Structural and functional bases for individual differences in motor learning

Resting-State Functional Networks Correlate with Motor Performance in a Complex Visuomotor Task: An EEG Microstate Pilot Study on Healthy Individuals

Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners' functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks-the Attention Network (AN) and the Default Mode Network (DMN)-affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN-linked to internally diverted attention and mind-wandering-would be detrimental for posterior motor performance. We extracted seven widely accepted microstates-representing participants mind states at rest-out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN-imaged using EEG microstates-as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.

Rich-club organization of whole-brain spatio-temporal multilayer functional connectivity networks

Objective

In this work, we propose a novel method for constructing whole-brain spatio-temporal multilayer functional connectivity networks (FCNs) and four innovative rich-club metrics.

Methods

Spatio-temporal multilayer FCNs achieve a high-order representation of the spatio-temporal dynamic characteristics of brain networks by combining the sliding time window method with graph theory and hypergraph theory. The four proposed rich-club scales are based on the dynamic changes in rich-club node identity, providing a parameterized description of the topological dynamic characteristics of brain networks from both temporal and spatial perspectives. The proposed method was validated in three independent differential analysis experiments: male-female gender difference analysis, analysis of abnormality in patients with autism spectrum disorders (ASD), and individual difference analysis.

Results

The proposed method yielded results consistent with previous relevant studies and revealed some innovative findings. For instance, the dynamic topological characteristics of specific white matter regions effectively reflected individual differences. The increased abnormality in internal functional connectivity within the basal ganglia may be a contributing factor to the occurrence of repetitive or restrictive behaviors in ASD patients.

Conclusion

The proposed methodology provides an efficacious approach for constructing whole-brain spatio-temporal multilayer FCNs and conducting analysis of their dynamic topological structures. The dynamic topological characteristics of spatio-temporal multilayer FCNs may offer new insights into physiological variations and pathological abnormalities in neuroscience.

Associating white matter microstructural integrity and improvements in reactive stepping in people with Parkinson's Disease

Reactive steps are rapid responses after balance challenges. People with Parkinson's Disease (PwPD) demonstrate impaired reactive stepping, increasing fall-risk. Although PwPD can improve steps through practice, the neural mechanisms contributing to improved reactive stepping are poorly understood. This study investigated white-matter correlates of responsiveness to reactive step training in PwPD. In an eighteen-week multiple-baseline study, participants (n = 22) underwent baseline assessments (B1 and B2 two-weeks apart), a two-week training protocol, and post-training assessments immediately (P1) and two-months (P2) post-training. Assessments involved three backward reactive step trials, measuring anterior-posterior margin of stability (AP MOS), step length, and step latency. Tract-Based Spatial Statistics correlated white-matter integrity (fractional anisotropy (FA) and radial diffusivity (RD)) with retained (P2-B2) and immediate improvements (P1-B2) in stepping. Significant and sustained improvements in step length and AP MOS were observed. Greater retention of step length improvement correlated with increased FA in the left anterior thalamic radiation (ATR), left posterior thalamic radiation (PTR), left superior longitudinal fasciculus (SLF), and right inferior longitudinal fasciculus (ILF). Step latency retention was associated with lower RD in the left posterior corona radiata and left PTR. Immediate improvements in AP MOS correlated with increased FA of the right ILF, right SLF, and right corticospinal tract. Immediate step length improvements were associated with increased FA in right and left ATR and right SLF. These findings highlight the importance of white-matter microstructural integrity in motor learning and retention processes in PD and could aid in identifying individuals with PD who would benefit most from balance rehabilitation.

Functional connectivity via the dorsolateral prefrontal cortex in the late phase of rest periods predicts offline learning

The relationship between offline learning gains and functional connectivity (FC) has been investigated in several studies. They have focused on average motor task performance and resting-state FC across subjects. Generally, individual differences are seen in both offline learning gain and neurophysiological profiles in resting-state FC. However, few studies have focused on the relationship between individual differences in offline learning gain and temporal characteristics of resting-state FC. The present study aimed to clarify this relationship between the two profiles. Thirty-four healthy right-handed participants performed a force-controlled motor task. Electroencephalography was performed during the 15-minute wakeful rest period between tasks. The results revealed a significant correlation between offline learning gain and FC between the contralateral dorsolateral prefrontal cortex (DLPFC) and contralateral primary motor cortex (M1), and ipsilateral primary somatosensory cortex (S1) during late phase of the rest interval. These results are consistent with the findings of previous studies showing the FC between M1, which is necessary for awake offline learning, and DLPFC, which is related to motor control. Additionally, sensory feedback related to force control may be caused by the interaction between contralateral DLPFC and ipsilateral S1. Our study shed light on the temporal profiles of resting-state FC associated with individual differences in offline learning.

Brain connectome correlates of short-term motor learning in healthy older subjects

The motor learning process entails plastic changes in the brain, especially in brain network reconfigurations. In the current study, we sought to characterize motor learning by determining changes in the coupling behaviour between the brain functional and structural connectomes on a short timescale. 39 older subjects (age: mean (SD) = 69.7 (4.7) years, men:women = 15:24) were trained on a visually guided sequential hand grip learning task. The brain structural and functional connectomes were constructed from diffusion-weighted MRI and resting-state functional MRI, respectively. The association of motor learning ability with changes in network topology of the brain functional connectome and changes in the correspondence between the brain structural and functional connectomes were assessed. Motor learning ability was related to decreased efficiency and increased modularity in the visual, somatomotor, and frontoparietal networks of the brain functional connectome. Between the brain structural and functional connectomes, reduced correspondence in the visual, ventral attention, and frontoparietal networks as well as the whole-brain network was related to motor learning ability. In addition, structure-function correspondence in the dorsal attention, ventral attention, and frontoparietal networks before motor learning was predictive of motor learning ability. These findings indicate that, in the view of brain connectome changes, short-term motor learning is represented by a detachment of the brain functional from the brain structural connectome. The structure-function uncoupling accompanied by the enhanced segregation into modular structures over the core functional networks involved in the learning process may suggest that facilitation of functional flexibility is associated with successful motor learning.

Individual differences in rhythm perception modulate music-related motor learning: a neurobehavioral training study with children

Rhythm and motor function are intrinsically linked to each other and to music, but the rhythm-motor interplay during music training, and the corresponding brain mechanisms, are underexplored. In a longitudinal training study with children, we examined the role of rhythm predisposition in the fine motor improvements arising from music training, and which brain regions would be implicated. Fifty-seven 8-year-olds were assigned to either a 6-month music training (n = 21), sports training (n = 18), or a control group (n = 18). They performed rhythm and motor tasks, and structural brain scans before and after training were collected. Better ability to perceive rhythm before training was related to less gray matter volume in regions of the cerebellum, fusiform gyrus, supramarginal gyrus, ventral diencephalon, amygdala, and inferior/middle temporal gyri. Music training improved motor performance, and greater improvements correlated with better pre-training rhythm discrimination. Music training also induced a loss of gray matter volume in the left cerebellum and fusiform gyrus, and volume loss correlated with higher motor gains. No such effects were found in the sports and control groups. In summary, children with finer-tuned rhythm perception abilities were prone to finer motor improvements through music training, and this rhythm-motor link was to some extent subserved by the left cerebellum and fusiform gyrus. These findings have implications for models on music-related plasticity and rhythm cognition, and for programs targeting motor function.

Curricula for teaching end-users to kinesthetically program collaborative robots

Non-expert users can now program robots using various end-user robot programming methods, which have widened the use of robots and lowered barriers preventing robot use by laypeople. Kinesthetic teaching is a common form of end-user robot programming, allowing users to forgo writing code by physically guiding the robot to demonstrate behaviors. Although it can be more accessible than writing code, kinesthetic teaching is difficult in practice because of users' unfamiliarity with kinematics or limitations of robots and programming interfaces. Developing good kinesthetic demonstrations requires physical and cognitive skills, such as the ability to plan effective grasps for different task objects and constraints, to overcome programming difficulties. How to help users learn these skills remains a largely unexplored question, with users conventionally learning through self-guided practice. Our study compares how self-guided practice compares with curriculum-based training in building users' programming proficiency. While we found no significant differences between study participants who learned through practice compared to participants who learned through our curriculum, our study reveals insights into factors contributing to end-user robot programmers' confidence and success during programming and how learning interventions may contribute to such factors. Our work paves the way for further research on how to best structure training interventions for end-user robot programmers.

Cognitive Predictors of Responsiveness to Reactive Step Training in People with Parkinson's Disease at Fall-Risk

Reactive stepping can be improved in people with Parkinson's Disease (PwPD). However, there is variability in the responsiveness to such training. This study examined if cognition could predict the responsiveness of PwPD to a two-week reactive step training intervention. 25 PwPD (70.52 years ± 7.15; Hoehn & Yahr range 1-3) at risk for falls completed a multiple baseline, open-label, uncontrolled pre-post intervention study. Reactive stepping was trained through a two-week (six-session) intervention with repeated support surface translations. Stepping performance was measured at two baseline assessments (B1 and B2), immediately after the intervention (P1), and two months after training (P2). Primary stepping outcomes were anterior-posterior margin of stability (MOS), step length, and step latency during backward steps. The primary aim assessed whether global cognition (Scales for Outcomes in Parkinson's Disease-Cognition - SCOPA-COG, & Montreal Cognitive Assessment - MoCA) was related to two-month retention of improvements in reactive stepping after practice. The secondary aim explored whether specific cognitive domains predicted retained stepping improvements, including attention/working memory, executive function, language, memory, and visuospatial function. Greater baseline global cognition was related to better two-month retention of step length improvements (SCOPA-COG: p = 0.002, f2 = 0.31; MoCA: p = 0.002, f2 = 0.38). However, only SCOPA-COG retained statistical significance after p-value adjustment for multiple comparisons (p = 0.04). Optimal cut-point analysis revealed that a SCOPA-COG threshold of 31 or higher was optimal for identifying individuals likely to retain improvement. Specific cognitive domains did not predict changes in reactive stepping outcomes. Participants with greater baseline global cognition, particularly as measured by SCOPA-COG, demonstrated greater retention of improvements in reactive stepping. In this cohort, a SCOPA-COG threshold of 31 could predict individuals likely to benefit from the intervention. These findings highlight the potential of cognitive screening to identify people more or less likely to benefit from reactive balance training.

Changes in brain perfusion with training-related visuomotor improvement in MS

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. A better understanding of the mechanisms supporting brain plasticity in MS would help to develop targeted interventions to promote recovery. A total of 29 MS patients and 19 healthy volunteers underwent clinical assessment and multi-modal MRI acquisition [fMRI during serial reaction time task (SRT), DWI, T1w structural scans and ASL of resting perfusion] at baseline and after 4-weeks of SRT training. Reduction of functional hyperactivation was observed in MS patients following the training, shown by the stronger reduction of the BOLD response during task execution compared to healthy volunteers. The functional reorganization was accompanied by a positive correlation between improvements in task accuracy and the change in resting perfusion after 4 weeks' training in right angular and supramarginal gyri in MS patients. No longitudinal changes in WM and GM measures and no correlation between task performance improvements and brain structure were observed in MS patients. Our results highlight a potential role for CBF as an early marker of plasticity, in terms of functional (cortical reorganization) and behavioral (performance improvement) changes in MS patients that may help to guide future interventions that exploit preserved plasticity mechanisms.

Vigilant attention mediates the association between resting EEG alpha oscillations and word learning ability

Individuals exhibit considerable variability in their capacity to learn and retain new information, including novel vocabulary. Prior research has established the importance of vigilance and electroencephalogram (EEG) alpha rhythm in the learning process. However, the interplay between vigilant attention, EEG alpha oscillations, and an individual's word learning ability (WLA) remains elusive. To address this knowledge gap, here we conducted two experiments with a total of 140 young and middle-aged adults who underwent resting EEG recordings prior to completing a paired-associate word learning task and a psychomotor vigilance test (PVT). The results of both experiments consistently revealed significant positive correlations between WLA and resting EEG alpha oscillations in the occipital and frontal regions. Furthermore, the association between resting EEG alpha oscillations and WLA was mediated by vigilant attention, as measured by the PVT. These findings provide compelling evidence supporting the crucial role of vigilant attention in linking EEG alpha oscillations to an individual's learning ability.

Initial motor skill performance predicts future performance, but not learning

People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants' future performance and learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We used machine learning to predict future performance and learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. Strong correlations were observed between initial and final performance, and individual learning was not predicted. While canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, development of novel tasks may shed light on the underlying mechanism of individual skill learning, relevant for real-life scenarios.

Neurophysiological and Clinical Effects of Upper Limb Robot-Assisted Rehabilitation on Motor Recovery in Patients with Subacute Stroke: A Multicenter Randomized Controlled Trial Study Protocol

BACKGROUND

The efficacy of upper limb (UL) robot-assisted therapy (RAT) on functional improvement after stroke remains unclear. However, recently published randomized controlled trials have supported its potential benefits in enhancing the activities of daily living, arm and hand function, and muscle strength. Task-specific and high-intensity exercises are key points in facilitating motor re-learning in neurorehabilitation since RAT can provide an assisted-as-needed approach. This study aims to investigate the clinical effects of an exoskeleton robotic system for UL rehabilitation compared with conventional therapy (CT) in people with subacute stroke. As a secondary aim, we seek to identify patients' characteristics, which can predict better recovery after UL-RAT and detects whether it could elicit greater brain stimulation.

METHODS

A total of 84 subacute stroke patients will be recruited from 7 Italian rehabilitation centers over 3 years. The patients will be randomly allocated to either CT (control group, CG) or CT plus UL-RT through an Armeo^®Power (Hocoma AG, CH, Volketswil, Switzerland) exoskeleton (experimental group, EG). A sample stratification based on distance since onset, DSO (DSO ≤ 30; DSO > 30), and Fugl-Meyer Assessment (FM)-UL (FM-UL ≤ 22; 22 < FM-UL ≤ 44) will be considered for the randomization. The outcomes will be recorded at baseline (T0), after 25 + 3 sessions of intervention (T1), and at 6 months post-stroke (T2). The motor functioning assessed by the FM-UL (0-66) will be considered the primary outcome. The clinical assessments will be set based on the International Classification of Function, Disability and Health (ICF). A patient satisfaction questionnaire will be evaluated in the EG at T1. A subgroup of patients will be evaluated at T0 and T1 via electroencephalography. Their brain electrical activity will be recorded during rest conditions with their eyes closed and open (5 min each).

CONCLUSION

The results of this trial will provide an in-depth understanding of the efficacy of early UL-RAT through a whole arm exoskeleton and how it may relate to the neural plasticity process. The trial was registered at ClinicalTrial.gov with the registration identifier NCT04697368.

Robust enhancement of motor sequence learning with 4 mA transcranial electric stimulation

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 polarities, 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.

Using whole-brain diffusion tensor analysis to evaluate white matter structural correlates of delayed visuospatial memory and one-week motor skill retention in nondemented older adults: A preliminary study

Skill retention is important for motor rehabilitation outcomes. Recent work has demonstrated that delayed visuospatial memory performance may predict motor skill retention in older and neuropathological populations. White matter integrity between parietal and frontal cortices may explain variance in upper-extremity motor learning tasks and visuospatial processes. We performed a whole-brain analysis to determine the white matter correlates of delayed visuospatial memory and one-week motor skill retention in nondemented older adults. We hypothesized that better frontoparietal tract integrity would be positively related to better behavioral performance. Nineteen participants (age>58) completed diffusion-weighted imaging, then a clinical test of delayed visuospatial memory and 50 training trials of an upper-extremity motor task; participants were retested on the motor task one week later. Principal component analysis was used to create a composite score for each participant's behavioral data, i.e. shared variance between delayed visuospatial memory and motor skill retention, which was then entered into a voxel-based regression analysis. Behavioral results demonstrated that participants learned and retained their skill level after a week of no practice, and their delayed visuospatial memory score was positively related to the extent of skill retention. Consistent with previous work, neuroimaging results indicated that regions within bilateral anterior thalamic radiations, corticospinal tracts, and superior longitudinal fasciculi were related to better delayed visuospatial memory and skill retention. Results of this study suggest that the simple act of testing for specific cognitive impairments prior to therapy may identify older adults who will receive little to no benefit from the motor rehabilitation regimen, and that these neural regions may be potential targets for therapeutic intervention.

A Systematic Review of Individual Differences in Perception, Action, and Decision Making: Implications for Dance Education

This systematic bibliometric review summarizes recent neurocognitive research highlighting inter-individual differences in perception, action, and decision making that may have implications for dance education. First, the relevance of individual differences in cognitive functioning for dance education is illustrated by describing how a person's preferred reliance on certain perceptual, motor, or (meta) cognitive skills may be exploited in dance training. Subsequently, we describe the findings of a literature search conducted to identify cognitive neuroscientific publications between 2010 and 2021 that highlight individual differences in cognitive functions that were also found to be supported by structural or functional-connectivity differences in the central nervous system. To cluster the findings of the literature search, we propose a simplified, six-category information processing model. Finally, for each model category, we summarize recent representative findings on salient individual differences and tentatively formulate testable implications for dance education practice with regard to pedagogical and curricula adaptations. Finally, the review also delineates an agenda for lines of research of which the results hopefully will assist dance instructors in the future.

General principles of brain electromagnetic rhythmic oscillations and implications for neuroplasticity

Neuro-plasticity describes the ability of the brain in achieving novel functions, either by transforming its internal connectivity, or by changing the elements of which it is made, meaning that, only those changes, that affect both structural and functional aspects of the system, can be defined as "plastic." The concept of plasticity can be applied to molecular as well as to environmental events that can be recognized as the basic mechanism by which our brain reacts to the internal and external stimuli. When considering brain plasticity within a clinical context-that is the process linked with changes of brain functions following a lesion- the term "reorganization" is somewhat synonymous, referring to the specific types of structural/functional modifications observed as axonal sprouting, long-term synaptic potentiation/inhibition or to the plasticity related genomic responses. Furthermore, brain rewires during maturation, and aging thus maintaining a remarkable learning capacity, allowing it to acquire a wide range of skills, from motor actions to complex abstract reasoning, in a lifelong expression. In this review, the contribution on the "neuroplasticity" topic coming from advanced analysis of EEG rhythms is put forward.

Microstructural Properties of Human Brain Revealed by Fractional Anisotropy Can Predict the After-Effect of Intermittent Theta Burst Stimulation

Intermittent theta burst stimulation (iTBS) delivered by transcranial magnetic stimulation (TMS) produces a long-term potentiation-like after-effect useful for investigations of cortical function and of potential therapeutic value. However, the iTBS after-effect over the primary motor cortex (M1) as measured by changes in motor evoked potential (MEP) amplitude exhibits a largely unexplained variability across individuals. Here, we present evidence that individual differences in white matter (WM) and gray matter (GM) microstructural properties revealed by fractional anisotropy (FA) predict the magnitude of the iTBS-induced after-effect over M1. The MEP amplitude change in the early phase (5–10 min post-iTBS) was associated with FA values in WM tracts such as right superior longitudinal fasciculus and corpus callosum. By contrast, the MEP amplitude change in the late phase (15–30 min post-iTBS) was associated with FA in GM, primarily in right frontal cortex. These results suggest that the microstructural properties of regions connected directly or indirectly to the target region (M1) are crucial determinants of the iTBS after-effect. FA values indicative of these microstructural differences can predict the potential effectiveness of repetitive TMS for both investigational use and clinical application.

Individual differences in motor skill learning: Past, present and future

Humans vary considerably in their ability to perform and learn new motor skills. In addition, they respond to different performance and practice conditions in varying ways. Historically, experimental psychologists have characterized these differences as 'experimental noise', yet for those who embrace differential psychology, the study of individual differences promises to deepen insights into the processes that mediate motor control and learning. In this paper, we highlight what we know about predicting motor learning based on individual difference characteristics and renew a call made by Lee Cronbach several decades ago to combine the methodologies used by experimental and differential psychologists to further our understanding of how to promote motor learning. The paper provides a brief historical overview of research on individual differences and motor learning followed by a systematic review of the last 20 years of research on this issue. The paper ends by highlighting some of the methodological challenges associated with conducting research on individual differences, as well as providing suggestions for future research. The study of individual differences has important implications for furthering our understanding of motor learning and when tailoring interventions for diverse learners at different stages of practice.

Theta but not beta power is positively associated with better explicit motor task learning

Neurophysiologic correlates of motor learning that can be monitored during neurorehabilitation interventions can facilitate the development of more effective learning methods. Previous studies have focused on the role of the beta band (14-30 Hz) because of its clear response during motor activity. However, it is difficult to discriminate between beta activity related to learning a movement and performing the movement. In this study, we analysed differences in the electroencephalography (EEG) power spectra of complex and simple explicit sequential motor tasks in healthy young subjects. The complex motor task (CMT) allowed EEG measurement related to motor learning. In contrast, the simple motor task (SMT) made it possible to control for EEG activity associated with performing the movement without significant motor learning. Source reconstruction of the EEG revealed task-related activity from 5 clusters covering both primary motor cortices (M1) and 3 clusters localised to different parts of the cingulate cortex (CC). We found no association between M1 beta power and learning, but the CMT produced stronger bilateral beta suppression compared to the SMT. However, there was a positive association between contralateral M1 theta (5-8 Hz) and alpha (8-12 Hz) power and motor learning, and theta and alpha power in the posterior mid-CC and posterior CC were positively associated with greater motor learning. These findings suggest that the theta and alpha bands are more related to motor learning than the beta band, which might merely relate to the level of perceived difficulty during learning.

Explicit motor sequence learning after stroke: a neuropsychological study

Motor learning interacts with and shapes experience-dependent cerebral plasticity. In stroke patients with paresis of the upper limb, motor recovery was proposed to reflect a process of re-learning the lost/impaired skill, which interacts with rehabilitation. However, to what extent stroke patients with hemiparesis may retain the ability of learning with their affected limb remains an unsolved issue, that was addressed by this study. Nineteen patients, with a cerebrovascular lesion affecting the right or the left hemisphere, underwent an explicit motor learning task (finger tapping task, FTT), which was performed with the paretic hand. Eighteen age-matched healthy participants served as controls. Motor performance was assessed during the learning phase (i.e., online learning), as well as immediately at the end of practice, and after 90 min and 24 h (i.e., retention). Results show that overall, as compared to the control group, stroke patients, regardless of the side (left/right) of the hemispheric lesion, do not show a reliable practice-dependent improvement; consequently, no retention could be detected in the long-term (after 90 min and 24 h). The motor learning impairment was associated with subcortical damage, predominantly affecting the basal ganglia; conversely, it was not associated with age, time elapsed from stroke, severity of upper-limb motor and sensory deficits, and the general neurological condition. This evidence expands our understanding regarding the potential of post-stroke motor recovery through motor practice, suggesting a potential key role of basal ganglia, not only in implicit motor learning as previously pointed out, but also in explicit finger tapping motor tasks.

Predictors of training-related improvement in visuomotor performance in patients with multiple sclerosis: A behavioural and MRI study

BACKGROUND

The development of tailored recovery-oriented strategies in multiple sclerosis requires early identification of an individual's potential for functional recovery.

OBJECTIVE

To identify predictors of visuomotor performance improvements, a proxy of functional recovery, using a predictive statistical model that combines demographic, clinical and magnetic resonance imaging (MRI) data.

METHODS

Right-handed multiple sclerosis patients underwent baseline disability assessment and MRI of the brain structure, function and vascular health. They subsequently undertook 4 weeks of right upper limb visuomotor practice. Changes in performance with practice were our outcome measure. We identified predictors of improvement in a training set of patients using lasso regression; we calculated the best performing model in a validation set and applied this model to a test set.

RESULTS

Patients improved their visuomotor performance with practice. Younger age, better visuomotor abilities, less severe disease burden and concurrent use of preventive treatments predicted improvements. Neuroimaging localised outcome-relevant sensory motor regions, the microstructure and activity of which correlated with performance improvements.

CONCLUSION

Initial characteristics, including age, disease duration, visuo-spatial abilities, hand dexterity, self-evaluated disease impact and the presence of disease-modifying treatments, can predict functional recovery in individual patients, potentially improving their clinical management and stratification in clinical trials. MRI is a correlate of outcome, potentially supporting individual prognosis.

Single-Trial Kernel-Based Functional Connectivity for Enhanced Feature Extraction in Motor-Related Tasks

Motor learning is associated with functional brain plasticity, involving specific functional connectivity changes in the neural networks. However, the degree of learning new motor skills varies among individuals, which is mainly due to the between-subject variability in brain structure and function captured by electroencephalographic (EEG) recordings. Here, we propose a kernel-based functional connectivity measure to deal with inter/intra-subject variability in motor-related tasks. To this end, from spatio-temporal-frequency patterns, we extract the functional connectivity between EEG channels through their Gaussian kernel cross-spectral distribution. Further, we optimize the spectral combination weights within a sparse-based ℓ2-norm feature selection framework matching the motor-related labels that perform the dimensionality reduction of the extracted connectivity features. From the validation results in three databases with motor imagery and motor execution tasks, we conclude that the single-trial Gaussian functional connectivity measure provides very competitive classifier performance values, being less affected by feature extraction parameters, like the sliding time window, and avoiding the use of prior linear spatial filtering. We also provide interpretability for the clustered functional connectivity patterns and hypothesize that the proposed kernel-based metric is promising for evaluating motor skills.

Multifocal stimulation of the cerebro-cerebellar loop during the acquisition of a novel motor skill

Transcranial direct current stimulation (tDCS)-based interventions for augmenting motor learning are gaining interest in systems neuroscience and clinical research. Current approaches focus largely on monofocal motorcortical stimulation. Innovative stimulation protocols, accounting for motor learning related brain network interactions also, may further enhance effect sizes. Here, we tested different stimulation approaches targeting the cerebro-cerebellar loop. Forty young, healthy participants trained a fine motor skill with concurrent tDCS in four sessions over two days, testing the following conditions: (1) monofocal motorcortical, (2) sham, (3) monofocal cerebellar, or (4) sequential multifocal motorcortico-cerebellar stimulation in a double-blind, parallel design. Skill retention was assessed after circa 10 and 20 days. Furthermore, potential underlying mechanisms were studied, applying paired-pulse transcranial magnetic stimulation and multimodal magnetic resonance imaging-based techniques. Multisession motorcortical stimulation facilitated skill acquisition, when compared with sham. The data failed to reveal beneficial effects of monofocal cerebellar or additive effects of sequential multifocal motorcortico-cerebellar stimulation. Multimodal multiple linear regression modelling identified baseline task performance and structural integrity of the bilateral superior cerebellar peduncle as the most influential predictors for training success. Multisession application of motorcortical tDCS in several daily sessions may further boost motor training efficiency. This has potential implications for future rehabilitation trials.

Age-related reduction in motor adaptation: brain structural correlates and the role of explicit memory

The adaption of movement to changes in the environment varies across life span. Recent evidence has linked motor adaptation and its reduction with age to differences in "explicit" learning processes. We examine differences in brain structure and cognition underlying motor adaptation in a population-based cohort (n = 322, aged 18-89 years) using a visuomotor learning task and structural magnetic resonance imaging. Reduced motor adaptation with age was associated with reduced volume in striatum, prefrontal, and sensorimotor cortical regions, but not cerebellum. Medial temporal lobe volume, including the hippocampus, became a stronger determinant of motor adaptation with age. Consistent with the role of the medial temporal lobes, declarative long-term memory showed a similar interaction, whereby memory was more positively correlated with motor adaptation with increasing age. By contrast, visual short-term memory was related to motor adaptation, independently of age. These results support the hypothesis that cerebellar learning is largely unaffected in old age, and the reduction in motor adaptation with age is driven by a decline in explicit memory systems.

Principles of Motor Learning to Support Neuroplasticity After ACL Injury: Implications for Optimizing Performance and Reducing Risk of Second ACL Injury

Athletes who wish to resume high-level activities after an injury to the anterior cruciate ligament (ACL) are often advised to undergo surgical reconstruction. Nevertheless, ACL reconstruction (ACLR) does not equate to normal function of the knee or reduced risk of subsequent injuries. In fact, recent evidence has shown that only around half of post-ACLR patients can expect to return to competitive level of sports. A rising concern is the high rate of second ACL injuries, particularly in young athletes, with up to 20% of those returning to sport in the first year from surgery experiencing a second ACL rupture. Aside from the increased risk of second injury, patients after ACLR have an increased risk of developing early onset of osteoarthritis. Given the recent findings, it is imperative that rehabilitation after ACLR is scrutinized so the second injury preventative strategies can be optimized. Unfortunately, current ACLR rehabilitation programs may not be optimally effective in addressing deficits related to the initial injury and the subsequent surgical intervention. Motor learning to (re-)acquire motor skills and neuroplastic capacities are not sufficiently incorporated during traditional rehabilitation, attesting to the high re-injury rates. The purpose of this article is to present novel clinically integrated motor learning principles to support neuroplasticity that can improve patient functional performance and reduce the risk of second ACL injury. The following key concepts to enhance rehabilitation and prepare the patient for re-integration to sports after an ACL injury that is as safe as possible are presented: (1) external focus of attention, (2) implicit learning, (3) differential learning, (4) self-controlled learning and contextual interference. The novel motor learning principles presented in this manuscript may optimize future rehabilitation programs to reduce second ACL injury risk and early development of osteoarthritis by targeting changes in neural networks.

Neurodiagnostics in Sports: Investigating the Athlete's Brain to Augment Performance and Sport-Specific Skills

Enhancing performance levels of athletes during training and competition is a desired goal in sports. Quantifying training success is typically accompanied by performance diagnostics including the assessment of sports-relevant behavioral and physiological parameters. Even though optimal brain processing is a key factor for augmented motor performance and skill learning, neurodiagnostics is typically not implemented in performance diagnostics of athletes. We propose, that neurodiagnostics via non-invasive brain imaging techniques such as functional near-infrared spectroscopy (fNIRS) will offer novel perspectives to quantify training-induced neuroplasticity and its relation to motor behavior. A better understanding of such a brain-behavior relationship during the execution of sport-specific movements might help to guide training processes and to optimize training outcomes. Furthermore, targeted non-invasive brain stimulation such as transcranial direct current stimulation (tDCS) might help to further enhance training outcomes by modulating brain areas that show training-induced neuroplasticity. However, we strongly suggest that ethical aspects in the use of non-invasive brain stimulation during training and/or competition need to be addressed before neuromodulation can be considered as a performance enhancer in sports.

Motor Imagery Training After Stroke Increases Slow-5 Oscillations and Functional Connectivity in the Ipsilesional Inferior Parietal Lobule

Background. Reorganization in motor areas have been suggested after motor imagery training (MIT). However, motor imagery involves a large-scale brain network, in which many regions, andnot only the motor areas, potentially constitute the neural substrate for MIT. Objective. This study aimed to identify the targets for MIT in stroke rehabilitation from a voxel-based whole brain analysis of resting-state functional magnetic resonance imaging (fMRI). Methods. Thirty-four chronic stroke patients were recruited and randomly assigned to either an MIT group or a control group. The MIT group received a 4-week treatment of MIT plus conventional rehabilitation therapy (CRT), whereas the control group only received CRT. Before and after intervention, the Fugl-Meyer Assessment Upper Limb subscale (FM-UL) and resting-state fMRI were collected. The fractional amplitude of low-frequency fluctuations (fALFF) in the slow-5 band (0.01-0.027 Hz) was calculated across the whole brain to identify brain areas with distinct changes between 2 groups. These brain areas were then targeted as seeds to perform seed-based functional connectivity (FC) analysis. Results. In comparison with the control group, the MIT group exhibited more improvements in FM-UL and increased slow-5 fALFF in the ipsilesional inferior parietal lobule (IPL). The change of the slow-5 oscillations in the ipsilesional IPL was positively correlated with the improvement of FM-UL. The MIT group also showed distinct alternations in FCs of the ipsilesional IPL, which were correlated with the improvement of FM-UL. Conclusions. The rehabilitation efficiency of MIT was associated with increased slow-5 oscillations and altered FC in the ipsilesional IPL. Clinical Trial Registration. http://www.chictr.org.cn . Unique Identifier. ChiCTR-TRC-08003005.

The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum

The corpus callosum serves the functional integration and interaction between the two hemispheres. Many studies investigate callosal microstructure via diffusion tensor imaging (DTI) fractional anisotropy (FA) in geometrically parcellated segments. However, FA is influenced by several different microstructural properties such as myelination and axon density, hindering a neurobiological interpretation. This study explores the relationship between FA and more specific measures of microstructure within the corpus callosum in a sample of 271 healthy participants. DTI tractography was used to assess 11 callosal segments and gain estimates of FA. We quantified axon density and myelination via neurite orientation dispersion and density imaging (NODDI) to assess intra-neurite volume fraction and a multiecho gradient spin-echo sequence estimating myelin water fraction. The results indicate three common factors in the distribution of FA, myelin content and axon density, indicating potentially shared rules of topographical distribution. Moreover, the relationship between measures varied across the corpus callosum, suggesting that FA should not be interpreted uniformly. More specific magnetic resonance imaging-based quantification techniques, such as NODDI and multiecho myelin water imaging, may thus play a key role in future studies of clinical trials and individual differences.

Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review

Brain computer interfaces (BCI) for the rehabilitation of motor impairments exploit sensorimotor rhythms (SMR) in the electroencephalogram (EEG). However, the neurophysiological processes underpinning the SMR often vary over time and across subjects. Inherent intra- and inter-subject variability causes covariate shift in data distributions that impede the transferability of model parameters amongst sessions/subjects. Transfer learning includes machine learning-based methods to compensate for inter-subject and inter-session (intra-subject) variability manifested in EEG-derived feature distributions as a covariate shift for BCI. Besides transfer learning approaches, recent studies have explored psychological and neurophysiological predictors as well as inter-subject associativity assessment, which may augment transfer learning in EEG-based BCI. Here, we highlight the importance of measuring inter-session/subject performance predictors for generalized BCI frameworks for both normal and motor-impaired people, reducing the necessity for tedious and annoying calibration sessions and BCI training.

Interindividual differences in gray and white matter properties are associated with early complex motor skill acquisition

Brain circuits mediate but also constrain experience-induced plasticity and corresponding behavioral changes. Here we tested whether interindividual behavioral differences in learning a challenging new motor skill correlate with variations in brain anatomy. Young, healthy participants were scanned using structural magnetic resonance imaging (T1-weighted MPRAGE, n = 75 and/or diffusion-weighted MRI, n = 59) and practiced a complex whole-body balancing task on a seesaw-like platform. Using conjunction tests based on the nonparametric combination (NPC) methodology, we found that gray matter volume (GMV) in the right orbitrofrontal cortex was positively related to the subjects' initial level of proficiency and their ability to improve performance during practice. Similarly, we obtained a strong trend toward a positive correlation between baseline fractional anisotropy (FA) in commissural prefrontal fiber pathways and later motor learning. FA results were influenced more strongly by radial than axial diffusivity. However, we did not find unique anatomical correlates of initial performance and learning to rate. Our findings reveal structural predispositions for successful motor skill performance and acquisition in frontal brain structures and underlying frontal white matter tracts. Together with previous results, these findings support the view that structural constraints imposed by the brain determine subsequent behavioral success and underline the importance of structural brain network constitution before learning starts.

Alterations of Functional Brain Connectivity After Long-Duration Spaceflight as Revealed by fMRI

The present study reports alterations of task-based functional brain connectivity in a group of 11 cosmonauts after a long-duration spaceflight, compared to a healthy control group not involved in the space program. To elicit the postural and locomotor sensorimotor mechanisms that are usually most significantly impaired when space travelers return to Earth, a plantar stimulation paradigm was used in a block design fMRI study. The motor control system activated by the plantar stimulation involved the pre-central and post-central gyri, SMA, SII/operculum, and, to a lesser degree, the insular cortex and cerebellum. While no post-flight alterations were observed in terms of activation, the network-based statistics approach revealed task-specific functional connectivity modifications within a broader set of regions involving the activation sites along with other parts of the sensorimotor neural network and the visual, proprioceptive, and vestibular systems. The most notable findings included a post-flight increase in the stimulation-specific connectivity of the right posterior supramarginal gyrus with the rest of the brain; a strengthening of connections between the left and right insulae; decreased connectivity of the vestibular nuclei, right inferior parietal cortex (BA40) and cerebellum with areas associated with motor, visual, vestibular, and proprioception functions; and decreased coupling of the cerebellum with the visual cortex and the right inferior parietal cortex. The severity of space motion sickness symptoms was found to correlate with a post- to pre-flight difference in connectivity between the right supramarginal gyrus and the left anterior insula. Due to the complex nature and rapid dynamics of adaptation to gravity alterations, the post-flight findings might be attributed to both the long-term microgravity exposure and to the readaptation to Earth's gravity that took place between the landing and post-flight MRI session. Nevertheless, the results have implications for the multisensory reweighting and gravitational motor system theories, generating hypotheses to be tested in future research.

Microstructural integrity of corticospinal and medial lemniscus tracts: insights from diffusion tensor tractography of right-hand amputees

Reductions in sensory and motor activity following unilateral upper limb amputation during adulthood are associated with widespread, activity-dependent reorganization of the gray matter and white matter through the central nervous system. Likewise, in cases of congenital limb absence there is evidence that limited afferent or efferent activity affects the structural integrity of white matter pathways serving the affected side. Evidence that the structural integrity of mature sensory and motor tracts controlling the lost upper limb exhibits similar activity dependence is, however, sparse and inconsistent. Here we used diffusion tensor tractography to test whether amputation of the dominant right hand during adulthood (n = 16) alters the microstructural integrity of the major sensory (medial lemniscus, ML) and motor (corticospinal tract, CST) pathways controlling missing hand function. Consistent with prior findings, healthy control subjects (n = 27) exhibited higher fractional anisotropy (FA), an index of white matter microstructural integrity, within dominant left CST and nondominant right ML. Critically, in contrast to what might be expected if the microstructural organization of these tracts is activity dependent, these asymmetries persisted in amputees. Moreover, we failed to detect any differences in dominant left ML or CST between healthy control subjects and amputees. Our results are consistent with these white matter tracts being robust to changes in activity once mature or that continued use of the residual limb (in a compensatory fashion or with prosthesis) provides stimulation sufficient to maintain tract integrity. NEW & NOTEWORTHY We report that unilateral hand amputation in adults has no significant effects on the structure of major sensory or motor pathways contralateral to the amputation. Our results are consistent with the organization of these white matter tracts being robust to changes in activity once mature or that continued use of the residual limb (with or without a prosthesis) provides stimulation sufficient to maintain tract integrity.

Inter-individual variability and consistency of saccade adaptation in oblique saccades: Amplitude increase and decrease in the horizontal or vertical saccade component

Despite changes in the physical structures controlling the eyes, saccades, the rapid eye movements used to explore the visual environment, remain accurate throughout the lifetime. The process underlying this sensorimotor adaptation is studied using a double step paradigm: an intra-saccadic target displacement introduces a systematic position error which triggers changes in saccadic amplitude or direction across trials. Numerous researches on this saccade adaptation have been conducted, but the level of inter-individual variability and consistency in saccade gain change and how it relates to increase- or decrease-amplitude paradigms is not fully described. We conducted experiments in four groups of 25 participants with 800 trials per participant, including 200 baseline trials and 200 recovery trials. We used four distinct double-step paradigms that differed by the intra-saccadic target-step leading to either a horizontal (Backward or Forward) or vertical (Upward or Downward) gain modulation. Across experiments 95% of the participants exhibited adaptation, revealing the consistency of this phenomenon. We observed strong inter-individual differences, both in the extent and rate of adaptation, which were not correlated with the individual baseline saccades characteristics. As previously reported, the rates of adaptation were higher for gain decrease than for gain increase experiments but the final extent of adaptation were similar. Our results also support the view that adaptation of oblique saccades occurs where the saccade command is represented as a vector. Finally, at the individual level, we did not observe systematic changes in the saccade metrics in relation to adaptation.

Consolidation alters motor sequence-specific distributed representations

Functional magnetic resonance imaging (fMRI) studies investigating the acquisition of sequential motor skills in humans have revealed learning-related functional reorganizations of the cortico-striatal and cortico-cerebellar motor systems accompanied with an initial hippocampal contribution. Yet, the functional significance of these activity-level changes remains ambiguous as they convey the evolution of both sequence-specific knowledge and unspecific task ability. Moreover, these changes do not specifically assess the occurrence of learning-related plasticity. To address these issues, we investigated local circuits tuning to sequence-specific information using multivariate distances between patterns evoked by consolidated or newly acquired motor sequences production. The results reveal that representations in dorsolateral striatum, prefrontal and secondary motor cortices are greater when executing consolidated sequences than untrained ones. By contrast, sequence representations in the hippocampus and dorsomedial striatum becomes less engaged. Our findings show, for the first time in humans, that complementary sequence-specific motor representations evolve distinctively during critical phases of skill acquisition and consolidation.

Thalamo-Cortical White Matter Underlies Motor Memory Consolidation via Modulation of Sleep Spindles in Young and Older Adults

Ample evidence suggests that consolidation of the memory trace associated with a newly acquired motor sequence is supported by thalamo-cortical spindle activity during subsequent sleep, as well as functional changes in a distributed cortico-striatal network. To date, however, no studies have investigated whether the structural white matter connections between these regions affect motor sequence memory consolidation in relation with sleep spindles. Here, we used diffusion weighted imaging (DWI) tractography to reconstruct the major fascicles of the cortico-striato-pallido-thalamo-cortical loop in both young and older participants who were trained on an explicit finger sequence learning task before and after a daytime nap. Thereby, this allowed us to examine whether post-learning sleep spindles measured using polysomnographic recordings interact with consolidation processes and this specific neural network. Our findings provide evidence corroborating the critical role of NREM2 thalamo-cortical sleep spindles in motor sequence memory consolidation, and show that the post-learning changes in these neurophysiological events relate specifically to white matter characteristics in thalamo-cortical fascicles. Moreover, we demonstrate that microstructure along this fascicle relates indirectly to offline gains in performance through an increase of spindle density over motor-related cortical areas. These results suggest that the integrity of thalamo-cortical projections, via their impact on sleep spindle generation, may represent one of the critical mechanisms modulating the expression of sleep-dependent offline gains following motor sequence learning in healthy adults.

Cortical neural modulation by previous trial outcome differentiates fast- from slow-learning rats on a visuomotor directional choice task

To better understand the neural cortical underpinnings that explain behavioral differences in learning rate, we recorded single-unit activity in primary motor (M1) and secondary motor (M2) areas while rats learned to perform a directional (left or right) operant visuomotor association task. Analysis of neural activity during the early portion of the cue period showed that neural modulation in the motor cortex was most strongly associated with two task factors: the previous trial outcome (success or error) and the current trial's directional choice (left or right). Furthermore, the fast learners, defined as those who had steeper learning curves and required fewer learning sessions to reach criterion performance, encoded the previous trial outcome factor more strongly than the directional choice factor. Conversely, the slow learners encoded directional choice more strongly than previous trial outcome. These differences in task factor encoding were observed in both the percentage of neurons and the neural modulation depth. These results suggest that fast learning is accompanied by a stronger component of previous trial outcome in the modulation representation present in motor cortex, which therefore may be a contributing factor to behavioral differences in learning rate. NEW & NOTEWORTHY We chronically recorded neural activity as rats learned a visuomotor directional choice task from a naive state. Learning rates varied. Single-unit neural modulation of two motor areas revealed that the fast learners encoded previous trial outcome more strongly than directional choice, whereas the reverse was true for slow learners. This finding provides novel evidence that rat learning rate is strongly correlated with the strength of neural modulation by previous trial outcome in motor cortex.

Individual Differences in Motor Noise and Adaptation Rate Are Optimally Related

Individual variations in motor adaptation rate were recently shown to correlate with movement variability or "motor noise" in a forcefield adaptation task. However, this finding could not be replicated in a meta-analysis of adaptation experiments. Possibly, this inconsistency stems from noise being composed of distinct components that relate to adaptation rate in different ways. Indeed, previous modeling and electrophysiological studies have suggested that motor noise can be factored into planning noise, originating from the brain, and execution noise, stemming from the periphery. Were the motor system optimally tuned to these noise sources, planning noise would correlate positively with adaptation rate, and execution noise would correlate negatively with adaptation rate, a phenomenon familiar in Kalman filters. To test this prediction, we performed a visuomotor adaptation experiment in 69 subjects. Using a novel Bayesian fitting procedure, we succeeded in applying the well-established state-space model of adaptation to individual data. We found that adaptation rate correlates positively with planning noise (β = 0.44; 95% HDI = [0.27 0.59]) and negatively with execution noise (β = -0.39; 95% HDI = [-0.50 -0.30]). In addition, the steady-state Kalman gain calculated from planning and execution noise correlated positively with adaptation rate (r = 0.54; 95% HDI = [0.38 0.66]). These results suggest that motor adaptation is tuned to approximate optimal learning, consistent with the "optimal control" framework that has been used to explain motor control. Since motor adaptation is thought to be a largely cerebellar process, the results further suggest the sensitivity of the cerebellum to both planning noise and execution noise.

Structural Plasticity in Adulthood with Motor Learning and Stroke Rehabilitation

The development of advanced noninvasive techniques to image the human brain has enabled the demonstration of structural plasticity during adulthood in response to motor learning. Understanding the basic mechanisms of structural plasticity in the context of motor learning is essential to improve motor rehabilitation in stroke patients. Here, we review and discuss the emerging evidence for motor-learning-related structural plasticity and the implications for stroke rehabilitation. In the clinical context, a few studies have started to assess the effects of rehabilitation on structural measures to understand recovery poststroke and additionally to predict intervention outcomes. Structural imaging will likely have a role in the future in providing measures that inform patient stratification for optimal outcomes.

Behavioral and neural effects of congruency of visual feedback during short-term motor learning

Visual feedback can facilitate or interfere with movement execution. Here, we describe behavioral and neural mechanisms by which the congruency of visual feedback during physical practice of a motor skill modulates subsequent performance gains. 18 healthy subjects learned to execute rapid sequences of right hand finger movements during fMRI scans either with or without visual feedback. Feedback consisted of a real-time, movement-based display of virtual hands that was either congruent (right virtual hand movement), or incongruent (left virtual hand movement yoked to the executing right hand). At the group level, right hand performance gains following training with congruent visual feedback were significantly higher relative to training without visual feedback. Conversely, performance gains following training with incongruent visual feedback were significantly lower. Interestingly, across individual subjects these opposite effects correlated. Activation in the Supplementary Motor Area (SMA) during training corresponded to individual differences in subsequent performance gains. Furthermore, functional coupling of SMA with visual cortices predicted individual differences in behavior. Our results demonstrate that some individuals are more sensitive than others to congruency of visual feedback during short-term motor learning and that neural activation in SMA correlates with such inter-individual differences.

Visuospatial function predicts one-week motor skill retention in cognitively intact older adults

Motor learning declines with aging, such that older adults retain less motor skill after practice compared to younger adults. However, it remains unclear if these motor learning declines are related to normal cognitive changes associated with aging. The purpose of this study was to examine which cognitive domains would best predict the amount of retention on a motor task one week after training in cognitively intact older adults. Twenty-one adults ages 65-84 years old were assessed with Repeatable Battery for the Assessment of Neuropsychological Status, which assesses five cognitive domains (immediate and delayed memory, visuospatial/constructional, language, and attention). Participants also completed one training session of a functional upper extremity task, and were re-tested one week later. Stepwise regression indicated that the visuospatial domain was the only significant predictor of how much skill participants retained over one week, with a visual perception subtest explaining the most variance. Results from this study support previous work reporting that older adults' capacity for motor learning can be probed with visuospatial tests. These tests may capture the structural or functional health of neural networks critical for skill learning within the aging brain, and provide valuable clinical insight about an individual's unique rehabilitation potential.

Electroencephalographic connectivity measures predict learning of a motor sequencing task

Individuals vary significantly with respect to rate and degree of improvement with motor practice. While the regions that underlie motor learning have been well described, neurophysiological factors underlying differences in response to motor practice are less well understood. The present study examined both resting-state and event-related EEG coherence measures of connectivity as predictors of response to motor practice on a motor sequencing task using the dominant hand. Thirty-two healthy young right-handed participants underwent resting EEG before motor practice. Response to practice was evaluated both across the single session of motor practice and 24 h later at a retention test of short-term motor learning. Behaviorally, the group demonstrated statistically significant gains both in single-session "motor improvement" and across-session "motor learning." A resting-state measure of whole brain coherence with primary motor cortex (M1) at baseline robustly predicted subsequent motor improvement (validated R² = 0.55) and motor learning (validated R² = 0.68) in separate partial least-squares regression models. Specifically, greater M1 coherence with left frontal-premotor cortex (PMC) at baseline was characteristic of individuals likely to demonstrate greater gains in both motor improvement and motor learning. Analysis of event-related coherence with respect to movement found the largest changes occurring in areas implicated in planning and preparation of movement, including PMC and frontal cortices. While event-related coherence provided a stronger prediction of practice-induced motor improvement (validated R² = 0.73), it did not predict the degree of motor learning (validated R² = 0.16). These results indicate that connectivity in the resting state is a better predictor of consolidated learning of motor skills. NEW & NOTEWORTHY Differences in response to motor training have significant societal implications across a lifetime of motor skill practice. By evaluating both resting-state and event-related measures of brain function, our findings highlight interindividual differences in brain connectivity providing unique insights into differences in response to motor training. These findings have wide-ranging implications in settings ranging from advanced professional motor training to rehabilitation after brain injury.

Learning about learning: Mining human brain sub-network biomarkers from fMRI data

Modeling the brain as a functional network can reveal the relationship between distributed neurophysiological processes and functional interactions between brain structures. Existing literature on functional brain networks focuses mainly on a battery of network properties in "resting state" employing, for example, modularity, clustering, or path length among regions. In contrast, we seek to uncover functionally connected subnetworks that predict or correlate with cohort differences and are conserved within the subjects within a cohort. We focus on differences in both the rate of learning as well as overall performance in a sensorimotor task across subjects and develop a principled approach for the discovery of discriminative subgraphs of functional connectivity based on imaging acquired during practice. We discover two statistically significant subgraph regions: one involving multiple regions in the visual cortex and another involving the parietal operculum and planum temporale. High functional coherence in the former characterizes sessions in which subjects take longer to perform the task, while high coherence in the latter is associated with high learning rate (performance improvement across trials). Our proposed methodology is general, in that it can be applied to other cognitive tasks, to study learning or to differentiate between healthy patients and patients with neurological disorders, by revealing the salient interactions among brain regions associated with the observed global state. The discovery of such significant discriminative subgraphs promises a better data-driven understanding of the dynamic brain processes associated with high-level cognitive functions.