Learning from the other limb's experience: sharing the 'trained' M1 representation of the motor sequence knowledge

Interlimb transfer of sequential motor learning between upper and lower effectors

BACKGROUND

Interlimb transfer of sequential motor learning (SML) refers to the positive influence of prior experiences in performing the same sequential movements using different effectors. Despite evidence from intermanual SML, and while most daily living activities involve interlimb cooperation and coordination between the four limbs, nothing is known about bilateral SML transfer between the upper and lower limbs.

RESEARCH QUESTION

We examined the transfer of bilateral SML from the upper to the lower limbs and vice versa.

METHODS

Twenty-four participants had to learn an initial bilateral SML task using the upper limbs and then performed the same sequence using the lower limbs during a transfer SML task. They performed the reversed situation 1 month apart. The performance was evaluated at the beginning and the end of both initial and transfer SML practice phases.

RESULTS

Significant and reciprocal transfer gains in performance were observed regardless of the effectors. Greater transfer gains in performance were observed at the beginning of the transfer SML from the lower to the upper limbs (44 %) but these gains vanished after practice with the transfer effectors (5 %). Although smaller gains were initially achieved in the transfer of SML from the upper to the lower limbs (15 %), these gains persisted and remained significant (9 %) after practice with the transfer effectors.

SIGNIFICANCE

Our results provide evidence of a reciprocal and asymmetrical interlimb transfer of bilateral SML between the upper and lower limbs. These findings could be leveraged as a relevant strategy in the context of sports and functional rehabilitation.

Neural correlates of transfer of learning in motor coordination tasks: role of inhibitory and excitatory neurometabolites

We aimed to investigate transfer of learning, whereby previously acquired skills impact new task learning. While it has been debated whether such transfer may yield positive, negative, or no effects on performance, very little is known about the underlying neural mechanisms, especially concerning the role of inhibitory (GABA) and excitatory (Glu) (measured as Glu + glutamine (Glx)) neurometabolites, as measured by magnetic resonance spectroscopy (MRS). Participants practiced a bimanual coordination task across four days. The Experimental group trained a task variant with the right hand moving faster than the left (Task A) for three days and then switched to the opposite variant (Task B) on Day4. The control group trained Task B across four days. MRS data were collected before, during, and after task performance on Day4 in the somatosensory (S1) and visual (MT/V5) cortex. Results showed that both groups improved performance consistently across three days. On Day4, the Experimental group experienced performance decline due to negative task transfer while the control group continuously improved. GABA and Glx concentrations obtained during task performance showed no significant group-level changes. However, individual Glx levels during task performance correlated with better (less negative) transfer performance. These findings provide a first window into the neurochemical mechanisms underlying task transfer.

Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Performance and learning rate prediction models development in FLS and RAS surgical tasks using electroencephalogram and eye gaze data and machine learning

OBJECTIVE

This study explored the use of electroencephalogram (EEG) and eye gaze features, experience-related features, and machine learning to evaluate performance and learning rates in fundamentals of laparoscopic surgery (FLS) and robotic-assisted surgery (RAS).

METHODS

EEG and eye-tracking data were collected from 25 participants performing three FLS and 22 participants performing two RAS tasks. Generalized linear mixed models, using L1-penalized estimation, were developed to objectify performance evaluation using EEG and eye gaze features, and linear models were developed to objectify learning rate evaluation using these features and performance scores at the first attempt. Experience metrics were added to evaluate their role in learning robotic surgery. The differences in performance across experience levels were tested using analysis of variance.

RESULTS

EEG and eye gaze features and experience-related features were important for evaluating performance in FLS and RAS tasks with reasonable results. Residents outperformed faculty in FLS peg transfer (p value = 0.04), while faculty and residents both excelled over pre-medical students in the FLS pattern cut (p value = 0.01 and p value < 0.001, respectively). Fellows outperformed pre-medical students in FLS suturing (p value = 0.01). In RAS tasks, both faculty and fellows surpassed pre-medical students (p values for the RAS pattern cut were 0.001 for faculty and 0.003 for fellows, while for RAS tissue dissection, the p value was less than 0.001 for both groups), with residents also showing superior skills in tissue dissection (p value  = 0.03).

CONCLUSION

Findings could be used to develop training interventions for improving surgical skills and have implications for understanding motor learning and designing interventions to enhance learning outcomes.

Effects of Sleep on Language and Motor Consolidation: Evidence of Domain General and Specific Mechanisms

The current study explores the effects of time and sleep on the consolidation of a novel language learning task containing both item-specific knowledge and the extraction of grammatical regularities. We also compare consolidation effects in language and motor sequence learning tasks, to ask whether consolidation mechanisms are domain general. Young adults learned to apply plural inflections to novel words based on morphophonological rules embedded in the input, and learned to type a motor sequence using a keyboard. Participants were randomly assigned into one of two groups, practicing each task during either the morning or evening hours. Both groups were retested 12 and 24 hours post-training. Performance on frequent trained items in the language task stabilized only following sleep, consistent with a hippocampal mechanism for item-specific learning. However, regularity extraction, indicated by generalization to untrained items in the linguistic task, as well as performance on motor sequence learning, improved 24 hours post-training, irrespective of the timing of sleep. This consolidation process is consistent with a frontostriatal skill-learning mechanism, common across the language and motor domains. This conclusion is further reinforced by cross-domain correlations at the individual level between improvement across 24 hours in the motor task and in the low-frequency trained items in the linguistic task, which involve regularity extraction. Taken together, our results at the group and individual levels suggest that some aspects of consolidation are shared across the motor and language domains, and more specifically, between motor sequence learning and grammar learning.

Neural mechanisms mediating cross education: With additional considerations for the ageing brain

CALVERT, G.H.M., and CARSON, R.G. Neural mechanisms mediating cross education: With additional considerations for the ageing brain. NEUROSCI BIOBEHAV REV 21(1) XXX-XXX, 2021. - Cross education (CE) is the process whereby a regimen of unilateral limb training engenders bilateral improvements in motor function. The contralateral gains thus derived may impart therapeutic benefits for patients with unilateral deficits arising from orthopaedic injury or stroke. Despite this prospective therapeutic utility, there is little consensus concerning its mechanistic basis. The precise means through which the neuroanatomical structures and cellular processes that mediate CE may be influenced by age-related neurodegeneration are also almost entirely unknown. Notwithstanding the increased incidence of unilateral impairment in later life, age-related variations in the expression of CE have been examined only infrequently. In this narrative review, we consider several mechanisms which may mediate the expression of CE with specific reference to the ageing CNS. We focus on the adaptive potential of cellular processes that are subserved by a specific set of neuroanatomical pathways including: the corticospinal tract, corticoreticulospinal projections, transcallosal fibres, and thalamocortical radiations. This analysis may inform the development of interventions that exploit the therapeutic utility of CE training in older persons.

The neural correlates of intermanual transfer

Intermanual transfer of motor learning is a form of learning generalization that leads to behavioral advantages in various tasks of daily life. It might also be useful for rehabilitation of patients with unilateral motor deficits. Little is known about neural structures and cognitive processes that mediate intermanual transfer. Previous studies have suggested a role for primary motor cortex (M1) and the supplementary motor area (SMA). Here, we investigated the functional neuroanatomy of intermanual transfer with a special emphasis on functional connectivity within the motor network and between motor regions and attentional networks, including the fronto-parietal executive control network and visual attention networks. We designed a finger tapping task, in which young, heathy subjects trained the non-dominant left hand in the MRI scanner. Behaviorally, transfer of sequence learning was observed in most cases, independently of the trained hand's performance. Pre- and post-training functional connectivity patterns of cortical motor seeds were investigated using generalized psychophysiological interaction analyses. Transfer was correlated with the strength of connectivity between the left premotor cortex and structures within the dorsal attention network (superior parietal cortex, left middle temporal gyrus) and executive control network (right prefrontal regions) during pre-training, relative to post-training. Changes in connectivity within the motor network, and more particularly between trained and untrained M1, as well as between the SMA and untrained M1, correlated with transfer after training. Together, these results suggest that the interplay between attentional, executive and motor networks may support processes leading to transfer, whereas, following training, transfer translates into increased connectivity within the motor network.

Interlimb Transfer of Reach Adaptation Does Not Require an Intact Corpus Callosum: Evidence from Patients with Callosal Lesions and Agenesis

Generalization of sensorimotor adaptation across limbs, known as interlimb transfer, is a well-demonstrated phenomenon in humans, yet the underlying neural mechanisms remain unclear. Theoretical models suggest that interlimb transfer is mediated by interhemispheric transfer of information via the corpus callosum. We thus hypothesized that lesions of the corpus callosum, especially to its midbody connecting motor, supplementary motor, and premotor areas of the two cerebral hemispheres, would impair interlimb transfer of sensorimotor adaptation. To test this hypothesis, we recruited three patients: two rare stroke patients with recent, extensive callosal lesions including the midbody and one patient with complete agenesis. A prismatic adaptation paradigm involving unconstrained arm reaching movements was designed to assess interlimb transfer from the prism-exposed dominant arm (DA) to the unexposed non-dominant arm (NDA) for each participant. Baseline results showed that spatial performance of each patient did not significantly differ from controls, for both limbs. Further, each patient adapted to the prismatic perturbation, with no significant difference in error reduction compared with controls. Crucially, interlimb transfer was found in each patient. The absolute magnitude of each patient’s transfer did not significantly differ from controls. These findings show that sensorimotor adaptation can transfer across limbs despite extensive lesions or complete absence of the corpus callosum. Therefore, callosal pathways connecting homologous motor, premotor, and supplementary motor areas are not necessary for interlimb transfer of prismatic reach adaptation. Such interlimb transfer could be mediated by transcallosal splenium pathways (connecting parietal, temporal and visual areas), ipsilateral cortico-spinal pathways or subcortical structures such as the cerebellum.

Motor skill learning with impaired transfer by children with developmental coordination disorder

BACKGROUND

DSM-5 criteria for developmental coordination disorder (DCD) emphasize deficits in the acquisition and execution of coordinated motor skills. Previous studies of motor skill learning in DCD suggest deficits in the execution of motor skills but do not reveal a deficit in learning new skills, possibly because of the heterogeneity of motor deficits in DCD.

AIM

In light of the high prevalence of handwriting difficulties among children with DCD, the current study compared motor skill learning in 5-6-year-old children with DCD and their peers using a grapho-motor learning task that resembles a letter-writing practice.

METHODS

Thirty-two boys, 16 with DCD, learned to produce a new "letter" formed by connecting three dots. Training, following-day consolidation, 1-week post-training retention, and far-transfer to a no-dot condition were tested.

RESULTS

Children with DCD exhibited rates of learning similar to those of their peers, but with overall poorer performance, replicating previous findings. Contrary to reports of intact skill transfer following a consolidation period in DCD, impaired transfer of the learned symbol was observed.

CONCLUSIONS

These findings may explain some of the motor difficulties experienced by children with DCD as well as contribute to the discussion on mechanisms involved in skill learning in these children.

Use-Dependent Plasticity in Human Primary Motor Hand Area: Synergistic Interplay Between Training and Immobilization

Training and immobilization are powerful drivers of use-dependent plasticity in human primary motor hand area (M1_HAND). In young right-handed volunteers, corticomotor representations of the left first dorsal interosseus and abductor digiti minimi muscles were mapped with neuronavigated transcranial magnetic stimulation (TMS) to elucidate how finger-specific training and immobilization interact within M1_HAND. A first group of volunteers trained to track a moving target on a smartphone with the left index or little finger for one week. Linear sulcus shape-informed TMS mapping revealed that the tracking skill acquired with the trained finger was transferred to the nontrained finger of the same hand. The cortical representations of the trained and nontrained finger muscle converged in proportion with skill transfer. In a second group, the index or little finger were immobilized for one week. Immobilization alone attenuated the corticomotor representation and pre-existing tracking skill of the immobilized finger. In a third group, the detrimental effects of finger immobilization were blocked by concurrent training of the nonimmobilized finger. Conversely, immobilization of the nontrained fingers accelerated learning in the adjacent trained finger during the first 2 days of training. Together, the results provide novel insight into use-dependent cortical plasticity, revealing synergistic rather than competitive interaction patterns within M1_HAND.

Explaining Individual Differences in Motor Behavior by Intrinsic Functional Connectivity and Corticospinal Excitability

Motor performance varies substantially between individuals. This variance is rooted in individuals' innate motor abilities, and should thus have a neural signature underlying these differences in behavior. Could these individual differences be detectable with neural measurements acquired at rest? Here, we tested the hypothesis that motor performance can be predicted by resting motor-system functional connectivity and motor-evoked-potentials (MEPs) induced by non-invasive brain stimulation. Twenty healthy right handed subjects performed structural and resting-state fMRI scans. On a separate day, MEPs were measured using transcranial magnetic stimulation (TMS) over the contrateral primary motor cortex (M1). At the end of the session, participants performed a finger-tapping task using their left non-dominant hand. Resting-state functional connectivity between the contralateral M1 and the supplementary motor area (SMA) predicted motor task performance, indicating that individuals with stronger resting M1-SMA functional connectivity exhibit better motor performance. This prediction was neither improved nor reduced by the addition of corticospinal excitability to the model. These results confirm that motor behavior can be predicted from neural measurements acquired prior to task performance, primarily relying on resting functional connectivity rather than corticospinal excitability. The ability to predict motor performance from resting neural markers, provides an opportunity to identify the extent of successful rehabilitation following neurological damage.

Weaker Inter-hemispheric and Local Functional Connectivity of the Somatomotor Cortex During a Motor Skill Acquisition Is Associated With Better Learning

Recently, an increasing interest in investigating interactions between brain regions using functional connectivity (FC) methods has shifted the initial focus of cognitive neuroimaging research from localizing functional circuits based on task activation to mapping brain networks based on intrinsic FC dynamics. Leveraging the advantages of the latter approach, it has been shown that despite primarily invariant intrinsic organization of the large-scale functional networks, interactions between and within these networks significantly differ between various behavioral and cognitive states. These differences presumably indicate transient reconfiguration of functional connections-an instantaneous process that flexibly mediates and calibrates human behavior according to momentary demands of the environment. Nevertheless, the specificity of these reconfigured FC patterns to the task at hand and their relevance to adaptive processes during learning remain elusive. To address this knowledge gap, we investigated (1) to what extent FC within the somatomotor network is reconfigured during motor skill practice, and (2) how these changes are related to learning. We applied a seed-driven FC approach to data collected during a continuous task-free condition, so-called resting state, and during a motor sequence learning task using functional magnetic resonance imaging. During the task, participants repeatedly performed a short five-element sequence with their non-dominant (left) hand. As predicted, such unimanual sequence production was associated with lateralized activation of the right somatomotor cortex (SMC). Using this "active" region as a seed, here we show that unimanual performance of the motor sequence relies on functional segregation between the two SMC and selective integration between the "active" SMC and supplementary motor area. Whereas, greater segregation between the two SMC was associated with gains in performance rate, greater segregation within the "active" SMC itself was associated with more consistent performance by the end of training. Nether the resting-state FC patterns within the somatomotor network nor their relative modulation by the task state predicted these behavioral benefits of learning. Our results suggest that task-induced FC changes reflect reconfiguration of the connectivity patterns within the somatomotor network rather than a simple amplification or silencing of its intrinsic dynamics. Such reconfiguration not only supports motor behavior but may also predict learning.

fMRIPrep: a robust preprocessing pipeline for functional MRI

Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad-hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available. The complexity of these workflows has snowballed with rapid advances in acquisition and processing. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for fMRI data. FMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing with no manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software-testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection. Additionally, fMRIPrep introduces less uncontrolled spatial smoothness than commonly used preprocessing tools. FMRIPrep equips neuroscientists with a high-quality, robust, easy-to-use and transparent preprocessing workflow, which can help ensure the validity of inference and the interpretability of their results.

Explaining the neural activity distribution associated with discrete movement sequences: Evidence for parallel functional systems

To explore the effects of practice we scanned participants with fMRI while they were performing four-key unfamiliar and familiar sequences, and compared the associated activities relative to simple control sequences. On the basis of a recent cognitive model of sequential motor behavior (C-SMB), we propose that the observed neural activity would be associated with three functional networks that can operate in parallel and that allow (a) responding to stimuli in a reaction mode, (b) sequence execution using spatial sequence representations in a central-symbolic mode, and (c) sequence execution using motor chunk representations in a chunking mode. On the basis of this model and findings in the literature, we predicted which neural areas would be active during execution of the unfamiliar and familiar keying sequences. The observed neural activities were largely in line with our predictions, and allowed functions to be attributed to the active brain areas that fit the three above functional systems. The results corroborate C-SMB’s assumption that at advanced skill levels the systems executing motor chunks and translating key-specific stimuli are racing to trigger individual responses. They further support recent behavioral indications that spatial sequence representations continue to be used.

Strong Functional Connectivity among Homotopic Brain Areas Is Vital for Motor Control in Unilateral Limb Movement

The mechanism underlying brain region organization for motor control in humans remains poorly understood. In this functional magnetic resonance imaging (fMRI) study, right-handed volunteers were tasked to maintain unilateral foot movements on the right and left sides as consistently as possible. We aimed to identify the similarities and differences between brain motor networks of the two conditions. We recruited 18 right-handed healthy volunteers aged 25 ± 2.3 years and used a whole-body 3T system for magnetic resonance (MR) scanning. Image analysis was performed using SPM8, Conn toolbox and Brain Connectivity Toolbox. We determined a craniocaudally distributed, mirror-symmetrical modular structure. The functional connectivity between homotopic brain areas was generally stronger than the intrahemispheric connections, and such strong connectivity led to the abovementioned modular structure. Our findings indicated that the interhemispheric functional interaction between homotopic brain areas is more intensive than the interaction along the conventional top-down and bottom-up pathways within the brain during unilateral limb movement. The detected strong interhemispheric horizontal functional interaction is an important aspect of motor control but often neglected or underestimated. The strong interhemispheric connectivity may explain the physiological phenomena and effects of promising therapeutic approaches. Further accurate and effective therapeutic methods may be developed on the basis of our findings.