Accurate perception of visuo-motor errors is essential for perceptual and sensorimotor learning so that corrective actions are performed timely to maintain stability and goal-directed behavior. However, a key challenge remain: conventional, behavioral perceptual training — typically based on response accuracy feedback— is limited in improving sensitivity to small, subtle errors. While prior approaches have focused on modulating sensory regions to enhance perceptual learning, we propose an alternative approach: targeting a cognitive neural marker, namely the error positivity (Pe), a component of the error-related potential (ErrP) that primarily originates in the anterior cingulate cortex (ACC), a key region involved in decision-making. We hypothesize that the Pe, which reflects conscious awareness of errors, serves as a modifiable neural correlate of error perception. To address the performance bottlenecks seen in conventional, behavioral perceptual training, we show that real-time feedback on ErrP presence or absence during perceptual training over five longitudinal days enhances the Pe component and improves participants’ ability to detect small visuo-motor errors —an outcome not achieved through conventional, behavioral perceptual training. These findings offer new neurophysiological insights into error perception and learning, and establish ErrP-based BCI interventions as a promising tool for accelerating perceptual learning, particularly in contexts where subtle error detection is critical. ### Competing Interest Statement The authors have declared no competing interest.

Multiple studies have demonstrated that transcranial direct current stimulation (tDCS) of the primary motor cortex (M1) can influence corticospinal excitability and motor skill acquisition. However, the evidence for these effects is inconsistent, and a common neural substrate for these effects has not been directly demonstrated. To address this, we hypothesized that higher tDCS intensities would produce more robust effects, and uncover their relationship. In this preregistered study, 120 participants engaged in a motor skill learning task while receiving tDCS with posterior-to-anterior currents through M1. We employed a double-blind, between-subjects design, with groups of 4 mA, 6 mA, or sham stimulation, while ensuring balanced groups in terms of typing speed. Cortical excitability was assessed via motor-evoked potentials (MEPs) and TMS-evoked potentials (TEPs) before and after motor skill learning with concurrent tDCS. tDCS at these higher intensities was well tolerated, and motor learning correlated with pretraining typing speed.Planned analysesfound no dose-response effect of tDCS on motor skill performance or MEP amplitude. This suggests that, under our experimental conditions, tDCS did not significantly modulate motor skill learning or corticospinal excitability. Furthermore, there was no correlation between motor performance and MEP, and thus no evidence for a common neural substrate.Exploratory analysesfound an increase in MEP and TEP amplitudes following the sequence learning task. Motor skill gains positively correlated with TEP changes over the stimulated M1, which were more negative with increasing tDCS intensity. The effects of tDCS on motor skill learning and MEPs, if they exist, may require particular experimental conditions that have not been tested here. Preregistration:https://osf.io/jyuev(in-principle acceptance: 2024/06/05).

Activities of daily living rely on our ability to acquire new motor skills composed of precise action sequences. Here, we asked in humans if the millisecond-level neural representation of an action performed at different contextual sequence locations within a skill differentiates or remains stable during early motor learning. We first optimized machine learning decoders predictive of sequence-embedded finger movements from magnetoencephalographic (MEG) activity. Using this approach, we found that the neural representation of the same action performed in different contextual sequence locations progressively differentiated—primarily during rest intervals of early learning (offline)—correlating with skill gains. In contrast, representational differentiation during practice (online) did not reflect learning. The regions contributing to this representational differentiation evolved with learning, shifting from the contralateral pre- and post-central cortex during early learning (trials 1–11) to increased involvement of the superior and middle frontal cortex once skill performance plateaued (trials 12–36). Thus, the neural substrates supporting finger movements and their representational differentiation during early skill learning differ from those supporting stable performance during the subsequent skill plateau period. Representational contextualization extended to Day 2, exhibiting specificity for the practiced skill sequence. Altogether, our findings indicate that sequence action representations in the human brain contextually differentiate during early skill learning, an issue relevant to brain-computer interface applications in neurorehabilitation.

Early skill learning develops in the context of activity changes in distributed cortico-subcortical regions. Here, we investigated network hubs-centers of information integration and transmission-within the brain network supporting early skill learning. We recorded magnetoencephalographic (MEG) brain activity in healthy human subjects who learned a challenging sequence skill with their non-dominant left hand. We then computed network hub strength by summing top 10 % functional connectivity over 86 parcellated brain regions (AAL3 atlas) and five brain oscillatory frequency bands (alpha, low-, high-beta, low- and high-gamma). Virtually all skill gains developed during rest intervals of early learning (micro-offline gains). MEG hub strength in the alpha band (8-13 Hz) in bilateral anterior cingulate (ACC) and caudate and in the low-beta band (13-16 Hz) in bilateral caudate and right putamen correlated with micro-offline gains. These regions linked strongly with the hippocampus, parahippocampal cortex, and lingual and fusiform gyri. Thus, alpha and low-beta brain oscillatory activity in cingulate and striatal regions appear to contribute as hubs of information integration and transmission during early skill learning. SIGNIFICANCE STATEMENT: Early learning of challenging skill sequences develops over periods of rest interspersed with practice (micro-offline gains). We demonstrate here a link between alpha and low-beta oscillatory activity in a cingulate-hippocampo-striato network hubs and rest intervals of early learning.

When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments ( N = 2095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0–30 s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill.

BACKGROUND AND OBJECTIVES:At least 15% of patients who recover from acute severe acute respiratory syndrome coronavirus 2 infection experience lasting symptoms ("Long-COVID") including "brain fog" and deficits in declarative memory. It is not known if Long-COVID affects patients' ability to form and retain procedural motor skill memories. The objective was to determine the ability of patients with Long-COVID to acquire and consolidate a new procedural motor skill over 2 training days. The primary outcome was to determine difference in early learning, measured as the increase in correct sequence typing speed over the initial 11 practice trials of a new skill. The secondary outcomes were initial and final typing speed on days 1 and 2, learning rate, overnight consolidation, and typing accuracy. METHODS:In this prospective, cross-sectional, online, case-control study, participants learned a sequential motor skill over 2 consecutive days (NCT05746624). Patients with Long-COVID (reporting persistent post-coronavirus disease 2019 [COVID-19] symptoms for more than 4 weeks) were recruited at the NIH. Patients were matched one-to-one by age and sex to controls recruited during the pandemic using a crowd-sourcing platform. Selection criteria included age 18-90 years, English speaking, right-handed, able to type with the left hand, denied active fever or respiratory infection, and no previous task exposure. Data were also compared with an age-matched and sex-matched control group who performed the task online before the COVID-19 pandemic (prepandemic controls). RESULTS:In total, 105 of 236 patients contacted agreed to participate and completed the experiment (mean ± SD age 46 ± 12.8 years, 82% female). Both healthy control groups had 105 participants (mean age 46 ± 13.1 and 46 ± 11.9 years, 82% female). Early learning was comparable across groups (Long-COVID: 0.36 ± 0.24 correct sequences/second, pandemic controls: 0.36 ± 0.53 prepandemic controls: 0.38 ± 0.57, patients vs pandemic controls [CI -0.068 to 0.067], vs prepandemic controls [CI -0.084 to 0.052], and between controls [CI -0.083 to 0.053], p = 0.82). Initial and final typing speeds on days 1 and 2 were slower in patients than controls. Patients with Long-COVID showed a significantly reduced overnight consolidation and a nonsignificant trend to reduced learning rates. DISCUSSION:Early learning was comparable in patients with Long-COVID and controls. Anomalous initial performance is consistent with executive dysfunction. Reduction in overnight consolidation may relate to deficits in procedural memory formation.

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 abstract 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.

Background and Aims: The purpose of this Third Stroke Recovery and Rehabilitation Roundtable (SRRR3) was to develop consensus recommendations to address outstanding barriers for the translation of preclinical and clinical research using the non-invasive brain stimulation (NIBS) techniques Transcranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS) and provide a roadmap for the integration of these techniques into clinical practice.Methods: International NIBS and stroke recovery experts (N = 18) contributed to the consensus process. Using a nominal group technique, recommendations were reached via a five-stage process, involving a thematic survey, two priority ranking surveys, a literature review and an in-person meeting.Results and Conclusions: Results of our consensus process yielded five key evidence-based and feasibility barriers for the translation of preclinical and clinical NIBS research, which were formulated into five core consensus recommendations. Recommendations highlight an urgent need for (1) increased understanding of NIBS mechanisms, (2) improved methodological rigor in both preclinical and clinical NIBS studies, (3) standardization of outcome measures, (4) increased clinical relevance in preclinical animal models, and (5) greater optimization and individualization of NIBS protocols. To facilitate the implementation of these recommendations, the expert panel developed a new SRRR3 Unified NIBS Research Checklist. These recommendations represent a translational pathway for the use of NIBS in stroke rehabilitation research and practice.

Various levels of somatotopic organization are present throughout the human nervous system. However, this organization can change when needed based on environmental demands, a phenomenon known as neuroplasticity. Neuroplasticity can occur when learning a new motor skill, adjusting to life after blindness, or following a stroke. Following an injury, these neuroplastic changes can be adaptive or maladaptive, and often occur regardless of whether rehabilitation occurs or not. But not all movements produce neuroplasticity, nor do all rehabilitation interventions. Here, we focus on research regarding how to maximize adaptive neuroplasticity while also minimizing maladaptive plasticity, known as applied neuroplasticity. Emphasis is placed on research exploring how best to apply neuroplastic principles to training environments and rehabilitation protocols. By studying and applying these principles in research and clinical practice, it is hoped that learning of skills and regaining of function and independence can be optimized.

Background and objectives: Motor learning experiments with transcranial direct current stimulation (tDCS) at 2 mA have produced mixed results. We hypothesize that tDCS boosts motor learning provided sufficiently high field intensity on the motor cortex.Methods: In a single-blinded design, 108 healthy participants received either anodal (N = 36) or cathodal (N = 36) tDCS at 4 mA total, or no stimulation (N = 36) while they practiced a 12-min sequence learning task. Anodal stimulation was delivered across four electrode pairs (1 mA each), with anodes above the right parietal lobe and cathodes above the right frontal lobe. Cathodal stimulation, with reversed po-larities, served as an active control for sensation, while the no-stimulation condition established baseline performance. fMRI-localized targets on the primary motor cortex in 10 subjects were used in current flow models to optimize electrode placement for maximal field intensity. A single electrode montage was then selected for all participants.Results: We found a significant difference in performance with anodal vs. cathodal stimulation (Cohen's d = 0.71) and vs. no stimulation (d = 0.56). This effect persisted for at least 1 h, and subsequent learning for a new sequence and the opposite hand also improved. Sensation ratings were comparable in the active groups and did not exceed moderate levels. Current flow models suggest the new electrode montage can achieve stronger motor cortex polarization than alternative montages.Conclusion: The present paradigm shows a medium to large effect size and is well-tolerated. It may serve as a go-to experiment for future studies on motor learning and tDCS. (c) 2023 The Authors. Published by Elsevier Inc.

Human skills are composed of sequences of individual actions performed with utmost precision. When occasional errors occur, they may have serious consequences, for example, when pilots are manually landing a plane. In such cases, the ability to predict an error before it occurs would clearly be advantageous. Here, we asked whether it is possible to predict future errors in a keyboard procedural human motor skill. We report that prolonged keypress transition times (KTTs), reflecting slower speed, and anomalous delta-band oscillatory activity in cingulate-entorhinal-precuneus brain regions precede upcoming errors in skill. Combined anomalous low-frequency activity and prolonged KTTs predicted up to 70% of future errors. Decoding strength (posterior probability of error) increased progressively approaching the errors. We conclude that it is possible to predict future individual errors in skill sequential performance.

Abundant evidence shows that consolidated memories are susceptible to modifications following their reactivation. Processes of memory consolidation and reactivation-induced skill modulation have been commonly documented after hours or days. Motivated by studies showing rapid consolidation in early stages of motor skill acquisition, here we asked whether motor skill memories are susceptible to modifications following brief reactivations, even at initial stages of learning. In a set of experiments, we collected crowdsourced online motor sequence data to test whether post-encoding interference and performance enhancement occur following brief reactivations in early stages of learning. Results indicate that memories forming during early learning are not susceptible to interference nor to enhancement within a rapid reactivation-induced time window, relative to control conditions. This set of evidence suggests that reactivation-induced motor skill memory modulation might be dependent on consolidation at the macro-timescale level, requiring hours or days to occur.

OBJECTIVE:To investigate the neuronal elements involved in the activation of corticospinal neurons in the primary motor cortex (M1). METHODS:We studied 10 healthy subjects. Cortical evoked potentials with different components induced by monophasic transcranial magnetic stimulation (TMS) in anterior-posterior and posterior-anterior currents recorded with electroencephalography (EEG) were analyzed. RESULTS:EEG signatures with P25 and N45 components recorded at the C3 electrode with posterior-anterior current were larger than those with anterior-posterior current, while the signatures with P180 and N280 components recorded at the FC1 electrode with anterior-posterior current were larger than those with posterior-anterior current. The source localization analysis revealed that the cortical evoked potential with anterior-posterior current distributed both in the M1 and premotor cortex while that with posterior-anterior current only located in the M1. CONCLUSIONS:We conclude that the activation of corticospinal pyramidal neurons in the M1 is affected by various neuronal elements including the local intracortical circuits in the M1 and inputs from premotor cortex with different sensitivities to TMS in opposite current directions. SIGNIFICANCE:Our finding helped answer a longstanding question about how the corticospinal pathway from the M1 is functionally organized and activated.

Neuroplasticity follows nervous system injury in the presence or absence of rehabilitative treatments. Rehabilitative interventions can be used to modulate adaptive neuroplasticity, reducing motor impairment and improving activities of daily living in patients with brain lesions. Learning principles guide some rehabilitative interventions. While basic science research has shown that reward combined with training enhances learning, this principle has been only recently explored in the context of neurorehabilitation. Commonly used reinforcers may be more or less rewarding depending on the individual or the context in which the task is performed. Studies in healthy humans showed that both reward and punishment can enhance within-session motor performance; but reward, and not punishment, improves consolidation and retention of motor skills. On the other hand, neurorehabilitative training after brain lesions involves complex tasks (e.g., walking and activities of daily living). The contribution of reward to neurorehabilitation is incompletely understood. Here, we discuss recent research on the role of reward in neurorehabilitation and the needed directions of future research.