Pablo Maceira-Elvira

The field of motor learning faces a critical gap between foundational theory and real-world application. This editorial synthesizes expert discussions from the First Theoretical and Applied Advances in Motor Learning Conference to address key issues impeding further progress. We are hampered by the science of “averages,” characterized by an overreliance on data from homogenous, Western, educated, industrialized, rich, and democratic populations and a flawed assumption of cognitive uniformity. This approach masks critical individual differences, limiting the translational potential of our science and leading to one-size-fits-all enhancement strategies. We propose a multitiered roadmap for the maturation of our field. The foundational priorities are structural: embracing co-creation with diverse communities; moving beyond Western, Educated, Industrialized, Rich, and Democratic science; and implementing structured mentorship and active sponsorship to empower a new generation of scholars. Building on this, we advocate for technology-driven individualization like using advanced Mobile Brain/Body Imaging techniques for the development of neurophenotypes, to fulfill the potential of Brain–Computer Interfaces. Finally, we call for a precision-enhancement framework, shifting from “learning boosters” to a diagnostic-to-prescriptive model that targets specific, identified bottlenecks. This roadmap allows our field to build upon its foundational principles to create a more effective, accessible, and equitable motor learning science for all.

The study introduces a framework to assess the complexity of neural outputs elicited by transcranial magnetic stimulation (TMS). We demonstrated that complexity, obtained from multimuscle motor-evoked potentials (MEPs) through dimensionality reduction, varied depending on stimulus intensities, was minimally influenced by the selection of muscles, and was associated with individual differences in motor cortex anatomy. Importantly, individuals with higher complexity exhibited better dexterous performance. The framework offers a novel perspective for investigating the motor system.

Healthy aging often entails a decline in cognitive and motor functions, affecting independence and quality of life in older adults. Brain stimulation shows potential to enhance these functions, but studies show variable effects. Previous studies have tried to identify responders and non-responders through correlations between behavioral change and baseline parameters, but results lack generalization to independent cohorts. We propose a method to predict an individual’s likelihood of benefiting from stimulation, based on baseline performance of a sequential motor task. Our results show that individuals with less efficient learning mechanisms benefit from stimulation, while those with optimal learning strategies experience none or even detrimental effects. This differential effect, first identified in a public dataset and replicated here in an independent cohort, was linked to one’s ability to integrate task-relevant information and not age. This study constitutes a further step towards personalized clinical-translational interventions based on brain stimulation.

Brain stimulation shows potential at enhancing cognitive and motor functions in humans. However, multiple studies assessing its effects on behavior show heterogeneous results, especially in healthy older subjects. We propose a new method to predict an individual’s likelihood and the magnitude of the benefit from stimulation, based on the baseline performance of a sequential motor task, framed in the context of their age. Our results show a differential effect of stimulation, in which individuals with less efficient learning mechanisms benefit from stimulation, while those possessing optimal learning strategies resent a detrimental effect. Importantly, this differential effect was determined by one’s ability to integrate task-relevant information at the early stages of training, and not the age. This study paves the way towards the personalized application of stimulation to maximize its effects, and constitutes the first steps to implement an individualized translational clinical intervention, based on the state of the neural system. Teaser: Age notwithstanding, brain stimulation is most effective in deficient neural systems, while being detrimental to optimal systems Visual Main finding: Anodal transcranial direct current stimulation (atDCS), applied over the hand representation of the motor cortex concomitant to the training of a sequential motor sequence, has differential effects as a function of the recipient’s ability to integrate task-relevant information at the early stages of training. Stimulation benefits individuals with seemingly less efficient learning mechanisms, enabling the rapid storage of the spatial coordinates of the motor sequence and an accelerated optimization of the accuracy of execution. In contrast, individuals possessing optimal learning mechanisms experience detrimental effects of stimulation, leading to drops in the accuracy of execution.

The stimulation of deep brain structures has thus far been possible only with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-concept was obtained through modeling, physics experiments and rodent models. Here, we show for the first time successful noninvasive neuromodulation of the striatum via tTIS in humans using computational modeling, fMRI studies and behavioral evaluations. Theta-burst patterned, LTP-like striatal tTIS increased activity in the striatum and associated motor network. Furthermore, striatal tTIS enhanced motor learning capacity, especially in healthy older participants, who have lower natural learning capacity than younger subjects. These findings suggest exciting methods for noninvasively targeting deep brain structures in humans, thus enhancing our understanding of their functional roles. Moreover, our results lay the groundwork for innovative, noninvasive treatment strategies for brain disorders, in which deep brain structures play key pathophysiological roles.

Practicing a previously unknown motor sequence often leads to the consolidation of motor chunks, which enable its accurate execution at increasing speeds. Recent imaging studies suggest the function of these structures to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We found that optimal motor skill acquisition prioritizes the storage of the spatial features of the sequence in memory over its rapid execution early in training, as proposed by Hikosaka in 1999. This process, seemingly diminished in older adults, was partially restored by anodal transcranial direct current stimulation over the motor cortex, as shown by a sharp improvement in accuracy and an earlier yet gradual emergence of motor chunks. These results suggest that the emergence of motor chunks is preceded by the storage of the sequence in memory but is not its direct consequence; rather, these structures depend on, and result from, motor practice.

During learning of novel motor sequences, practice leads to the consolidation of hierarchical structures, namely motor chunks, facilitating the accurate execution of sequences at increasing speeds. Recent studies show that such hierarchical structures are largely represented upstream of the primary motor cortex in the motor network, suggesting their function to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We isolated different components of motor skill acquisition related to the consolidation of spatiotemporal features and followed their evolution over training. We found that optimal motor skill acquisition relies on the storage of the spatial features of the sequence in memory, followed by the optimization of its execution and increased execution speeds (i.e., a shift in the speed-accuracy trade-off) early in training, supporting the model proposed by Hikosaka in 1999. Contrasting the dynamics of these components during ageing, we identified less-than-optimal mechanisms in older adults explaining the observed differences in performance. We applied noninvasive brain stimulation in an attempt to support the aging brain to compensate for these deficits. The present study found that anodal direct current stimulation applied over the motor cortex restored the mechanisms involved in the consolidation of spatial features, without directly affecting the speed of execution of the sequence. This led older adults to sharply improve their accuracy, resulting in an earlier yet gradual emergence of motor chunks. The results suggest the early storage of the sequence in memory, largely independent of motor practice, is crucial for an optimal motor acquisition and retrieval of this motor behavior. Nevertheless, the consolidation of optimal temporal patterns, detected as motor chunks at a behavioral level, is not a direct consequence of storing the sequence elements, but rather of motor practice.

Stroke is one of the main causes of long-term disability worldwide, placing a large burden on individuals and society. Rehabilitation after stroke consists of an iterative process involving assessments and specialized training, aspects often constrained by limited resources of healthcare centers. Wearable technology has the potential to objectively assess and monitor patients inside and outside clinical environments, enabling a more detailed evaluation of the impairment and allowing the individualization of rehabilitation therapies. The present review aims to provide an overview of wearable sensors used in stroke rehabilitation research, with a particular focus on the upper extremity. We summarize results obtained by current research using a variety of wearable sensors and use them to critically discuss challenges and opportunities in the ongoing effort towards reliable and accessible tools for stroke rehabilitation. Finally, suggestions concerning data acquisition and processing to guide future studies performed by clinicians and engineers alike are provided.

A key feature of a successful game is its ability to provide the player with an adequate level of challenge. However, the objective of difficulty adaptation in serious games is not only to maintain the player’s motivation by challenging, but also to ensure the completion of training objectives.This paper describes our proposed upper-limb rehabilitation game with tangible robots and investigates the effect of game elements and gameplay on the amount of the performed motion in several planes and percentage of failure by using the data from 33 unimpaired subjects who played 53 games within two consecutive days. In order to provide a more generic adaptation strategy in the future, we discretize the game area to circular zones. We then show the effect of changing these zones during gameplay on the activation of different muscles through EMG data in a pilot study.The study shows that it is possible to increase the challenge level by adding more active agents chasing the player and increasing the speed of these agents. However, only the increase in number of agents significantly increases the users’ motion on both planes. Analysis of player behaviors leads us to suggest that by adapting the behaviour of these active agents in specific zones, it is possible to change the trajectory of the user, and to provide a focus on the activation of specific muscles.