Skill learning strengthens cortical representations of motor sequences

C-SMB 2.0: Integrating over 25 years of motor sequencing research with the Discrete Sequence Production task

An exhaustive review is reported of over 25 years of research with the Discrete Sequence Production (DSP) task as reported in well over 100 articles. In line with the increasing call for theory development, this culminates into proposing the second version of the Cognitive framework of Sequential Motor Behavior (C-SMB 2.0), which brings together known models from cognitive psychology, cognitive neuroscience, and motor learning. This processing framework accounts for the many different behavioral results obtained with the DSP task and unveils important properties of the cognitive system. C-SMB 2.0 assumes that a versatile central processor (CP) develops multimodal, central-symbolic representations of short motor segments by repeatedly storing the elements of these segments in short-term memory (STM). Independently, the repeated processing by modality-specific perceptual and motor processors (PPs and MPs) and by the CP when executing sequences gradually associates successively used representations at each processing level. The high dependency of these representations on active context information allows for the rapid serial activation of the sequence elements as well as for the executive control of tasks as a whole. Speculations are eventually offered as to how the various cognitive processes could plausibly find their neural underpinnings within the intricate networks of the brain.

Hemispheric divergence of interoceptive processing across psychiatric disorders

Interactions between top-down attention and bottom-up visceral inputs are assumed to produce conscious perceptions of interoceptive states, and while each process has been independently associated with aberrant interoceptive symptomatology in psychiatric disorders, the neural substrates of this interface are unknown. We conducted a preregistered functional neuroimaging study of 46 individuals with anxiety, depression, and/or eating disorders (ADE) and 46 propensity-matched healthy comparisons (HC), comparing their neural activity across two interoceptive tasks differentially recruiting top-down or bottom-up processing within the same scan session. During an interoceptive attention task, top-down attention was voluntarily directed towards cardiorespiratory or visual signals, whereas during an interoceptive perturbation task, intravenous infusions of isoproterenol (a peripherally-acting beta-adrenergic receptor agonist) were administered in a double-blinded and placebo-controlled fashion to drive bottom-up cardiorespiratory sensations. Across both tasks, neural activation converged upon the insular cortex, localizing within the granular and ventral dysgranular subregions bilaterally. However, contrasting hemispheric differences emerged, with the ADE group exhibiting (relative to HCs) an asymmetric pattern of overlap in the left insula, with increased or decreased proportions of co-activated voxels within the left or right dysgranular insula, respectively. The ADE group also showed less agranular anterior insula activation during periods of bodily uncertainty (i.e., when anticipating possible isoproterenol-induced changes that never arrived). Finally, post-task changes in insula functional connectivity were associated with anxiety and depression severity. These findings confirm the dysgranular mid-insula as a key cortical interface where attention and prediction meet real-time bodily inputs, especially during heightened awareness of interoceptive states. Further, the dysgranular mid-insula may indeed be a "locus of disruption" for psychiatric disorders.

Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training

Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.

A theory of the skill-performance relationship

The skill-performance relationship is a cornerstone of a meritocratic society. People are selected for schools, colleges and jobs based on the premise that more skillful individuals perform better. Scientific understanding of the skill-performance relationship demands that the effect of skill on performance is objectively assessed without subjective, social, and political considerations. One of the best areas for this analysis is sports. In many sports settings, the skill-performance relationship can objectively be examined at the technical, behavioral, psychological, and neurological levels. This examination reveals that skill and performance are inextricably intertwined. While skill affects performance, performance in turn defines and affects skill. To disentangle the previously confusing and interchangeable use of these key constructs, the paper presents a theoretical model specifying that ability and effort have their own direct effects on performance, as well as indirect effects on performance through skill possession and skill execution in cognitive and physical domains of human performance. Thus, ability and skill are not the same. Although skill is a key determinant of performance, recent theory and research suggests that successful performers are successful not just because of their skills per se, but because they take advantage of their skills by creating more occurrences of momentum, making them last longer, and using them to bounce back faster from streaks of unsuccessful performance. Thus, momentum is an important mediator of the effects of skill on performance.

Knowns and unknowns about the neurobiology of stuttering

Stuttering occurs in early childhood during a dynamic phase of brain and behavioral development. The latest studies examining children at ages close to this critical developmental period have identified early brain alterations that are most likely linked to stuttering, while spontaneous recovery appears related to increased inter-area connectivity. By contrast, therapy-driven improvement in adults is associated with a functional reorganization within and beyond the speech network. The etiology of stuttering, however, remains enigmatic. This Unsolved Mystery highlights critical questions and points to neuroimaging findings that could inspire future research to uncover how genetics, interacting neural hierarchies, social context, and reward circuitry contribute to the many facets of stuttering.

Neural correlates of fine motor grasping skills: Longitudinal insights into motor cortex activation using fNIRS

BACKGROUND

Motor learning is essential for performing specific tasks and progresses through distinct stages, including the rapid learning phase (initial skill acquisition), the consolidation phase (skill refinement), and the stable performance phase (skill mastery and maintenance). Understanding the cortical activation dynamics during these stages can guide targeted rehabilitation interventions.

METHODS

In this longitudinal randomized controlled trial, functional near-infrared spectroscopy was used to explore the temporal dynamics of cortical activation in hand-related motor learning. Thirty-one healthy right-handed individuals were randomly assigned to perform either easy or intricate motor tasks with their non-dominant hand over 10 days. We conducted 10 monitoring sessions to track cortical activation in the right hemisphere (according to lateralization principles, the primary hemisphere for motor control) and evaluated motor proficiency concurrently.

RESULTS

The study delineated three stages of nondominant hand motor learning: rapid learning (days 1 and 2), consolidation (days 3-7), and stable performance (days 8-10). There was a power-law enhancement of motor skills correlated with learning progression. Sustained activation was observed in the supplementary motor area (SMA) and parietal lobe (PL), whereas activation in the right primary motor cortex (M1R) and dorsolateral prefrontal cortex (PFCR) decreased. These cortical activation patterns exhibited a high correlation with the augmentation of motor proficiency.

CONCLUSIONS

The findings suggest that early rehabilitation interventions, such as transcranial magnetic stimulation and transcranial direct current stimulation (tDCS), could be optimally directed at M1 and PFC in the initial stages. In contrast, SMA and PL can be targeted throughout the motor learning process. This research illuminates the path for developing tailored motor rehabilitation interventions based on specific stages of motor learning.

NEW AND NOTEWORTHY

In an innovative approach, our study uniquely combines a longitudinal design with the robustness of generalized estimating equations (GEEs). With the synergy of functional near-infrared spectroscopy (fNIRS) and the Minnesota Manual Dexterity Test (MMDT) paradigm, we precisely trace the evolution of neural resources during complex, real-world fine-motor task learning. Centering on right-handed participants using their nondominant hand magnifies the intricacies of right hemisphere spatial motor processing. We unravel the brain's dynamic response throughout motor learning stages and its potent link to motor skill enhancement. Significantly, our data point toward the early-phase rehabilitation potential of TMS and transcranial direct current stimulation on the M1 and PFC regions. Concurrently, SMA and PL appear poised to benefit from ongoing interventions during the entire learning curve. Our findings carve a path for refined motor rehabilitation strategies, underscoring the importance of timely noninvasive brain stimulation treatments.

Stable Cortical Body Maps Before and After Arm Amputation

Neuroscientists have long debated the adult brain's capacity to reorganize itself in response to injury. A driving model for studying plasticity has been limb amputation. For decades, it was believed that amputation triggers large-scale reorganization of cortical body resources. However, these studies have relied on cross-sectional observations post-amputation, without directly tracking neural changes. Here, we longitudinally followed adult patients with planned arm amputations and measured hand and face representations, before and after amputation. By interrogating the representational structure elicited from movements of the hand (pre-amputation) and phantom hand (post-amputation), we demonstrate that hand representation is unaltered. Further, we observed no evidence for lower face (lip) reorganization into the deprived hand region. Collectively, our findings provide direct and decisive evidence that amputation does not trigger large-scale cortical reorganization.

Cortical circuit dynamics underlying motor skill learning: from rodents to humans

Motor learning is crucial for the survival of many animals. Acquiring a new motor skill involves complex alterations in both local neural circuits in many brain regions and long-range connections between them. Such changes can be observed anatomically and functionally. The primary motor cortex (M1) integrates information from diverse brain regions and plays a pivotal role in the acquisition and refinement of new motor skills. In this review, we discuss how motor learning affects the M1 at synaptic, cellular, and circuit levels. Wherever applicable, we attempt to relate and compare findings in humans, non-human primates, and rodents. Understanding the underlying principles shared by different species will deepen our understanding of the neurobiological and computational basis of motor learning.

Performing a vibrotactile discrimination task modulates finger representations in primary somatosensory cortex

It is well established that vibrotactile stimuli are represented in somatotopic maps. However, less is known about whether these somatotopic representations are modulated by task demands and maybe even in the absence of tactile input. Here, we used a vibrotactile discrimination task as a tool to investigate these questions in further detail. Participants were required to actively perceive and process tactile stimuli in comparison to a no-task control condition where identical stimuli were passively perceived (no-memory condition). Importantly, both vibrotactile stimuli were either applied to the right index or little finger, allowing us to investigate whether cognitive task demands shape finger representations in primary somatosensory cortex (S1). Using multivoxel pattern analysis and representational similarity analysis, we found that S1 finger representations were more distinct during the memory than the no-memory condition. Interestingly, this effect was not only observed while tactile stimuli were presented but also during the delay period (i.e., in the absence of tactile stimulation). Our findings imply that when individuals are required to focus on tactile stimuli, retain them in their memory, and engage in active processing of distinctive stimulus features, this exerts a modulatory effect on the finger representations present in S1.NEW & NOTEWORTHY Using multivoxel pattern analysis, we found that discrimination task demands shape finger representations in the contralateral primary somatosensory cortex (S1), and that somatotopic representations are modulated by task demands not only during tactile stimulation but also to a certain extent in the absence of tactile input.

Dissociating the contributions of sensorimotor striatum to automatic and visually guided motor sequences

The ability to sequence movements in response to new task demands enables rich and adaptive behavior. However, such flexibility is computationally costly and can result in halting performances. Practicing the same motor sequence repeatedly can render its execution precise, fast and effortless, that is, 'automatic'. The basal ganglia are thought to underlie both types of sequence execution, yet whether and how their contributions differ is unclear. We parse this in rats trained to perform the same motor sequence instructed by cues and in a self-initiated overtrained, or 'automatic,' condition. Neural recordings in the sensorimotor striatum revealed a kinematic code independent of the execution mode. Although lesions reduced the movement speed and affected detailed kinematics similarly, they disrupted high-level sequence structure for automatic, but not visually guided, behaviors. These results suggest that the basal ganglia are essential for 'automatic' motor skills that are defined in terms of continuous kinematics, but can be dispensable for discrete motor sequences guided by sensory cues.

Reassessing referral of touch following peripheral deafferentation: The role of contextual bias

Some amputees have been famously reported to perceive facial touch as arising from their phantom hand. These referred sensations have since been replicated across multiple neurological disorders and were classically interpreted as a perceptual correlate of cortical plasticity. Common to all these and related studies is that participants might have been influenced in their self-reports by the experimental design or related contextual biases. Here, we investigated whether referred sensations reports might be confounded by demand characteristics (e.g., compliance, expectation, suggestion). Unilateral upper-limb amputees (N = 18), congenital one-handers (N = 19), and two-handers (N = 22) were repeatedly stimulated with computer-controlled vibrations on 10 body-parts and asked to report the occurrence of any concurrent sensations on their hand(s). To further manipulate expectations, we gave participants the suggestion that some of these vibrations had a higher probability to evoke referred sensations. We also assessed similarity between (phantom) hand and face representation in primary somatosensory cortex (S1), using functional Magnetic Resonance Imaging (fMRI) multivariate representational similarity analysis. We replicated robust reports of referred sensations in amputees towards their phantom hand; however, the frequency and distribution of reported referred sensations were similar across groups. Moreover, referred sensations were evoked by stimulation of multiple body-parts and similarly reported on both the intact and phantom hand in amputees. Face-to-phantom-hand representational similarity was not different in amputees' missing hand region, compared with controls. These findings weaken the interpretation of referred sensations as a perceptual correlate of S1 plasticity and reveal the need to account for contextual biases when evaluating anomalous perceptual phenomena.

Motor cortex is required for flexible but not automatic motor sequences

How motor cortex contributes to motor sequence execution is much debated, with studies supporting disparate views. Here we probe the degree to which motor cortex's engagement depends on task demands, specifically whether its role differs for highly practiced, or 'automatic', sequences versus flexible sequences informed by external events. To test this, we trained rats to generate three-element motor sequences either by overtraining them on a single sequence or by having them follow instructive visual cues. Lesioning motor cortex revealed that it is necessary for flexible cue-driven motor sequences but dispensable for single automatic behaviors trained in isolation. However, when an automatic motor sequence was practiced alongside the flexible task, it became motor cortex-dependent, suggesting that subcortical consolidation of an automatic motor sequence is delayed or prevented when the same sequence is produced also in a flexible context. A simple neural network model recapitulated these results and explained the underlying circuit mechanisms. Our results critically delineate the role of motor cortex in motor sequence execution, describing the condition under which it is engaged and the functions it fulfills, thus reconciling seemingly conflicting views about motor cortex's role in motor sequence generation.

A randomized controlled trial of changes in resting-state functional connectivity associated with short-term motor learning of chopstick use with the non-dominant hand

INTRODUCTION

This study identified the offline brain networks associated with motor learning of non-dominant hand chopstick use within-session.

METHODS

40 healthy right-handed adults were randomly assigned to the practice and control groups (20 each). The performance, resting-state functional connectivity (RSFC), and their correlation were compared within and between groups. Both groups repeated 9 cycles of 30 s task and rest. During the task, the practice group performed the chopstick-use practice with their left hand, while the control group held chopsticks without acquiring any skills. During the rest, both groups fixated their gaze on a fixation point. The number of times candies were moved using chopsticks with the left hand in 30 s was used to evaluate the performance. RSFC was obtained by resting-state fMRI scanning and extracting Z-scores between the right primary motor cortex and all other brain regions.

RESULTS

Both the groups improved in the post-task performance; the practice group improved more. The RSFC of the two networks increased in the practice group. One network was the RSFC between the right M1 and the right cerebellar Crus I, positively correlated with performance in the post-task. Another was the RSFC between the right M1 and the left cerebellar Crus II, positively correlated with skills in the amount of change pre- and post-task.

CONCLUSION

Offline enhancement of RSFC in these networks was shown to contribute to early chopstick-use motor learning with the left hand. These results serve as a basis for future studies on compensatory networks in individuals with stroke.

Self-supervised pretraining improves the performance of classification of task functional magnetic resonance imaging

Introduction

Decoding brain activities is one of the most popular topics in neuroscience in recent years. And deep learning has shown high performance in fMRI data classification and regression, but its requirement for large amounts of data conflicts with the high cost of acquiring fMRI data.

Methods

In this study, we propose an end-to-end temporal contrastive self-supervised learning algorithm, which learns internal spatiotemporal patterns within fMRI and allows the model to transfer learning to datasets of small size. For a given fMRI signal, we segmented it into three sections: the beginning, middle, and end. We then utilized contrastive learning by taking the end-middle (i.e., neighboring) pair as the positive pair, and the beginning-end (i.e., distant) pair as the negative pair.

Results

We pretrained the model on 5 out of 7 tasks from the Human Connectome Project (HCP) and applied it in a downstream classification of the remaining two tasks. The pretrained model converged on data from 12 subjects, while a randomly initialized model required 100 subjects. We then transferred the pretrained model to a dataset containing unpreprocessed whole-brain fMRI from 30 participants, achieving an accuracy of 80.2 ± 4.7%, while the randomly initialized model failed to converge. We further validated the model's performance on the Multiple Domain Task Dataset (MDTB), which contains fMRI data of 26 tasks from 24 participants. Thirteen tasks of fMRI were selected as inputs, and the results showed that the pre-trained model succeeded in classifying 11 of the 13 tasks. When using the 7 brain networks as input, variations of the performance were observed, with the visual network performed as well as whole brain inputs, while the limbic network almost failed in all 13 tasks.

Discussion

Our results demonstrated the potential of self-supervised learning for fMRI analysis with small datasets and unpreprocessed data, and for analysis of the correlation between regional fMRI activity and cognitive tasks.

Cortico-cortical paired associative stimulation (ccPAS) over premotor-motor areas affects local circuitries in the human motor cortex via Hebbian plasticity

Transcranial magnetic stimulation (TMS) studies have shown that cortico-cortical paired associative stimulation (ccPAS) can strengthen connectivity between the ventral premotor cortex (PMv) and the primary motor cortex (M1) by modulating convergent input over M1 via Hebbian spike-timing-dependent plasticity (STDP). However, whether ccPAS locally affects M1 activity remains unclear. We tested 60 right-handed young healthy humans in two studies, using a combination of dual coil TMS and ccPAS over the left PMv and M1 to probe and manipulate PMv-to-M1 connectivity, and single- and paired-pulse TMS to assess neural activity within M1. We provide convergent evidence that ccPAS, relying on repeated activations of excitatory PMv-to-M1 connections, acts locally over M1. During ccPAS, motor-evoked potentials (MEPs) induced by paired PMv-M1 stimulation gradually increased. Following ccPAS, the threshold for inducing MEPs of different amplitudes decreased, and the input-output curve (IO) slope increased, highlighting increased M1 corticospinal excitability. Moreover, ccPAS reduced the magnitude of short-interval intracortical inhibition (SICI), reflecting suppression of GABA-ergic interneuronal mechanisms within M1, without affecting intracortical facilitation (ICF). These changes were specific to ccPAS Hebbian strengthening of PMv-to-M1 connectivity, as no modulations were observed when reversing the order of the PMv-M1 stimulation during a control ccPAS protocol. These findings expand prior ccPAS research that focused on the malleability of cortico-cortical connectivity at the network-level, and highlight local changes in the area of convergent activation (i.e., M1) during plasticity induction. These findings provide new mechanistic insights into the physiological basis of ccPAS that are relevant for protocol optimization.

Visual perceptual load and processing of somatosensory stimuli in primary and secondary somatosensory cortices

Load theory assumes that neural activation to distractors in early sensory cortices is modulated by the perceptual load of a main task, regardless of whether task and distractor share the same sensory modality or not. While several studies have investigated the question of load effects on distractor processing in early sensory areas, there is no functional magnetic resonance imaging (fMRI) study regarding load effects on somatosensory stimuli. Here, we used fMRI to investigate effects of visual perceptual load on neural responses to somatosensory stimuli applied to the wrist in a study with 44 participants. Perceptual load was manipulated by an established sustained visual detection task, which avoided simultaneous target and distractor presentations. Load was operationalized by detection difficulty of subtle or clear color changes of one of 12 rotating dots. While all somatosensory stimuli led to activation in somatosensory areas SI and SII, we found no statistically significant difference in brain activation to these stimuli under high compared to low sustained visual load. Moreover, exploratory Bayesian analyses supported the absence of differences. Thus, our findings suggest a resistance of somatosensory processing to at least some forms of visual perceptual load, possibly due to behavioural relevance of discrete somatosensory stimuli and separable attentional resources for the somatosensory and visual modality.

Cortical Patterns Shift from Sequence Feature Separation during Planning to Integration during Motor Execution

Performing sequences of movements from memory and adapting them to changing task demands is a hallmark of skilled human behavior, from handwriting to playing a musical instrument. Prior studies showed a fine-grained tuning of cortical primary motor, premotor, and parietal regions to motor sequences: from the low-level specification of individual movements to high-level sequence features, such as sequence order and timing. However, it is not known how tuning in these regions unfolds dynamically across planning and execution. To address this, we trained 24 healthy right-handed human participants (14 females, 10 males) to produce four five-element finger press sequences with a particular finger order and timing structure in a delayed sequence production paradigm entirely from memory. Local cortical fMRI patterns during preparation and production phases were extracted from separate No-Go and Go trials, respectively, to tease out activity related to these perimovement phases. During sequence planning, premotor and parietal areas increased tuning to movement order or timing, regardless of their combinations. In contrast, patterns reflecting the unique integration of sequence features emerged in these regions during execution only, alongside timing-specific tuning in the ventral premotor, supplementary motor, and superior parietal areas. This was in line with the participants' behavioral transfer of trained timing, but not of order to new sequence feature combinations. Our findings suggest a general informational state shift from high-level feature separation to low-level feature integration within cortical regions for movement execution. Recompiling sequence features trial-by-trial during planning may enable flexible last-minute adjustment before movement initiation.SIGNIFICANCE STATEMENT Musicians and athletes can modify the timing and order of movements in a sequence trial-by-trial, allowing for a vast repertoire of flexible behaviors. How does the brain put together these high-level sequence features into an integrated whole? We found that, trial-by-trial, the control of sequence features undergoes a state shift from separation during planning to integration during execution across a network of motor-related cortical areas. These findings have implications for understanding the hierarchical control of skilled movement sequences, as well as how information in brain areas unfolds across planning and execution.

To copy or not to copy? That is the question! From chimpanzees to the foundation of human technological culture

A prerequisite for copying innovative behaviour faithfully is the capacity of observers' brains, regarded as 'hierarchically mechanistic minds', to overcome cognitive 'surprisal' (see 2.), by maximising the evidence for their internal models, through active inference. Unlike modern humans, chimpanzees and other great apes show considerable limitations in their ability, or 'Zone of Bounded Surprisal', to overcome cognitive surprisal induced by innovative or unorthodox behaviour that rarely, therefore, is copied precisely or accurately. Most can copy adequately what is within their phenotypically habitual behavioural repertoire, in which technology plays scant part. Widespread intra- and intergenerational social transmission of complex technological innovations is not a hall-mark of great-ape taxa. 3 Ma, precursors of the genus Homo made stone artefacts, and stone-flaking likely was habitual before 2 Ma. After that time, early Homo erectus has left traces of technological innovations, though faithful copying of these and their intra- and intergenerational social transmission were rare before 1 Ma. This likely owed to a cerebral infrastructure of interconnected neuronal systems more limited than ours. Brains were smaller in size than ours, and cerebral neuronal systems ceased to develop when early Homo erectus attained full adult maturity by the mid-teen years, whereas its development continues until our mid-twenties nowadays. Pleistocene Homo underwent remarkable evolutionary adaptation of neurobiological propensities, and cerebral aspects are discussed that, it is proposed here, plausibly, were fundamental for faithful copying, which underpinned social transmission of technologies, cumulative learning, and culture. Here, observers' responses to an innovation are more important for ensuring its transmission than is an innovator's production of it, because, by themselves, the minimal cognitive prerequisites that are needed for encoding and assimilating innovations are insufficient for practical outcomes to accumulate and spread intra- and intergenerationally.

Complex pattern of facial remapping in somatosensory cortex following congenital but not acquired hand loss

Cortical remapping after hand loss in the primary somatosensory cortex (S1) is thought to be predominantly dictated by cortical proximity, with adjacent body parts remapping into the deprived area. Traditionally, this remapping has been characterised by changes in the lip representation, which is assumed to be the immediate neighbour of the hand based on electrophysiological research in non-human primates. However, the orientation of facial somatotopy in humans is debated, with contrasting work reporting both an inverted and upright topography. We aimed to fill this gap in the S1 homunculus by investigating the topographic organisation of the face. Using both univariate and multivariate approaches we examined the extent of face-to-hand remapping in individuals with a congenital and acquired missing hand (hereafter one-handers and amputees, respectively), relative to two-handed controls. Participants were asked to move different facial parts (forehead, nose, lips, tongue) during functional MRI (fMRI) scanning. We first confirmed an upright face organisation in all three groups, with the upper-face and not the lips bordering the hand area. We further found little evidence for remapping of both forehead and lips in amputees, with no significant relationship to the chronicity of their phantom limb pain (PLP). In contrast, we found converging evidence for a complex pattern of face remapping in congenital one-handers across multiple facial parts, where relative to controls, the location of the cortical neighbour - the forehead - is shown to shift away from the deprived hand area, which is subsequently more activated by the lips and the tongue. Together, our findings demonstrate that the face representation in humans is highly plastic, but that this plasticity is restricted by the developmental stage of input deprivation, rather than cortical proximity.

A Method for Estimating Longitudinal Change in Motor Skill from Individualized Functional-Connectivity Measures

Pragmatic, objective, and accurate motor assessment tools could facilitate more frequent appraisal of longitudinal change in motor function and subsequent development of personalized therapeutic strategies. Brain functional connectivity (FC) has shown promise as an objective neurophysiological measure for this purpose. The involvement of different brain networks, along with differences across subjects due to age or existing capabilities, motivates an individualized approach towards the evaluation of FC. We advocate the use of EEG-based resting-state FC (rsFC) measures to address the pragmatic requirements. Pertaining to appraisal of accuracy, we suggest using the acquisition of motor skill by healthy individuals that could be quantified at small incremental change. Computer-based tracing tasks are a good candidate in this regard when using spatial error in tracing as an objective measure of skill. This work investigates the application of an individualized method that utilizes Partial Least Squares analysis to estimate the longitudinal change in tracing error from changes in rsFC. Longitudinal data from participants yielded an average accuracy of 98% (standard deviation of 1.2%) in estimating tracing error. The results show potential for an accurate individualized motor assessment tool that reduces the dependence on the expertise and availability of trained examiners, thereby facilitating more frequent appraisal of function and development of personalized training programs.

Memory decay and generalization following distinct motor learning mechanisms

Motor skill learning is considered to arise out of contributions from multiple learning mechanisms, including error-based learning (EBL), use-dependent learning (UDL), and reinforcement learning (RL). These learning mechanisms exhibit dissociable roles and engage different neural circuits during skill acquisition. However, it remains largely unknown how a newly formed motor memory acquired through each learning mechanism decays over time and whether distinct learning mechanisms produce different generalization patterns. Here, we used variants of reaching paradigms that dissociated these learning mechanisms to examine the time course of memory decay following each learning and the generalization patterns of each learning. We found that motor memories acquired through these learning mechanisms decayed as a function of time. Notably, 15 min, 6 h, and 24 h after acquisition, the memory of EBL decayed much greater than that of RL. The memory acquired through UDL faded away within a few minutes. Motor memories formed through EBL and RL for given movement directions generalized to untrained movement directions, with the generalization of EBL being greater than that of RL. In contrast, motor memory of UDL could not generalize to untrained movement directions. These results suggest that distinct learning mechanisms exhibit different patterns of memory decay and generalization.NEW & NOTEWORTHY Motor skill learning is likely to involve error-based learning, use-dependent plasticity, and operant reinforcement. Here, we showed that these dissociable learning mechanisms exhibited distinct patterns of memory decay and generalization. With a better understanding of the characteristics of these learning mechanisms, it becomes possible to regulate each learning process separately to improve neurological rehabilitation.

Learning-induced changes in the neural circuits underlying motor sequence execution

As the old adage goes: practice makes perfect. Yet, the neural mechanisms by which rote repetition transforms a halting behavior into a fluid, effortless, and "automatic" action are not well understood. Here we consider the possibility that well-practiced motor sequences, which initially rely on higher-level decision-making circuits, become wholly specified in lower-level control circuits. We review studies informing this idea, discuss the constraints on such shift in control, and suggest approaches to pinpoint circuit-level changes associated with motor sequence learning.

Hierarchical Reinforcement Learning, Sequential Behavior, and the Dorsal Frontostriatal System

To effectively behave within ever-changing environments, biological agents must learn and act at varying hierarchical levels such that a complex task may be broken down into more tractable subtasks. Hierarchical reinforcement learning (HRL) is a computational framework that provides an understanding of this process by combining sequential actions into one temporally extended unit called an option. However, there are still open questions within the HRL framework, including how options are formed and how HRL mechanisms might be realized within the brain. In this review, we propose that the existing human motor sequence literature can aid in understanding both of these questions. We give specific emphasis to visuomotor sequence learning tasks such as the discrete sequence production task and the M × N (M steps × N sets) task to understand how hierarchical learning and behavior manifest across sequential action tasks as well as how the dorsal cortical-subcortical circuitry could support this kind of behavior. This review highlights how motor chunks within a motor sequence can function as HRL options. Furthermore, we aim to merge findings from motor sequence literature with reinforcement learning perspectives to inform experimental design in each respective subfield.

Neural circuit mechanisms of hierarchical sequence learning tested on large-scale recording data

The brain performs various cognitive functions by learning the spatiotemporal salient features of the environment. This learning requires unsupervised segmentation of hierarchically organized spike sequences, but the underlying neural mechanism is only poorly understood. Here, we show that a recurrent gated network of neurons with dendrites can efficiently solve difficult segmentation tasks. In this model, multiplicative recurrent connections learn a context-dependent gating of dendro-somatic information transfers to minimize error in the prediction of somatic responses by the dendrites. Consequently, these connections filter the redundant input features represented by the dendrites but unnecessary in the given context. The model was tested on both synthetic and real neural data. In particular, the model was successful for segmenting multiple cell assemblies repeating in large-scale calcium imaging data containing thousands of cortical neurons. Our results suggest that recurrent gating of dendro-somatic signal transfers is crucial for cortical learning of context-dependent segmentation tasks.

A conceptual model for clinical psychomotor skill development in an era of simulated and virtual reality

Psychomotor skill development is central to a beginner practitioner's learning pathway. Curriculum constraints around time, access to facilities and resources in health professions education have prompted the growth in alternative approaches to clinical skill development in both simulation and direct patient care. Among these is the increased incorporation of virtual reality (VR) systems with haptic feedback alongside traditional, solid simulations. Given the rapid growth in the adoption of technological affordances to support skill development, it is cogent to pause and examine whether the underpinning concepts regarding psychomotor skill development that have driven much of the approaches to teach clinical skill acquisition in dentistry remain fit-for-purpose. This conceptual paper proposes a new taxonomy for clinical simulation psychomotor skill development in the era of increasing variety of simulation modalities.

The role of feedback in the production of skilled finger sequences

Actions involving fine control of the hand, for example, grasping an object, rely heavily on sensory information from the fingertips. Although the integration of feedback during the execution of individual movements is well understood, less is known about the use of sensory feedback in the control of skilled movement sequences. To address this gap, we trained participants to produce sequences of finger movements on a keyboard-like device over a 4-day training period. Participants received haptic, visual, and auditory feedback indicating the occurrence of each finger press. We then either transiently delayed or advanced the feedback for a single press by a small amount of time (30 or 60 ms). We observed that participants rapidly adjusted their ongoing finger press by either accelerating or prolonging the ongoing press, in accordance with the direction of the perturbation. Furthermore, we could show that this rapid behavioral modulation was driven by haptic feedback. Although these feedback-driven adjustments reduced in size with practice, they were still clearly present at the end of training. In contrast to the directionally specific effect we observed on the perturbed press, a feedback perturbation resulted in a delayed onset of the subsequent presses irrespective of perturbation direction or feedback modality. This observation is consistent with a hierarchical organization of even very skilled and fast movement sequences, with different levels reacting distinctly to sensory perturbations.NEW & NOTEWORTHY Sensory feedback is important during the execution of a movement. However, little is known about how sensory feedback is used during the production of movement sequences. Here, we show two distinct feedback processes in the execution of fast finger movement sequences. By transiently delaying or advancing the feedback of a single press within a sequence, we observed a directionally specific effect on the perturbed press and a directionally non-specific effect on the subsequent presses.

Beyond body maps: Information content of specific body parts is distributed across the somatosensory homunculus

The homunculus in primary somatosensory cortex (S1) is famous for its body part selectivity, but this dominant feature may eclipse other representational features, e.g., information content, also relevant for S1 organization. Using multivariate fMRI analysis, we ask whether body part information content can be identified in S1 beyond its primary region. Throughout S1, we identify significant representational dissimilarities between body parts but also subparts in distant non-primary regions (e.g., between the hand and the lips in the foot region and between different face parts in the foot region). Two movements performed by one body part (e.g., the hand) could also be dissociated well beyond its primary region (e.g., in the foot and face regions), even within Brodmann area 3b. Our results demonstrate that information content is more distributed across S1 than selectivity maps suggest. This finding reveals underlying information contents in S1 that could be harnessed for rehabilitation and brain-machine interfaces.

Brain Activity and Functional Connectivity Patterns Associated With Fast and Slow Motor Sequence Learning in Late Middle Adulthood

The human brain undergoes structural and functional changes across the lifespan. The study of motor sequence learning in elderly subjects is of particularly interest since previous findings in young adults might not replicate during later stages of adulthood. The present functional magnetic resonance imaging (fMRI) study assessed the performance, brain activity and functional connectivity patterns associated with motor sequence learning in late middle adulthood. For this purpose, a total of 25 subjects were evaluated during early stages of learning [i.e., fast learning (FL)]. A subset of these subjects (n = 11) was evaluated after extensive practice of a motor sequence [i.e., slow learning (SL) phase]. As expected, late middle adults improved motor performance from FL to SL. Learning-related brain activity patterns replicated most of the findings reported previously in young subjects except for the lack of hippocampal activity during FL and the involvement of cerebellum during SL. Regarding functional connectivity, precuneus and sensorimotor lobule VI of the cerebellum showed a central role during improvement of novel motor performance. In the sample of subjects evaluated, connectivity between the posterior putamen and parietal and frontal regions was significantly decreased with aging during SL. This age-related connectivity pattern may reflect losses in network efficiency when approaching late adulthood. Altogether, these results may have important applications, for instance, in motor rehabilitation programs.

Motor sequences; separating the sequence from the motor. A longitudinal rsfMRI study

In motor learning, sequence specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific decreases in functional connectivity during overall learning in the right supplementary motor area (SMA). We found that connectivity changes in a key region of the motor network, the superior parietal cortex (SPC) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA that has previously been identified in online task-based learning studies, and extends it to resting state network changes after sequence-specific MSL.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

Performance in Hand Coordination Tasks and Concurrent Functional MRI Findings in 13-Year-Olds Born Very Preterm

BACKGROUND

Fine motor and coordination problems are frequently reported among adolescents born preterm. We aimed to assess performance in hand coordination tasks and to compare concurrent brain activation between adolescents born very preterm and at term at 13 years.

METHODS

A total of 34 right-handed adolescents born very preterm (gestational age less than 32 weeks/birth weight ≤1500 grams) and 37 controls born at term during 2003 to 2006 in Turku University Hospital, Finland, were recruited. At 13 years, finger opposition and diadochokinesis were assessed, and brain functional magnetic resonance imaging data were acquired while the adolescents performed unimanual hand coordination tasks in response to visual cue.

RESULTS

Adolescents born very preterm performed similar to controls in hand coordination tasks. The very preterm group evoked greater brain activation than the controls in the right precentral gyrus and in the right postcentral gyrus during left-hand finger opposition and in the right postcentral gyrus during left-hand diadochokinesis. Within the very preterm group, lower gestational age was associated with reduced activation in the left superior parietal lobule during right-hand diadochokinesis. Regarding left-hand tasks, lower gestational age was associated with stronger activation in the right cerebellar lobule V and left cerebellar lobule VI during finger opposition and stronger activation in the right superior parietal lobule during diadochokinesis.

CONCLUSIONS

Very preterm birth affected hand coordination-related brain activation. Most of the effects were found for nondominant hand. Clinical performance during the hand coordination tasks was similar in adolescents born very preterm and controls.

Combining Repetition Suppression and Pattern Analysis Provides New Insights into the Role of M1 and Parietal Areas in Skilled Sequential Actions

How does the brain change during learning? In functional magnetic resonance imaging (fMRI) studies, both multivariate pattern analysis (MVPA) and repetition suppression (RS) have been used to detect changes in neuronal representations. In the context of motor sequence learning, the two techniques have provided discrepant findings: pattern analysis showed that only premotor and parietal regions, but not primary motor cortex (M1), develop a representation of trained sequences. In contrast, RS suggested trained sequence representations in all these regions. Here, we applied both analysis techniques to a five-week finger sequence training study, in which participants executed each sequence twice before switching to a different sequence. Both RS and pattern analysis indicated learning-related changes for parietal areas, but only RS showed a difference between trained and untrained sequences in M1. A more fine-grained analysis, however, revealed that the RS effect in M1 reflects a fundamentally different process than in parietal areas. On the first execution, M1 represents especially the first finger of each sequence, likely reflecting preparatory processes. This effect dramatically reduces during the second execution. In contrast, parietal areas represent the identity of a sequence, and this representation stays relatively stable on the second execution. These results suggest that the RS effect does not reflect a trained sequence representation in M1, but rather a preparatory signal for movement initiation. More generally, our study demonstrates that across regions RS can reflect different representational changes in the neuronal population code, emphasizing the importance of combining pattern analysis and RS techniques.SIGNIFICANCE STATEMENT Previous studies using pattern analysis have suggested that primary motor cortex (M1) does not represent learnt sequential actions. However, a study using repetition suppression (RS) has reported M1 changes during motor sequence learning. Combining both techniques, we first replicate the discrepancy between them, with learning-related changes in M1 in RS, but not pattern dissimilarities. We further analyzed the representational changes with repetition, and found that the RS effects differ across regions. M1's activity represents the starting finger of the sequence, an effect that vanishes with repetition. In contrast, activity patterns in parietal areas exhibit sequence dependency, which persists with repetition. These results demonstrate the importance of combining RS and pattern analysis to understand the function of brain regions.

Linking Individual Movements to a Skilled Repertoire: Fast Modulation of Motor Synergies by Repetition of Stereotyped Movements

Motor skills emerge when practicing individual movements enables the motor system to extract building instructions that facilitate the generation of future diverse movements. Here we asked how practicing stereotyped movements for minutes affects motor synergies that encode human motor skills acquired over years of training. Participants trained a kinematically highly constrained combined index-finger and thumb movement. Before and after training, finger movements were evoked at rest by transcranial magnetic stimulation (TMS). Post-training, the angle between posture vectors describing TMS-evoked movements and the training movements temporarily decreased, suggesting the presence of a short-term memory for the trained movement. Principal component analysis was used to identify joint covariance patterns in TMS-evoked movements. The quality of reconstruction of training or grasping movements from linear combinations of a small subset of these TMS-derived synergies was used as an index of neural efficiency of movement generation. The reconstruction quality increased for the trained movement but remained constant for grasping movements. These findings suggest that the motor system rapidly reorganizes to enhance the coding efficiency of a difficult movement without compromising the coding efficiency of overlearned movements. Practice of individual movements may drive an unsupervised bottom-up process that ultimately shapes synergistic neuronal organization by constant competition of action memories.

Interleaving Motor Sequence Training With High-Frequency Repetitive Transcranial Magnetic Stimulation Facilitates Consolidation

The acquisition of novel motor skills is a fundamental process of lifelong learning and crucial for everyday behavior. Performance gains acquired by training undergo a transition from an initially labile state to a state that is progressively robust towards interference, a phenomenon referred to as motor consolidation. Previous work has demonstrated that the primary motor cortex (M1) is a neural key region for motor consolidation. However, it remains unknown whether physiological processes underlying posttraining motor consolidation in M1 are active already during an ongoing training phase or only after completion of the training. We examined whether 10-Hz interleaved repetitive transcranial magnetic stimulation (i-rTMS) of M1 during rest periods between active motor training in an explicit motor learning task affects posttraining offline consolidation. Relative to i-rTMS to the vertex (control region), i-rTMS to the M1_hand area of the nondominant hand facilitated posttraining consolidation assessed 6 h after training without affecting training performance. This facilitatory effect generalized to delayed performance of the mirror-symmetric sequence with the untrained (dominant) hand. These findings indicate that posttraining consolidation can be facilitated independently from training-induced performance increments and suggest that consolidation is initiated already during offline processing in short rest periods between active training phases.

Robotic hand augmentation drives changes in neural body representation

Humans have long been fascinated by the opportunities afforded through augmentation. This vision not only depends on technological innovations but also critically relies on our brain's ability to learn, adapt, and interface with augmentation devices. Here, we investigated whether successful motor augmentation with an extra robotic thumb can be achieved and what its implications are on the neural representation and function of the biological hand. Able-bodied participants were trained to use an extra robotic thumb (called the Third Thumb) over 5 days, including both lab-based and unstructured daily use. We challenged participants to complete normally bimanual tasks using only the augmented hand and examined their ability to develop hand-robot interactions. Participants were tested on a variety of behavioral and brain imaging tests, designed to interrogate the augmented hand's representation before and after the training. Training improved Third Thumb motor control, dexterity, and hand-robot coordination, even when cognitive load was increased or when vision was occluded. It also resulted in increased sense of embodiment over the Third Thumb. Consequently, augmentation influenced key aspects of hand representation and motor control. Third Thumb usage weakened natural kinematic synergies of the biological hand. Furthermore, brain decoding revealed a mild collapse of the augmented hand's motor representation after training, even while the Third Thumb was not worn. Together, our findings demonstrate that motor augmentation can be readily achieved, with potential for flexible use, reduced cognitive reliance, and increased sense of embodiment. Yet, augmentation may incur changes to the biological hand representation. Such neurocognitive consequences are crucial for successful implementation of future augmentation technologies.

Sequence learning recodes cortical representations instead of strengthening initial ones

We contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patterns from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations.

The Planning Horizon for Movement Sequences

When performing a long chain of actions in rapid sequence, future movements need to be planned concurrently with ongoing action. However, how far ahead we plan, and whether this ability improves with practice, is currently unknown. Here, we designed an experiment in which healthy volunteers produced sequences of 14 finger presses quickly and accurately on a keyboard in response to numerical stimuli. On every trial, participants were only shown a fixed number of stimuli ahead of the current keypress. The size of this viewing window varied between 1 (next digit revealed with the pressing of the current key) and 14 (full view of the sequence). Participants practiced the task for 5 days, and their performance was continuously assessed on random sequences. Our results indicate that participants used the available visual information to plan multiple actions into the future, but that the planning horizon was limited: receiving information about more than three movements ahead did not result in faster sequence production. Over the course of practice, we found larger performance improvements for larger viewing windows and an expansion of the planning horizon. These findings suggest that the ability to plan future responses during ongoing movement constitutes an important aspect of skillful movement. Based on the results, we propose a framework to investigate the neuronal processes underlying simultaneous planning and execution.

Watch and Learn: The Cognitive Neuroscience of Learning from Others' Actions

The mirror neuron system has dominated understanding of observational learning from a cognitive neuroscience perspective. Our review highlights the value of observational learning frameworks that integrate a more diverse and distributed set of cognitive and brain systems, including those implicated in sensorimotor transformations, as well as in more general processes such as executive control, reward, and social cognition. We argue that understanding how observational learning occurs in the real world will require neuroscientific frameworks that consider how visuomotor processes interface with more general aspects of cognition, as well as how learning context and action complexity shape mechanisms supporting learning from watching others.

Towards a common template for neural reinforcement of finger individuation

The inability to individuate finger movements is a common impairment following stroke. Conventional physical therapy ignores underlying neural changes with recovery, leaving it unclear why sensorimotor function often remains impaired. Functional MRI neurofeedback can monitor neural activity and reinforce it towards a healthy template to restore function. However, identifying an individualized training template may not be possible depending on the severity of impairment. In this study, we investigated the use of functional alignment of brain data across healthy participants to create an idealized neural template to be used as a training target for new participants. We employed multi-voxel pattern analyses to assess the prediction accuracy and robustness to missing data of pre-trained functional templates corresponding to individual finger presses. We found a significant improvement in classification accuracy (p < 0.001) of individual finger presses when group data was aligned based on function (88%) rather than anatomy (46%). Importantly, we found no significant drop in performance when aligning a new participant to a pre-established template as compared to including this new participant in the creation of a new template. These results indicate that functionally aligned templates could provide an effective surrogate training target for patients following neurological injury.

Encouraging an excitable brain state: mechanisms of brain repair in stroke

Stroke induces a plastic state in the brain. This period of enhanced plasticity leads to the sprouting of new axons, the formation of new synapses and the remapping of sensory-motor functions, and is associated with motor recovery. This is a remarkable process in the adult brain, which is normally constrained in its levels of neuronal plasticity and connectional change. Recent evidence indicates that these changes are driven by molecular systems that underlie learning and memory, such as changes in cellular excitability during memory formation. This Review examines circuit changes after stroke, the shared mechanisms between memory formation and brain repair, the changes in neuronal excitability that underlie stroke recovery, and the molecular and pharmacological interventions that follow from these findings to promote motor recovery in animal models. From these findings, a framework emerges for understanding recovery after stroke, central to which is the concept of neuronal allocation to damaged circuits. The translation of the concepts discussed here to recovery in humans is underway in clinical trials for stroke recovery drugs.

Altered Inferior Parietal Functional Connectivity is Correlated with Praxis and Social Skill Performance in Children with Autism Spectrum Disorder

Children with autism spectrum disorder (ASD) have difficulties perceiving and producing skilled gestures, or praxis. The inferior parietal lobule (IPL) is crucial to praxis acquisition and expression, yet how IPL connectivity contributes to autism-associated impairments in praxis as well as social-communicative skill remains unclear. Using resting-state functional magnetic resonance imaging, we applied independent component analysis to test how IPL connectivity relates to praxis and social-communicative skills in children with and without ASD. Across all children (with/without ASD), praxis positively correlated with connectivity of left posterior-IPL with the left dorsal premotor cortex and with the bilateral posterior/medial parietal cortex. Praxis also correlated with connectivity of right central-IPL connectivity with the left intraparietal sulcus and medial parietal lobe. Further, in children with ASD, poorer praxis and social-communicative skills both correlated with weaker right central-IPL connectivity with the left cerebellum, posterior cingulate, and right dorsal premotor cortex. Our findings suggest that IPL connectivity is linked to praxis development, that contributions arise bilaterally, and that right IPL connectivity is associated with impaired praxis and social-communicative skills in autism. The findings underscore the potential impact of IPL connectivity and impaired skill acquisition on the development of a range of social-communicative and motor functions during childhood, including autism-associated impairments.

Reward modulates cortical representations of action

People are capable of rapid improvements in performance when they are offered a reward. The neural mechanism by which this performance enhancement occurs remains unclear. We investigated this phenomenon by offering people monetary reward for successful performance in a sequence production task. We found that people performed actions more quickly and accurately when they were offered large reward. Increasing reward magnitude was associated with elevated activity throughout the brain prior to movement. Multivariate patterns of activity in these reward-responsive regions encoded information about the upcoming action. Follow-up analyses provided evidence that action decoding in pre-SMA and other motor planning areas was improved for large reward trials and successful action decoding in SMA was associated with improved performance. These results suggest that reward may enhance performance by enhancing neural representations of action used in motor planning.

Motor Learning Improves the Stability of Large-Scale Brain Connectivity Pattern

Repeated practice is fundamental to the acquisition of skills, which is typically accompanied by increasing reliability of neural representations that manifested as more stable activation patterns for the trained stimuli. However, large-scale neural pattern induced by learning has been rarely studied. Here, we investigated whether global connectivity patterns became more reliable as a result of motor learning using a novel analysis of the multivariate pattern of functional connectivity (MVPC). Human participants were trained with a finger-tapping motor task for five consecutive days and went through Functional magnetic resonance imaging (fMRI) scanning before and after training. We found that motor learning increased the whole-brain MVPC stability of the primary motor cortex (M1) when participants performed the trained sequence, while no similar effects were observed for the untrained sequence. Moreover, the increase of MVPC stability correlated with participants’ improvement in behavioral performance. These findings suggested that the acquisition of motor skills was supported by the increased connectivity pattern stability between the M1 and the rest of the brain. In summary, our study not only suggests global neural pattern stabilization as a neural signature for effective learning but also advocates applying the MVPC analysis to reveal mechanisms of distributed network reorganization supporting various types of learning.

Movement errors during skilled motor performance engage distinct prediction error mechanisms

The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes. Axiomatic to these computations are salience and valence prediction error signals, which alert the brain to the occurrence and value of unexpected events. Despite the theoretical assertion of these prediction error signals, it is unknown whether and how brain mechanisms underlying their computations support error processing during skilled motor behavior. Here we demonstrate, with functional magnetic resonance imaging, that internal detection, i.e., without externally-provided feedback, of self-generated movement errors evokes instantaneous activity increases within the salience network and delayed lingering decreases within the nucleus accumbens - a key structure in the reward valuation pathway. A widespread suppression within the sensorimotor network was also observed. Our findings suggest that neural computations of salience and valence prediction errors during skilled motor behaviors operate on different time-scales and, therefore, may contribute differentially to immediate and longer-term adaptive processes.

Motor training strengthens corticospinal suppression during movement preparation

Movement preparation involves a broad suppression in the excitability of the corticospinal pathway, a phenomenon called preparatory suppression. Here, we show that motor training strengthens preparatory suppression and that this strengthening is associated with faster reaction times. Our findings highlight a key role of preparatory suppression in training-driven behavioral improvements.

Symmetric interlimb transfer of newly acquired skilled movements

In this study, we aimed to examine features of interlimb generalization or "transfer" of newly acquired motor skills, with a broader goal of better understanding the mechanisms mediating skill learning. Right-handed participants (n = 36) learned a motor task that required them to make very rapid but accurate reaches to one of eight randomly presented targets, thus bettering the typical speed-accuracy tradeoff. Subjects were divided into an "RL" group that first trained with the right arm and was then tested on the left and an "LR" group that trained with the left arm and was subsequently tested on the right. We found significant interlimb transfer in both groups. Remarkably, we also observed that participants learned faster with their left arm compared with the right. We hypothesized that this could be due to a previously suggested left arm/right hemisphere advantage for movements under variable task conditions. To corroborate this, we recruited two additional groups of participants (n = 22) that practiced the same task under a single target condition. This removal of task level variability eliminated learning rate differences between the arms, yet interlimb transfer remained robust and symmetric, as in the first experiment. Additionally, the strategy used to reduce errors during learning, albeit heterogeneous across subjects particularly in our second experiment, was adopted by the untrained arm. These findings may be best explained as the outcome of the operation of cognitive strategies during the early stages of motor skill learning.NEW & NOTEWORTHY How newly acquired motor skills generalize across effectors is not well understood. Here, we show that newly learned skilled actions transfer symmetrically across the arms and that task-level variability influences learning rate but not transfer magnitude or direction. Interestingly, strategies developed during learning with one arm transfer to the untrained arm. This likely reflects the outcome of learning driven by cognitive mechanisms during the initial stages of motor skill acquisition.

The effect of instruction on motor skill learning

Many motor skills are learned with the help of instructions. In the context of complex motor sequences, instructions often break down the movement into chunks that can then be practiced in isolation. Thus, instructions shape an initial cognitive representation of the skill, which in turn guides practice. Are there ways of breaking up a motor sequence that are better than others? If participants are instructed in a way that hinders performance, how much practice does it take to overcome the influence of the instruction? To answer these questions, we used a paradigm in which participants were asked to perform finger sequences as fast and accurately as possible on a keyboard-like device. In the initial phases of training, participants had to explicitly remember and practice two- or three-digit chunks. These chunks were then combined to form seven 11-digit sequences that participants practiced for the remainder of the study. Each sequence was broken up into chunks in a way such that the instruction was either aligned or misaligned with the basic execution-level constraints. We found that misaligned chunk instruction led to an initial performance deficit compared with the aligned chunk instruction. Overall, instructions still influenced the temporal pattern of performance after 10 days of subsequent training, with shorter interpress intervals within a chunk compared with between chunks. However, for the misaligned instructed sequences, this temporal pattern was altered more rapidly, such that participants could overcome the induced performance deficit in the last week. At the end of training, participants found idiosyncratic, but interindividually stable, ways of performing each sequence.NEW & NOTEWORTHY Instructions often break down motor sequences into smaller parts, such that they can be more easily remembered. Here, we show that different ways of breaking down a finger sequence can subsequently lead to better or worse performance. The initial instruction still influenced the temporal performance pattern after 10 days of practice. The results demonstrate that the initial cognitive representation of a motor skill strongly influences how a skill is learned and performed.

Action-Perception Coupling and Near Transfer: Listening to Melodies after Piano Practice Triggers Sequence-Specific Representations in the Auditory-Motor Network

Understanding how perception and action are coupled in the brain has important implications for training, rehabilitation, and brain–machine interfaces. Ideomotor theory postulates that willed actions are represented through previously experienced effects and initiated by the anticipation of those effects. Previous research has accordingly found that sensory events, if previously associated with action outcomes, can induce activity in motor regions. However, it remains unclear whether the motor-related activity induced during perception of more naturalistic sequences of actions actually represents “sequence-specific” information. In the present study, nonmusicians were firstly trained to play two melodies on the piano; secondly, they performed an fMRI experiment while listening to these melodies as well as novel, untrained melodies; thirdly, multivariate pattern analysis was used to test if voxel-wise patterns of brain activity could identify trained, but not novel melodies. The results importantly show that after associative learning, a series of sensory events can trigger sequence-specific representations in both sensory and motor networks. Interestingly, also novel melodies could be classified in multiple regions, including default mode regions. A control experiment confirmed these outcomes to be training-dependent. We discuss how action-perception coupling may enable spontaneous near transfer and action simulation during action observation.

Discrete finger sequences are widely represented in human striatum

Research in primates and rodents ascribes the striatum a critical role in integrating elementary movements into unitary action sequences through reinforcement-based learning. Yet it remains to be shown whether the human striatum represents action sequence-specific information. Young right-handed volunteers underwent functional magnetic resonance imaging while they performed four discrete finger sequences with their right hand, consisting of five button presses. Specific finger sequences could be discriminated based on the distributed activity patterns in left and right striatum, but not by average differences in single-voxel activity. Multiple bilateral clusters in putamen and caudate nucleus belonging to motor, associative, parietal and limbic territories contributed to classification sensitivity. The results show that individual finger movement sequences are widely represented in human striatum, supporting functional integration rather than segregation. The findings are compatible with the idea that the basal ganglia simultaneously integrate motor, associative and limbic aspects in the control of complex overlearned behaviour.