentional resources on adaptation. Again, we found no effect of attention, with the rate of adaptation similar under focused and divided attention conditions. However, we found that attention modulates adaptation in an indirect manner: The rate of adaptation was significantly attenuated when the attended stimulus changed from the end of one trial to the start of the next trial. In contrast, similar changes to unattended stimuli had no impact on adaptation. These results suggest that visual attention defines the cues that establish the context for sensorimotor learning.

The development of new studies that consider different structures of the hierarchical sensorimotor control system is essential to enable a more holistic understanding about movement. The incorporation of more biological proprioceptive and neuronal circuit models to muscles can turn neuromusculoskeletal systems more appropriate to investigate and elucidate motor control. Specifically, further studies that consider the closed-loop between proprioception and central nervous system may allow to better understand the yet open question about the importance of afferent feedback for sensorimotor learning and execution in the intact biological system. Therefore, this study aims to investigate the processing of spindle afferent firings by spiking neuronal network and their relevance for sensorimotor control. We integrated our previously published physiological model of the muscle spindle in a biological arm model, corresponding to a musculoskeletal system able to reproduce biological motion inside of the demoa multi-body simulation framework. We coupled this musculoskeletal system to physiologically-motivated neuronal spinal pathways, which were implemented based on literature in the NEST spiking neural network simulator, intended to perform human center-out reaching arising from spinal synaptic learning. As result, the spindle connections to the spinal neurons were strengthened for the more difficult targets (i.e. higher above placed targets) under perturbation, highlighting the importance of spindle proprioception to succeed in more difficult scenarios. Furthermore, an additionally-implemented simpler spinal network (that does not include the pathways with spindle proprioception) presented an inferior performance in the task by not being able to reach all the evaluated targets.

An often-desired feature of motor learning is that it generalizes to untrained scenarios. Yet, how this is supported by brain activity remains poorly understood. Here we show, using human functional MRI and a sensorimotor adaptation task involving the transfer of learning from the trained to untrained hand, that the transfer phase of adaptation re-instantiates a highly similar large-scale pattern of brain activity to that observed during initial adaptation. Notably, we find that these neural changes, rather than occurring at the level of sensorimotor regions, predominantly occur across distributed areas of higher-order transmodal cortex, specifically in regions of the default mode network (DMN). Moreover, we show that these learning-related neural changes relate to the structural properties of transmodal cortex (its myelin content and neurotransmitter receptor density), and that intersubject differences in DMN activity relate to both adaptation- and transfer-phase task performance. Together, these findings suggest that the transfer of learning across the hands is supported by the re-expression of the same activity patterns in the DMN as those that support initial learning. Collectively, these results offer a unique characterization of the whole-brain macroscale changes associated with sensorimotor learning and generalization, and establish a key role for higher-order brain areas, such as the DMN, in the transfer of learning to untrained scenarios.

The sensorimotor system must constantly decide which errors to learn from and which to ignore. Recent work has shown that humans are remarkably precise in parsing movement errors into internally and externally generated components for this purpose: participants automatically ignore internally generated reaching errors caused by motor noise, yet implicitly adapt to size-matched externally generated errors caused by visual perturbations. Following replication of these results with 16 neurotypical adults, we formalized our understanding of this behaviour with a novel Bayesian decision-making model. The Parsing of Internal and External Causes of Error (PIECE) model frames adaptation as a process of causal inference regarding the source of error, with the magnitude of motor corrections reflecting a combination of state estimation and the observer's degree-of-belief that their movement was externally perturbed. Thus, PIECE challenges current computational theories that posit adaptation as a process of re-aligning the perceived hand position with the movement goal. When formally compared with three representative models of this hand-to-target alignment view, we show that only PIECE can capture the precise parsing of internal versus external errors observed. Combined, this work provides a normative explanation of how the nervous system discounts intrinsic motor noise and adapts to perturbations, keeping movements finely calibrated.