Bilateral intracortical inhibition during unilateral motor preparation and sequence learning

Motor sequence learning gradually quickens reaction time, suggesting that sequence learning alters motor preparation processes. Interestingly, evidence has shown that preparing sequence movements decreases short intracortical inhibition (SICI) in the contralateral motor cortex (M1), but also that sequence learning alters motor preparation processes in both the contralateral and ipsilateral M1s. Therefore, one possibility is that sequence learning alters the SICI decreases occurring during motor preparation in bilateral M1s. To examine this, two novel hypotheses were tested: unilateral sequence preparation would decrease SICI in bilateral M1s, and sequence learning would alter such bilateral SICI responses. Paired-pulse transcranial magnetic stimulation was delivered over the contralateral and ipsilateral M1s to assess SICI in an index finger muscle during the preparation of sequences initiated by either the right index or little finger. In the absence of sequence learning, SICI decreased in both the contralateral and ipsilateral M1s during the preparation of sequences initiated by the right index finger, suggesting that SICI decreases in bilateral M1s during unilateral motor preparation. As sequence learning progressed, SICI decreased in the contralateral M1 whilst it increased in the ipsilateral M1. Moreover, these bilateral SICI responses were observed at the onset of motor preparation, suggesting that sequence learning altered baseline SICI levels rather than the SICI decreases occurring during motor preparation per se. Altogether, these results suggest that SICI responses in bilateral M1s reflect two motor processes: an acute decrease of inhibition during motor preparation, and a cooperative but bidirectional shift of baseline inhibition levels as sequence learning progresses.

Disentangling Effects of Memory Storage and Inter-articulator Coordination on Generalization in Speech Motor Sequence Learning

Generalization in motor control is the extent to which motor learning affects movements in situations different than those in which it originally occurred. Recent data on orofacial speech movements indicates that motor sequence learning generalizes to novel syllable sequences containing phonotactically illegal, but previously practiced, consonant clusters. Practicing an entire syllable, however, results in even larger performance gains compared to practicing just its clusters. These patterns of generalization could reflect language-general changes in phonological memory storage and/or inter-articulator coordination during motor sequence learning. To disentangle these factors, we conducted two experiments in which talkers intensively practiced producing novel syllables containing illegal onset and coda clusters over two consecutive days. During the practice phases of both experiments, we observed that, through repetition, talkers gradually produced the syllables with fewer errors, indicative of learning. After learning, talkers were tested for generalization to single syllables (Experiment 1) or syllable pairs (Experiment 2) that overlapped to varying degrees with the practiced syllables. Across both experiments, we found that performance improvements from practicing syllables with illegal clusters partially generalized to novel syllables that contained those clusters, but performance was more error prone if the clusters occurred in a different syllable position (onset versus coda) as in practice, demonstrating that inter-articulator coordination is contextually sensitive. Furthermore, changing the position of a cluster was found to be more deleterious to motor performance during the production of the second syllables in syllable pairs, which required talkers to store more phonological material in memory prior to articulation, compared to single syllables. This interaction effect reveals a complex interplay between memory storage and inter-articulator coordination on generalization in speech motor sequence learning.

Suppression of Motor Sequence Learning and Execution Through Anodal Cerebellar Transcranial Electrical Stimulation

Cerebellum (CB) and primary motor cortex (M1) have been associated with motor learning, with different putative roles. Modulation of task performance through application of transcranial direct current stimulation (TDCS) to brain structures provides causal evidence for their engagement in the task. Studies evaluating and comparing TDCS to these structures have provided conflicting results, however, likely due to varying paradigms and stimulation parameters. Here we applied TDCS to CB and M1 within the same experimental design, to enable direct comparison of their roles in motor sequence learning. We examined the effects of anodal TDCS during motor sequence learning in 60 healthy participants, randomly allocated to CB-TDCS, M1-TDCS, or Sham stimulation groups during a serial reaction time task. Key to the design was an equal number of repeated and random sequences. Reaction times (RTs) to implicitly learned and random sequences were compared between groups using ANOVAs and post hoc t-tests. A speed-accuracy trade-off was excluded by analogous analysis of accuracy scores. An interaction was observed between whether responses were to learned or random sequences and the stimulation group. Post hoc analyses revealed a preferential slowing of RTs to implicitly learned sequences in the group receiving CB-TDCS. Our findings provide evidence that CB function can be modulated through transcranial application of a weak electrical current, that the CB and M1 cortex perform separable functions in the task, and that the CB plays a specific role in motor sequence learning during implicit motor sequence learning.

Prefrontal stimulation as a tool to disrupt hippocampal and striatal reactivations underlying fast motor memory consolidation

BACKGROUND

Recent evidence suggests that hippocampal replay in humans support rapid motor memory consolidation during epochs of wakefulness interleaved with task practice.

OBJECTIVES/HYPOTHESES

The goal of this study was to test whether such reactivation patterns can be modulated with experimental interventions and in turn influence fast consolidation. We hypothesized that non-invasive brain stimulation targeting hippocampal and striatal networks via the prefrontal cortex would influence brain reactivation and the rapid form of motor memory consolidation.

METHODS

Theta-burst stimulation was applied to a prefrontal cluster functionally connected to both the hippocampus and striatum of young healthy participants before they learned a motor sequence task in a functional magnetic resonance imaging (fMRI) scanner. Neuroimaging data acquired during task practice and the interleaved rest epochs were analyzed to comprehensively characterize the effect of stimulation on the neural processes supporting fast motor memory consolidation.

RESULTS

Our results collectively show that active, as compared to control, theta-burst stimulation of the prefrontal cortex hindered fast motor memory consolidation. Converging evidence from both univariate and multivariate analyses of fMRI data indicate that active stimulation disrupted hippocampal and caudate responses during inter-practice rest, presumably altering the reactivation of learning-related patterns during the micro-offline consolidation episodes. Last, stimulation altered the link between the brain and the behavioral markers of the fast consolidation process.

CONCLUSION

These results suggest that stimulation targeting deep brain regions via the prefrontal cortex can be used to modulate hippocampal and striatal reactivations in the human brain and influence motor memory consolidation.

Involvement of the prefrontal cortex in motor sequence learning: A functional near-infrared spectroscopy (fNIRS) study

Our previous functional near-infrared spectroscopy (fNIRS) study on motor sequence learning (Polskaia et al., 2020) did not detect the same decrease in activity in the left dorsolateral prefrontal cortex (DLPFC) associated with movement automaticity, as reported by Wu et al. (2004). This was partly attributed to insufficient practice time to reach neural efficiency. Therefore, we sought to expand on our previous work to better understand the contribution of the prefrontal cortex (PFC) to motor sequence learning by examining learning across a longer period of time. Participants were randomly assigned to one of two groups: control or trained. fNIRS was acquired at three time points: pre-test, post-test, and retention. Participants performed four sequences (S1, S2, S3, and S4) of right-hand finger tapping. The trained group also underwent four days of practice of S1 and S2. No group differences in the left DLPFC and ventrolateral (VLPFC) were found between sessions for S1 and S2. Our findings revealed increased contribution from the right VLPFC in post-test for the trained group, which may reflect the active retrieval of explicit information from long-term memory. Our results suggest that despite additional practice time, explicit motor sequence learning requires the continued involvement of the PFC.

Differences in implicit motor learning between adults who do and do not stutter

Implicit learning allows us to acquire complex motor skills through repeated exposure to sensory cues and repetition of motor behaviours, without awareness or effort. Implicit learning is also critical to the incremental fine-tuning of the perceptual-motor system. To understand how implicit learning and associated domain-general learning processes may contribute to motor learning differences in people who stutter, we investigated implicit finger-sequencing skills in adults who do (AWS) and do not stutter (ANS) on an Alternating Serial Reaction Time task. Our results demonstrated that, while all participants showed evidence of significant sequence-specific learning in their speed of performance, male AWS were slower and made fewer sequence-specific learning gains than their ANS counterparts. Although there were no learning gains evident in accuracy of performance, AWS performed the implicit learning task more accurately than ANS, overall. These findings may have implications for sex-based differences in the experience of developmental stuttering, for the successful acquisition of complex motor skills during development by individuals who stutter, and for the updating and automatization of speech motor plans during the therapeutic process.

Brain white matter correlates of learning ankle tracking using a wearable device: importance of the superior longitudinal fasciculus II

Background

Wearable devices have been found effective in training ankle control in patients with neurological diseases. However, the neural mechanisms associated with using wearable devices for ankle training remain largely unexplored. This study aimed to investigate the ankle tracking performance and brain white matter changes associated with ankle tracking learning using a wearable-device system and the behavior–brain structure relationships in middle-aged and older adults.

Methods

Twenty-six middle-aged and older adults (48–75 years) participated in this study. Participants underwent 5-day ankle tracking learning with their non-dominant foot using a custom-built ankle tracking system equipped with a wearable sensor and a sensor-computer interface for real-time visual feedback and data acquisition. Repeated and random sequences of target tracking trajectories were both used for learning and testing. Ankle tracking performance, calculated as the root-mean-squared-error (RMSE) between the target and actual ankle trajectories, and brain diffusion spectrum MR images were acquired at baseline and retention tests. The general fractional anisotropy (GFA) values of eight brain white matter tracts of interest were calculated to indicate their integrity. Two-way (Sex × Time) mixed repeated measures ANOVA procedures were used to investigate Sex and Time effects on RMSE and GFA. Correlations between changes in RMSE and those in GFA were analyzed, controlling for age and sex.

Results

After learning, both male and female participants reduced the RMSE of tracking repeated and random sequences (both p < 0.001). Among the eight fiber tracts, the right superior longitudinal fasciculus II (R SLF II) was the only one which showed both increased GFA (p = 0.039) after learning and predictive power of reductions in RMSE for random sequence tracking with its changes in GFA [β = 0.514, R² change = 0.259, p = 0.008].

Conclusions

Our findings implied that interactive tracking movement learning using wearable sensors may place high demands on the attention, sensory feedback integration, and sensorimotor transformation functions of the brain. Therefore, the SLF II, which is known to perform these brain functions, showed corresponding neural plasticity after such learning, and its plasticity also predicted the behavioral gains. The SLF II appears to be a very important anatomical neural correlate involved in such learning paradigms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01042-2.

Single session transcranial direct current stimulation to the primary motor cortex fails to enhance early motor sequence learning in Parkinson's disease

INTRODUCTION

Explicit motor sequence learning is impaired in Parkinson's disease (PD). Transcranial direct current stimulation (tDCS) applied over the motor cortex in healthy can improve explicit motor learning, but comparative effects in PD are unknown. This exploratory study aims to examine the effect of single session tDCS on explicit motor sequence learning in PD.

METHODS

Thirty-three people with mild to moderate PD learnt a short and long finger tapping sequence with their right hand. Participants received either anodal, cathodal, or sham tDCS applied over the left primary motor cortex during task practice. Single- and dual-task finger tapping performance was assessed before and after task practice and functional near-infrared spectroscopy used to measure task related changes of oxygenated haemoglobin.

RESULTS

Finger tapping performance of short and long sequences under single-task conditions significantly improved following practice (p = 0.010 and p < 0.001, respectively). A condition-by-time interaction trend was observed for the long finger tapping sequence (p = 0.069) driven by improved performance in the cathodal (p = 0.001) and sham (p < 0.001) tDCS conditions, but not anodal tDCS (p = 0.198). The primary and premotor cortex and supplementary motor area were active in all tasks. No interaction or main effects were observed for task related changes of oxygenated haemoglobin.

CONCLUSIONS

PD patients retain the capacity to learn an explicit sequence of movements. Motor cortex tDCS does not improve explicit motor learning in PD and anodal tDCS may even suppress the rate of learning.

Preserved motor memory in Parkinson's disease

Patients with Parkinson's disease, who lose the dopaminergic projections to the striatum, are impaired in certain aspects of motor learning. Recent evidence suggests that, in addition to its role in motor performance, the striatum plays a key role in the memory of motor learning. Whether Parkinson's patients have impaired motor memory and whether motor memory is modulated by dopamine at the time of initial learning is unknown. To address these questions, we measured memory of a learned motor sequence in Parkinson's patients who were either On or Off their dopaminergic medications at the time of initial learning. We compared them to a group of older and younger controls. Contrary to our predictions, motor memory was not impaired in patients compared to older controls, and was not influenced by dopamine state at the time of initial learning. To probe post-learning consolidation processes, we also tested whether learning a new sequence shortly after learning the initial sequence would interfere with later memory. We found that, in contrast to younger adults, neither older adults nor patients were susceptible to this interference. These findings suggest that motor memory is preserved in Parkinson's patients and raise the possibility that motor memory in patients is supported by compensatory non-dopamine sensitive mechanisms. Furthermore, given the similar performance characteristics observed in the patients and older adults and the absence of an effect of dopamine, these results raise the possibility that aging and Parkinson's disease affect motor memory in similar ways.

Default mode and dorsal attention network involvement in visually guided motor sequence learning

Motor sequence learning (MSL) paradigms are often used to investigate the neural processes underlying the acquisition of complex motor skills. Behavioral and neuroimaging studies have indicated an early stage in which spatial learning is prominent and a late stage of automatized performance after multiple training periods. Functional magnetic resonance imaging (fMRI) studies yielded both decreased and increased activations of the sensorimotor and association areas. However, task-negative and task-positive intrinsic connectivity networks (ICNs), the default mode (DMN) and dorsal attention (DAN) networks involved in governing attention demands during various task conditions were not specifically addressed in most studies. In the present fMRI study, a visually guided MSL (VMSL) task was used for bringing roles of visuospatial and motor attention into foreground in order to investigate the role of attention-related ICNs in MSL. Seventeen healthy, right-handed participants completed training and test sessions of VMSL during fMRI on the 1st day. Then, after daily training for three consecutive days outside the scanner, they were re-tested during the 5th day's scanning session. When test session after early learning period was compared with training session, activation decrease was observed in the occipito-temporal fusiform cortex, while task-related suppression of DMN was reduced. Reduced deactivation after early learning was correlated with decreased error rates. After late learning stage we observed activation decreases in bilateral superior parietal lobules of task-positive DAN, dorsal precunei, and cerebellum. Reduced activity in left posterior parietal and right cerebellar regions were correlated with gains in speed, error rate, respectively. This dissociation in activity changes of DMN and DAN related areas suggests that DAN shows high contribution during both early and late MSL stages, possibly due to attention requirement for automatization of spatial and temporal aspects of motor sequence. In contrast, spatial learning occurring during early MSL stage was sufficient for releasing DMN resources.

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.

Alpha oscillations modulate premotor-cerebellar connectivity in motor learning: Insights from transcranial alternating current stimulation

Alpha oscillations (8-13 Hz) have been suggested to play an important role in dynamic neural processes underlying learning and memory. The goal of this study was to scrutinize the role of alpha oscillations in communication within a cortico-cerebellar network implicated in motor sequence learning. To this end, we conducted two EEG experiments using a serial reaction time task. In the first experiment, we explored changes in alpha power and cross-channel alpha coherence as subjects learned a motor sequence. We found a gradual decrease in spectral alpha power over left premotor cortex (PMC) and sensorimotor cortex (SM1) during learning blocks. In addition, alpha coherence between left PMC/SM1 and left cerebellar crus I was specifically decreased during sequence learning, possibly reflecting a functional decoupling in the broader motor learning network. In the second experiment in a different cohort, we applied 10Hz transcranial alternating current stimulation (tACS), a method shown to entrain local oscillatory activity, to left M1 (lM1) and right cerebellum (rCB) during sequence learning. We observed a tendency for diminished learning following rCB tACS compared to sham, but not following lM1 tACS. Learning-related alpha power following rCB tACS was increased in left PMC, possibly reflecting increase in local inhibitory neural activity. Importantly, learning-specific alpha coherence between left PMC and right cerebellar lobule VIIb was enhanced following rCB tACS. These findings provide strong evidence for a causal role of alpha oscillations in controlling information transfer in a premotor-cerebellar loop during motor sequence learning. Our findings are consistent with a model in which sequence learning may be impaired by enhancing premotor cortical alpha oscillation via external modulation of cerebellar oscillations.

White matter microstructural changes in short-term learning of a continuous visuomotor sequence

Efficient neural transmission is crucial for optimal brain function, yet the plastic potential of white matter (WM) has long been overlooked. Growing evidence now shows that modifications to axons and myelin occur not only as a result of long-term learning, but also after short training periods. Motor sequence learning (MSL), a common paradigm used to study neuroplasticity, occurs in overlapping learning stages and different neural circuits are involved in each stage. However, most studies investigating short-term WM plasticity have used a pre-post design, in which the temporal dynamics of changes across learning stages cannot be assessed. In this study, we used multiple magnetic resonance imaging (MRI) scans at 7 T to investigate changes in WM in a group learning a complex visuomotor sequence (LRN) and in a control group (SMP) performing a simple sequence, for five consecutive days. Consistent with behavioral results, where most improvements occurred between the two first days, structural changes in WM were observed only in the early phase of learning (d1-d2), and in overall learning (d1-d5). In LRNs, WM microstructure was altered in the tracts underlying the primary motor and sensorimotor cortices. Moreover, our structural findings in WM were related to changes in functional connectivity, assessed with resting-state functional MRI data in the same cohort, through analyses in regions of interest (ROIs). Significant changes in WM microstructure were found in a ROI underlying the right supplementary motor area. Together, our findings provide evidence for highly dynamic WM plasticity in the sensorimotor network during short-term MSL.

Beneficial effects of cerebellar tDCS on motor learning are associated with altered putamen-cerebellar connectivity: A simultaneous tDCS-fMRI study

Non-invasive transcranial stimulation of cerebellum and primary motor cortex (M1) has been shown to enhance motor learning. However, the mechanisms by which stimulation improves learning remain largely unknown. Here, we sought to shed light on the neural correlates of transcranial direct current stimulation (tDCS) during motor learning by simultaneously recording functional magnetic resonance imaging (fMRI). We found that right cerebellar tDCS, but not left M1 tDCS, led to enhanced sequence learning in the serial reaction time task. Performance was also improved following cerebellar tDCS compared to sham in a sequence production task, reflecting superior training effects persisting into the post-training period. These behavioral effects were accompanied by increased learning-specific activity in right M1, left cerebellum lobule VI, left inferior frontal gyrus and right inferior parietal lobule during cerebellar tDCS compared to sham. Despite the lack of group-level changes comparing left M1 tDCS to sham, activity increase in right M1, supplementary motor area, and bilateral middle frontal cortex, under M1 tDCS, was associated with better sequence performance. This suggests that lack of group effects in M1 tDCS relate to inter-individual variability in learning-related activation patterns. We further investigated how tDCS modulates effective connectivity in the cortico-striato-cerebellar learning network. Using dynamic causal modelling, we found altered connectivity patterns during both M1 and cerebellar tDCS when compared to sham. Specifically, during cerebellar tDCS, negative modulation of a connection from putamen to cerebellum was decreased for sequence learning only, effectively leading to decreased inhibition of the cerebellum. These results show specific effects of cerebellar tDCS on functional activity and connectivity in the motor learning network and may facilitate the optimization of motor rehabilitation involving cerebellar non-invasive stimulation.

A functional near-infrared spectroscopy (fNIRS) examination of how self-initiated sequential movements become automatic

The neural mechanisms underlying movement automaticity have been investigated using PET and fMRI and more recently functional near-infrared spectroscopy (fNIRS). As fNIRS is an emerging technique, the objective of the present study was to replicate the functional magnetic resonance imaging-related motor sequence findings as reported by Wu et al. (J Neurophysiol 91:1690-1698, https://doi.org/10.1152/jn.01052.2003, 2004) using fNIRS. Seventeen right-handed participants practiced self-initiated sequential finger movements of two lengths (4 and 12) until a level of automaticity was achieved. Automaticity was evaluated by performing a visual-letter-counting task concurrently with the sequential finger movements. Our data were unable to replicate the pre-to-post-practice decrease in cortical activity in the left dorsolateral prefrontal cortex for both motor sequence tasks. The findings did reveal increased contribution from the right hemisphere following learning. The observed lateralization is suggestive of explicit learning and the involvement of working memory in motor sequence production.

Testing enhances motor practice

We investigated how retrieval of a set of newly learned motor sequences influences subsequent learning of another set of motor sequences. In four experiments, retrieval reduced an acceleration of movement execution over subsequent study trials. This relative slowing-down was associated with better recall performance in a final memory test. Explicit retrievability of motor sequences benefited from longer study-trial response times (RTs), suggesting that retrieval caused more attentive encoding. The use of motor sequences requiring overt action during encoding allowed for this demonstration of a twofold forward effect of testing on encoding quality and on recall. Experiment 1 adopted a paradigm used in previous studies with verbal materials. Experiment 2 changed the test format to be less susceptible to interference. Experiments 3 and 4 additionally switched from a between-participants design to a within-participants design. These modifications did not affect the occurrence of the twofold forward effect of testing but enabled detecting a correlation between recall and study-trial performance that had been precluded by the strongly interference-dependent test format of the original paradigm. Our findings demonstrate an immediate learning benefit of testing. It enhances encoding in subsequent study trials.

Time-dependent motor memory representations in prefrontal cortex

How memories evolve over time is fundamental for understanding memory. Hippocampus-dependent episodic memories are generally assumed to undergo a time-dependent neural reorganization involving an increased reliance on neocortical areas. Yet, whether other forms of memory undergo a similar reorganization over time remains unclear. Here, we examined whether the neural underpinnings of motor sequence memories change over time. Participants were trained on a motor sequence learning task. Either 1d or 28d later, they performed a retention test for this task in the fMRI scanner. Sequence-specific motor memory was observed both 1d and 28d after initial training. Bayesian second-level fMRI analyses suggested a higher probability for task activity in the middle frontal gyrus and frontal pole 28d compared to 1d after initial motor learning. Searchlight representational similarity analysis indicated that areas in middle and superior frontal cortex were more involved in differentiating between multivariate activity patterns for old motor sequence memories and newly learned motor sequences in the 28d-group compared to the 1d-group. This increased involvement of lateral frontal areas during the task after 28 days was not paralleled by a decrease in those areas that were involved in performing the motor sequence retention task after 1d. These novel findings provide insights into how memories beyond the hippocampus evolve over time.

Glucocorticoid response to stress induction prior to learning is negatively related to subsequent motor memory consolidation

Hippocampal activity during early motor sequence learning is critical to trigger subsequent sleep-related consolidation processes. Based on previous evidence that stress-induced cortisol release modulates hippocampal activity, the current study investigates whether exposure to stress prior to motor sequence learning influences the ensuing learning and overnight consolidation process. Seventy-four healthy young adults were exposed to a stressor (i.e., the socially evaluated cold pressor test, SECPT) or a control procedure before initial training on a bimanual motor sequence learning task. Participants were retested on the motor task 24 h (including a night of sleep) after training to assess memory consolidation. Our results indicate that the SECPT, as compared to the control condition, induced significant physiological stress responses as evidenced by increased heart rate and blood pressure as well as elevated salivary cortisol concentrations. Cortisol concentration in the stress group reached peak levels immediately before and stayed significantly elevated for the full duration of initial motor learning before returning to baseline during the consolidation period. Stress induction prior to learning did not, on average, influence initial performance nor subsequent motor memory consolidation as indicated by similar overnight gains in performance in both groups. However, higher levels of stress-induced cortisol prior to training were correlated to smaller overnight gains in performance speed. These results indicate that the glucocorticoid response to a stressful encounter experienced prior to hippocampal-mediated motor learning is negatively related to subsequent memory consolidation processes.

Brain state flexibility accompanies motor-skill acquisition

Learning requires the traversal of inherently distinct cognitive states to produce behavioral adaptation. Yet, tools to explicitly measure these states with non-invasive imaging – and to assess their dynamics during learning – remain limited. Here, we describe an approach based on a distinct application of graph theory in which points in time are represented by network nodes, and similarities in brain states between two different time points are represented as network edges. We use a graph-based clustering technique to identify clusters of time points representing canonical brain states, and to assess the manner in which the brain moves from one state to another as learning progresses. We observe the presence of two primary states characterized by either high activation in sensorimotor cortex or high activation in a frontal-subcortical system. Flexible switching among these primary states and other less common states becomes more frequent as learning progresses, and is inversely correlated with individual differences in learning rate. These results are consistent with the notion that the development of automaticity is associated with a greater freedom to use cognitive resources for other processes. Taken together, our work offers new insights into the constrained, low dimensional nature of brain dynamics characteristic of early learning, which give way to less constrained, high-dimensional dynamics in later learning.

Transient synchronization of hippocampo-striato-thalamo-cortical networks during sleep spindle oscillations induces motor memory consolidation

Sleep benefits motor memory consolidation. This mnemonic process is thought to be mediated by thalamo-cortical spindle activity during NREM-stage2 sleep episodes as well as changes in striatal and hippocampal activity. However, direct experimental evidence supporting the contribution of such sleep-dependent physiological mechanisms to motor memory consolidation in humans is lacking. In the present study, we combined EEG and fMRI sleep recordings following practice of a motor sequence learning (MSL) task to determine whether spindle oscillations support sleep-dependent motor memory consolidation by transiently synchronizing and coordinating specialized cortical and subcortical networks. To that end, we conducted EEG source reconstruction on spindle epochs in both cortical and subcortical regions using novel deep-source localization techniques. Coherence-based metrics were adopted to estimate functional connectivity between cortical and subcortical structures over specific frequency bands. Our findings not only confirm the critical and functional role of NREM-stage2 sleep spindles in motor skill consolidation, but provide first-time evidence that spindle oscillations [11-17 Hz] may be involved in sleep-dependent motor memory consolidation by locally reactivating and functionally binding specific task-relevant cortical and subcortical regions within networks including the hippocampus, putamen, thalamus and motor-related cortical regions.

The effect of transcranial direct current stimulation on motor sequence learning and upper limb function after stroke

OBJECTIVE

To assess the impact of electrode arrangement on the efficacy of tDCS in stroke survivors and determine whether changes in transcallosal inhibition (TCI) underlie improvements.

METHODS

24 stroke survivors (3-124months post-stroke) with upper limb impairment participated. They received blinded tDCS during a motor sequence learning task, requiring the paretic arm to direct a cursor to illuminating targets on a monitor. Four tDCS conditions were studied (crossover); anodal to ipsilesional M1, cathodal to contralesional M1, bihemispheric, sham. The Jebsen Taylor hand function test (JTT) was assessed pre- and post-stimulation and TCI assessed as the ipsilateral silent period (iSP) duration using transcranial magnetic stimulation.

RESULTS

The time to react to target illumination reduced with learning of the movement sequence, irrespective of tDCS condition (p>0.1). JTT performance improved after unilateral tDCS (anodal or cathodal) compared with sham (p<0.05), but not after bihemispheric (p>0.1). There was no effect of tDCS on change in iSP duration (p>0.1).

CONCLUSIONS

Unilateral tDCS is effective for improving JTT performance, but not motor sequence learning.

SIGNIFICANCE

This has implications for the design of future clinical trials.

Motor sequence learning and the effect of context on transfer from part-to-whole and from whole-to-part

The present study attempts to characterize the contextual conditions (i.e., addition versus omission of elements) that enable or prevent transfer of an acquired skill. The effect of learning and transfer from part-to-whole and from whole-to-part was studied with the serial reaction time (SRT) task. In this study, two alternative sequences of the SRT task were utilized, a short (i.e., 'part') sequence consisting of six elements (ADBACD), and a long (i.e., 'whole') one consisting of 12 elements (BDCADBACDABC) in which the short sequence was embedded. Three groups participated in the study: one was trained with the 'whole' sequence and two with the 'part' sequence (differing in the number of initial training trials performed), for six blocks followed by a random block. Then, for an additional block, each group was divided into two subgroups, one which continued to practice the same sequence, while the other was transferred to the alternate sequence (i.e., 'part-to-whole' and 'whole-to-part'). Results indicated that the group that first practiced the 'whole' and then the 'part' sequence showed full transfer, while the other group showed only partial transfer from the 'part' to 'whole' sequence. The findings of the present study are inconsistent with Thorndike's principle of identical elements, and, instead, indicate that full transfer is enabled in spite of certain contextual changes (i.e., omissions), but only partial transfer is enabled when other changes are applied (i.e., additions).

Explicit motor sequence learning with the paretic arm after stroke

PURPOSE

Motor sequence learning is important for stroke recovery, but experimental tasks require dexterous movements, which are impossible for people with upper limb impairment. This makes it difficult to draw conclusions about the impact of stroke on learning motor sequences. We aimed to test a paradigm requiring gross arm movements to determine whether stroke survivors with upper limb impairment were capable of learning a movement sequence as effectively as age-matched controls.

MATERIALS AND METHODS

In this case-control study, 12 stroke survivors (10-138 months post-stroke, mean age 64 years) attempted the task once using their affected arm. Ten healthy controls (mean 66 years) used their non-dominant arm. A sequence of 10 movements was repeated 25 times. The variables were: time from target illumination until the cursor left the central square (onset time; OT), accuracy (path length), and movement speed.

RESULTS

OT reduced with training (p < 0.05) for both groups, with no change in movement speed or accuracy (p > 0.1). We quantified learning as the OT difference between the end of training and a random sequence; this was smaller for stroke survivors than controls (p = 0.015).

CONCLUSIONS

Stroke survivors can learn a movement sequence with their paretic arm, but demonstrate impairments in sequence specific learning. Implications for Rehabilitation Motor sequence learning is important for recovery of movement after stroke. Stroke survivors were found to be capable of learning a movement sequence with their paretic arm, supporting the concept of repetitive task training for recovery of movement. Stroke survivors showed impaired sequence specific learning in comparison with age-matched controls, indicating that they may need more repetitions of a sequence in order to re-learn movements. Further research is required into the effect of lesion location, time since stroke, hand dominance and gender on learning of motor sequences after stroke.

Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation

Sleep is necessary for the optimal consolidation of procedural learning, and in particular, for motor sequential skills. Motor sequence learning remains intact with age, but sleep-dependent consolidation is impaired, suggesting that memory deficits for procedural skills are specifically impacted by age-related changes in sleep. Age-related changes in spindles may be responsible for impaired motor sequence learning consolidation, but the morphological basis for this deficit is unknown. Here, we found that gray matter in the hippocampus and cerebellum was positively correlated with both sleep spindles and offline improvements in performance in young participants but not in older participants. These results suggest that age-related changes in gray matter in the hippocampus relate to spindles and may underlie age-related deficits in sleep-related motor sequence memory consolidation. In this way, spindles can serve as a biological marker for structural brain changes and the related memory deficits in older adults.

Consolidating behavioral and neurophysiologic findings to explain the influence of contextual interference during motor sequence learning

Motor sequence learning under high levels of contextual interference (CI) disrupts initial performance but supports delayed test and transfer performance when compared to learning under low CI. Integrating findings from early behavioral work and more recent experimental efforts that incorporated neurophysiologic measures led to a novel account of the role of CI during motor sequence learning. This account focuses on important contributions from two neural regions-the dorsal premotor area and the SMA complex-that are recruited earlier and more extensively during the planning of a motor sequence in a high CI context. It is proposed that activation of these regions is critical to early adaptation of sequence structure amenable to long-term storage. Moreover, greater CI enhances access to newly acquired motor sequence knowledge through (1) the emergence of temporary functional connectivity between neural sites previously described as crucial to successful long-term performance of sequential behaviors, and (2) heightened excitability of M1-a key constituent of the temporary coupled neural circuits, and the primary candidate for storage of motor memory.

The effect of anodal transcranial direct current stimulation on motor sequence learning in healthy individuals: A systematic review and meta-analysis

A large number of studies have indicated the effect of anodal transcranial direct current stimulation (a-tDCS) on the primary motor cortex (M1) during motor skill training. The effects of a-tDCS on different stages of motor sequence learning are not yet completely understood. The purpose of this meta-analysis was to determine the effects of single and multiple sessions of a-tDCS on two different tasks: the sequential finger tapping task/serial reaction time task (SEQTAP/SRTT) and the sequential visual isometric pinch task (SVIPT). We searched electronic databases for M1 a-tDCS studies. Thirteen studies met the inclusion criteria. The results indicate that application of multiple sessions of a-tDCS, compared to single session a-tDCS induced a significant improvement in skill in both SEQTAP/SRTT and SVIPT. Retention after a single day and multiple days of a-tDCS was statistically significant for the SEQTAP/SRTT task but not for SVIPT. Therefore, our findings suggest that application of M1 a-tDCS across the three or five consecutive days can be helpful to improve motor sequence learning.

Limits on movement integration in children: The concatenation of trained subsequences into composite sequences as a specific experience-triggered skill

Complex movement sequences may be easier to acquire in sub-segments. Nevertheless, the neuro-behavioral constraints on assembling short multi-element movement segments, acquired piecemeal and serially, into larger, composite units of action, are not clear. Here we examined the ability of children to combine movement subsequences into longer, composite, sequences. Eleven-year-olds were trained in the performance of two, 3-elements, finger-to-thumb opposition movement sequences and were tested, overnight, in the performance of composite, 6-elements, sequences. Two experiments were compared, differing only in whether or not a brief test for integration into a composite sequence was afforded immediately post-training. This composite sequence (Full) was a direct forward integration of the two subsequences, maintaining the order in which the two subsequences were trained. In both experiments, overnight performance of movement elements within the composite sequences was better than naive performance, but slower and less accurate compared to the performance of the identical movement elements in the context of the trained subsequences. Integration was as effective in the Full sequence as when the order between subsequences was switched (Reversed). However, the early test for subsequence integration was critical in inducing clear between-session ('offline') gains, as expressed in overnight performance, in both the Full and Reversed sequences. Without this brief experience in integration, no overnight gains were expressed in any of the 6-elements sequences. Moreover, the immediate post-training test resulted in a relative advantage of the Full and Reversed sequences over a 6-element sequence in which the order of the elements was mirror-reversed within each subsequence. Thus, training on subsequences may not spontaneously lead to an advantage in the performance of composite sequences, in children. However, an early brief experience with a composite sequence can suffice to trigger the establishment and consolidation of an integration routine. This routine is specific for the order of movement within the trained subsequences, but not for the order in which the subsequences were practiced.

Compensatory motor network connectivity is associated with motor sequence learning after subcortical stroke

Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke.

Maintaining vs. enhancing motor sequence memories: respective roles of striatal and hippocampal systems

It is now accepted that hippocampal- and striatal-dependent memory systems do not act independently, but rather interact during both memory acquisition and consolidation. However, the respective functional roles of the hippocampus and the striatum in these processes remain unknown. Here, functional magnetic resonance imaging (fMRI) was used in a daytime sleep/wake protocol to investigate this knowledge gap. Using a protocol developed earlier in our lab (Albouy et al., 2013a), the manipulation of an explicit sequential finger-tapping task, allowed us to isolate allocentric (spatial) and egocentric (motor) representations of the sequence, which were supported by distinct hippocampo- and striato-cortical networks, respectively. Importantly, a sleep-dependent performance enhancement emerged for the hippocampal-dependent memory trace, whereas performance was maintained for the striatal-dependent memory trace, irrespective of the sleep condition. Regression analyses indicated that the interaction between these two systems influenced subsequent performance improvements. While striatal activity was negatively correlated with performance enhancement after both sleep and wakefulness in the allocentric representation, hippocampal activity was positively related to performance improvement for the egocentric representation, but only if sleep was allowed after training. Our results provide the first direct evidence of a functional dissociation in consolidation processes whereby memory stabilization seems supported by the striatum in a time-dependent manner whereas memory enhancement seems linked to hippocampal activity and sleep-dependent processes.

Delineating the cortico-striatal-cerebellar network in implicit motor sequence learning

Theoretical models and experimental evidence suggest that cortico-striatal-cerebellar networks play a crucial role in mediating motor sequence learning. However, how these different regions interact in order to mediate learning is less clear. In the present fMRI study, we used dynamic causal modeling to investigate effective connectivity within the cortico-striatal-cerebellar network while subjects performed a serial reaction time task. Using Bayesian model selection and family wise inference, we show that the cortico-cerebellar loop had higher model evidence than the cortico-striatal loop during motor learning. We observed significant negative modulatory effects on the connections from M1 to cerebellum bilaterally during learning. The results suggest that M1 causes the observed decrease in activity in the cerebellum as learning progresses. The current study stresses the significant role that the cerebellum plays in motor learning as previously suggested by fMRI studies in healthy subjects as well as behavioral studies in patients with cerebellar dysfunction. These results provide important insight into the neural mechanisms underlying motor learning.