Motor Sequence Research Articles

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.

Dissipation of reactive inhibition is sufficient to explain post-rest improvements in motor sequence learning

The prevailing hypothesis for observed post-rest motor reaction time improvements is offline consolidation. In the present study, we present evidence for an alternate account involving the accrual and dissipation of reactive inhibition. Four groups of participants (N = 159) performed a finger-tapping task involving either massed (30 s per trial) or spaced (10 s per trial) training, and with one of two break intervals between each trial: 10 s or 30 s. After 360 s of training in each group, there was a 300 s rest period followed by a final test on the same task. The results show that the smaller the ratio of break time to on-task trial time during training, the larger the improvement in reaction time after the rest period. Those results are fully consistent with a model that assumes no facilitating offline consolidation, but rather learning that is concurrent with performance and reactive inhibition that builds during performance and dissipates during breaks.

A neural network model for timing control with reinforcement.

How do humans and animals perform trial-and-error learning when the space of possibilities is infinite? In a previous study, we used an interval timing production task and discovered an updating strategy in which the agent adjusted the behavioral and neuronal noise for exploration. In the experiment, human subjects proactively generated a series of timed motor outputs. Positive or negative feedback was provided after each response based on the timing accuracy. We found that the sequential motor timing varied at two temporal scales: long-term correlation around the target interval due to memory drifts and short-term adjustments of timing variability according to feedback. We have previously described these two key features of timing variability with an augmented Gaussian process, termed reward-sensitive Gaussian process (RSGP). In a nutshell, the temporal covariance of the timing variable was updated based on the feedback history to recreate the two behavioral characteristics mentioned above. However, the RSGP was mainly descriptive and lacked a neurobiological basis of how the reward feedback can be used by a neural circuit to adjust motor variability. Here we provide a mechanistic model and simulate the process by borrowing the architecture of recurrent neural networks (RNNs). While recurrent connection provided the long-term serial correlation in motor timing, to facilitate reward-driven short-term variations, we introduced reward-dependent variability in the network connectivity, inspired by the stochastic nature of synaptic transmission in the brain. Our model was able to recursively generate an output sequence incorporating internal variability and external reinforcement in a Bayesian framework. We show that the model can generate the temporal structure of the motor variability as a basis for exploration and exploitation trade-off. Unlike other neural network models that search for unique network connectivity for the best match between the model prediction and observation, this model can estimate the uncertainty associated with each outcome and thus did a better job in teasing apart adjustable task-relevant variability from unexplained variability. The proposed artificial neural network model parallels the mechanisms of information processing in neural systems and can extend the framework of brain-inspired reinforcement learning (RL) in continuous state control.

Suppression-induced forgetting of motor sequences

Two experiments examined the effects of deliberately suppressing retrieval of motor sequences on their later recall, in the think/no-think paradigm (Anderson & Green, 2001). After several motor sequences had been associated with individual cues through repeated practice cycles, a subset of these sequences was retrieved in response to their respective cues (think trials), whereas other sequences were suppressed. In such no-think trials, cues were shown but participants were instructed to withhold the associated motor response and to suppress its recollection. We found that suppressing retrieval impaired later memory performance for the suppressed sequences in comparison to items that were not cued at all after their initial training (baseline sequences). Suppression impaired later sequence recall and sequence speed although in different ways depending on the training level: with higher initial training of sequences (Experiment 1), suppression impaired reaction time, but not recall accuracy; with lower initial training (Experiment 2), suppression reduced recall accuracy. Reaction time analyses revealed a consistent slowing of movement execution for suppressed sequences. These findings show that inhibitory control processes engaged during retrieval suppression can influence memory representations of motor actions, by not only reducing their accessibility but also by affecting their execution, once retrieved.

Neural Correlates of Dual-Task Processing following Motor Sequence Learning: A Functional Near-Infrared Spectroscopy (fNIRS) Study

The current study used functional near-infrared spectroscopy (fNIRS) to examine cerebral oxygenation changes in the prefrontal cortex (PFC) associated with dual-task processing before and after motor sequence learning. Participants performed self-initiated sequential finger movements that were 4 and 12 units in length with a visual letter-counting task. After practice, dual-task sequence-4 performance revealed decreased activity in the right dorsolateral PFC, medial PFC, and orbitofrontal cortex. However, dual-task sequence-12 performance revealed increased activity in the right ventrolateral PFC when compared to the left hemisphere. The findings suggest that dual-task interference was reduced following practice for dual-task sequence-4. The results also suggest that increased right hemisphere activation is needed to maintain performance when the primary sequential task (e.g., dual-task sequence-12) has a high level of difficulty.

INTERMANUAL TRANSFER OF RETRIEVAL-INDUCED FORGETTING IN MOTOR SEQUENCE LEARNING

Previous studies have found that Retrieval-Induced Forgetting (RIF) affects motor-sequence learning on the keyboard, but no studies have examined whether practicing with a different effector induces forgetting. This experiment examined whether left-hand practice causes competition and induces forgetting of other right-hand learned, but unpracticed keyboard sequences using mouse sequences as memory baseline. This experiment used two primary ways through which right hand movements can be translated onto left hands, transpositional translation (same visual representations but different fingers) and mirrored translation (same fingers but reversed visual representations) of right-hand sequences on left hand to examine whether they induced forgetting differently. RIF appeared in all three between-subject groups such that the overall recall accuracy for practiced keyboard sequences (Rp+) was higher than that of the unpracticed sequences, and the recall accuracy for unpracticed keyboard sequences (Rp-) was lower than that of the unpracticed mouse sequences (Nrp). However, RIF did not vary across groups: right hand, left-hand transposition, and left-hand mirror practice all induced forgetting with no interaction with sequence types. The present findings are consistent with an abstract representation of sequential finger movements that can be translated across hands such that retrieval-practice on a different hand could induce forgetting of motor sequences originally learned on the other.

Initialization of latent space coordinates via random linear projections for learning robotic sensory-motor sequences.

Robot kinematic data, despite being high-dimensional, is highly correlated, especially when considering motions grouped in certain primitives. These almost linear correlations within primitives allow us to interpret motions as points drawn close to a union of low-dimensional affine subspaces in the space of all motions. Motivated by results of embedding theory, in particular, generalizations of the Whitney embedding theorem, we show that random linear projection of motor sequences into low-dimensional space loses very little information about the structure of kinematic data. Projected points offer good initial estimates for values of latent variables in a generative model of robot sensory-motor behavior primitives. We conducted a series of experiments in which we trained a Recurrent Neural Network to generate sensory-motor sequences for a robotic manipulator with 9 degrees of freedom. Experimental results demonstrate substantial improvement in generalization abilities for unobserved samples during initialization of latent variables with a random linear projection of motor data over initialization with zero or random values. Moreover, latent space is well-structured such that samples belonging to different primitives are well separated from the onset of the training process.

A single bout of aerobic exercise modulates motor learning performance and cortical excitability in humans

BackgroundEvidence indicates beneficial effects of aerobic exercise on motor learning performance, which might be caused by the impact of aerobic exercise on cortical excitability. It is thus suggested that physiological effects of aerobic exercise on cortical excitability determine the effects of aerobic exercise on motor learning. Nevertheless, respective results usually come from independent studies, and a prove of the causal relationship between neurophysiological and motor learning effects is still missing. This study aims to explore the impact of a single bout of aerobic exercise on brain physiology and motor learning, and the association between these phenomena in humans MethodThe study was conducted in a cross-over design. In twenty healthy subjects, cortical excitability and motor learning were assessed before and after a single bout of aerobic exercise or a control intervention ResultsThe results show that aerobic exercise improved motor sequence learning and enhanced cortical excitability in humans. Furthermore, a correlation between the exercise-dependent alteration of cortical excitability (short intracortical inhibition, which is determined primarily by the GABAergic system) and improvement of motor learning has been found DiscussionThe study found motor learning performance-improving effects of aerobic exercise, and these results might be explained by an exercised-caused alteration of cortical excitability, especially a reduction of GABA activity.

Neural basis of implicit motor sequence learning: Modulation of cortical power.

Implicit sequence learning describes the acquisition of serially ordered movements and sequentially structured cognitive information, that occurs without awareness. Theta, alpha and beta cortical oscillations are present during implicit motor sequence learning, but their role in this process is unclear. The current study addressed this gap in the literature. A total of 50 healthy adults aged between 19 and 37 years participated in the study. Implicit motor sequence learning was examined using the Serial Reaction Time task where participants unknowingly repeat a sequence of finger movements in response to a visual stimulus. Sequence learning was examined by comparing reaction times and oscillatory power between sequence trials and a set of control trials comprising random stimulus presentations. Electroencephalography was recorded as participants completed the task. Analyses of the behavioral data revealed participants learnt the sequence. Analyses of oscillatory activity, using permutation testing, revealed sequence learning was associated with a decrease in theta band (4-7Hz) power recorded over frontal and central electrode sites. Sequence learning effects were not observed in the alpha (7-12 Hz) or beta bands (12-20 Hz). Even though alpha and beta power modulations have long been associated with executing a motor response, it seems theta power is a correlate of sequence learning in the manual domain. Theta power modulations on the serial reaction time task may reflect disengagement of attentional resources, either promoting or occurring as a consequence of implicit motor sequence learning.

Does the hippocampus exhibit offline reactivation of neural activity following motor sequence learning?

Memory consolidation in the declarative memory domain is known to be supported by the replay or reactivation of learning-related hippocampal activity during subsequent offline epochs (i.e., during post-encoding rest). Examinations into an analogous hippocampal reactivation process following motor learning have, until recently, been non-existent. This gap in the literature has been fueled by the traditional – yet outdated - view that the hippocampus is not involved in motor learning. Here, we discuss recent research in the motor memory domain that provides evidence in support of hippocampal reactivation following motor sequence learning. We conclude by highlighting several areas that warrant examination in future research, including experimentally manipulating post-learning hippocampal reactivation in an effort to enhance the motor memory consolidation process.

The effect of the reciprocal method associated with sequential and random motor skills implementation exercises in learning skill performance in football

The aim of the research is to identify the effect of the reciprocal method associated with the sequential motor skills implementation exercises in learning skill performance in football. The researchers assumed that there were statistically significant differences between the pre-test and the post-test in learning some basic football skills for the three groups and in favor of the post-test. There are statistical differences between the post-test for the three research groups experimental and control) and in favor of the second group. The researchers used the experimental method for its suitability and the nature of the problem. The sample included (30) students. They were chosen at random from the community of (58) students from Qaraqosh Preparatory School for Boys for the academic year (2019-2020). They were divided into three equal groups, one-group share (10) students. The first group studied in the reciprocal method associated with sequential exercises and the second group studied in the reciprocal style associated with random exercises, while the control group studied in the usual way, then the experiment was applied and its implementation took (6) weeks up to two educational units per week for one group, the (SPSS) system was used to statistically process the data. The researchers concluded: The effectiveness of the experimental approach used according to sequential and random exercises by reciprocal teaching, with the superiority of reciprocal teaching associated with random exercises.

The effect of educational games according to the stages of the complete kinetic sequence to develop some physical abilities and the achievement of junior long jump players

Progress and performance to the best level is the goal of educational games according to the stages of the complete motor sequence, so we need to apply the principles of learning and its correct methods, which must be effective and brief at the same time. And the research community was identified for long jump players in the Specialized School for Talent Care for the 2022 sports season in Baghdad, which numbered (12 jumpers). To the most important conclusions, as the results showed a marked superiority between the tribal and remote measurements, the effect of educational games on the stages of the kinetic sequence, to develop some physical abilities and the achievement of the junior long jump players for the experimental group and in favor of the dimensional measurement.

Somatosensory targeted memory reactivation enhances motor performance via hippocampal-mediated plasticity.

Increasing evidence suggests that reactivation of newly acquired memory traces during postlearning wakefulness plays an important role in memory consolidation. Here, we sought to boost the reactivation of a motor memory trace during postlearning wakefulness (quiet rest) immediately following learning using somatosensory targeted memory reactivation (TMR). Using functional magnetic resonance imaging, we examined the neural correlates of the reactivation process as well as the effect of the TMR intervention on brain responses elicited by task practice on 24 healthy young adults. Behavioral data of the post-TMR retest session showed a faster learning rate for the motor sequence that was reactivated as compared to the not-reactivated sequence. Brain imaging data revealed that motor, parietal, frontal, and cerebellar brain regions, which were recruited during initial motor learning, were specifically reactivated during the TMR episode and that hippocampo-frontal connectivity was modulated by the reactivation process. Importantly, the TMR-induced behavioral advantage was paralleled by dynamical changes in hippocampal activity and hippocampo-motor connectivity during task practice. Altogether, the present results suggest that somatosensory TMR during postlearning quiet rest can enhance motor performance via the modulation of hippocampo-cortical responses.

Complementary Roles of Primate Dorsal Premotor and Pre-Supplementary Motor Areas to the Control of Motor Sequences.

We are able to temporally organize multiple movements in a purposeful manner in everyday life. Both the dorsal premotor (PMd) area and pre-supplementary motor area (pre-SMA) are known to be involved in the performance of motor sequences. However, it is unclear how each area differentially contributes to controlling multiple motor sequences. To address this issue, we recorded single-unit activity in both areas while monkeys (one male, one female) performed sixteen motor sequences. Each sequence comprised either a series of two identical movements (repetition) or two different movements (nonrepetition). The sequence was initially instructed with visual signals but had to be remembered thereafter. Here, we showed that the activity of single neurons in both areas transitioned from reactive- to predictive encoding while motor sequences were memorized. In the memory-guided trials, in particular, the activity of PMd cells preferentially represented the second movement (2M) in the sequence leading to a reward generally regardless of the first movement (1M). Such activity frequently began even before the 1M in a prospective manner, and was enhanced in nonrepetition sequences. Behaviorally, a lack of the activity enhancement often resulted in premature execution of the 2M. In contrast, cells in pre-SMA instantiated particular sequences of actions by coordinating switching or nonswitching movements in sequence. Our findings suggest that PMd and pre-SMA play complementary roles within behavioral contexts: PMd preferentially controls the movement that leads to a reward rather than the sequence per se, whereas pre-SMA coordinates all elements in a sequence by integrating temporal orders of multiple movements.SIGNIFICANCE STATEMENT Although both dorsal premotor (PMd) area and pre-supplementary motor area (pre-SMA) are involved in the control of motor sequences, it is not clear how these two areas contribute to coordination of sequential movements differently. To address this issue, we directly compared neuronal activity in the two areas recorded while monkeys memorized and performed multiple motor sequences. Our findings suggest that PMd preferentially controls the final action that ultimately leads to a reward in a prospective manner, whereas the pre-SMA coordinates switching among multiple actions within the context of the sequence. Our findings are of significance to understand the distinct roles for motor-related areas in the planning and executing motor sequences and the pathophysiology of apraxia and/or Parkinson's diseases that disables skilled motor actions.

The online and offline effects of changing movement timing variability during training on a finger-opposition task

In motor learning tasks, there is mixed evidence for whether increased task-relevant variability in early learning stages leads to improved outcomes. One problem is that there may be a connection between skill level and motor variability, such that participants who initially have more variability may also perform worse on the task, so will have more room to improve. To avoid this confound, we experimentally manipulated the amount of movement timing variability (MTV) during training to test whether it improves performance. Based on previous studies showing that most of the improvement in finger-opposition tasks comes from optimizing the relative onset time of the finger movements, we used auditory cues (beeps) to guide the onset times of sequential movements during a training session, and then assessed motor performance after the intervention. Participants were assigned to three groups that either: (a) followed a prescribed random rhythm for their finger touches (Variable MTV), (b) followed a fixed rhythm (Fixed control MTV), or (c) produced the entire sequence following a single beep (Unsupervised control MTV). While the intervention was successful in increasing MTV during training for the Variable group, it did not lead to improved outcomes post-training compared to either control group, and the use of fixed timing led to significantly worse performance compared to the Unsupervised control group. These results suggest that manipulating MTV through auditory cues does not produce greater learning than unconstrained training in motor sequence tasks.

Dissecting motor skill acquisition: Spatial coordinates take precedence.

Practicing a previously unknown motor sequence often leads to the consolidation of motor chunks, which enable its accurate execution at increasing speeds. Recent imaging studies suggest the function of these structures to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We found that optimal motor skill acquisition prioritizes the storage of the spatial features of the sequence in memory over its rapid execution early in training, as proposed by Hikosaka in 1999. This process, seemingly diminished in older adults, was partially restored by anodal transcranial direct current stimulation over the motor cortex, as shown by a sharp improvement in accuracy and an earlier yet gradual emergence of motor chunks. These results suggest that the emergence of motor chunks is preceded by the storage of the sequence in memory but is not its direct consequence; rather, these structures depend on, and result from, motor practice.

Attentional Demand of a Movement Sequence Guided by Visual-Spatial and by Motor Representations

The objective of the experiment was to assess the change in attentional demands of a movement sequence guided by visual-spatial and motor representations across practice sessions in a dual-task probe paradigm. Participants were randomly assigned to either a 1-day or 2-day practice group. Following acquisition of the motor sequence task, participants first conducted a retention test and then four inter-manual transfer tests under single and dual-task conditions. The probe task was a simple reaction time. The inter-manual transfer tests, consisting of a mirror and non-mirror test, examined the development of the motor and visual-spatial representation, respectively. The results indicated that both representations guided the movement sequence and required attention. The attentional demands did not change with additional practice.

Whole-body sensorimotor skill learning in football players: No evidence for motor transfer effects.

Besides simple movement sequences, precise whole-body motor sequences are fundamental for top athletic performance. It has long been questioned whether athletes have an advantage when learning new whole-body motor sequences. In a previous study, we did not find any superior learning or transfer effects of strength and endurance athletes in a complex whole-body serial reaction time task (CWB-SRTT). In the present study, we aimed to extend this research by increasing the overlap of task requirements between CWB-SRTT and a specific sports discipline. For this purpose, we assessed differences between football players and non-athletes during motor sequence learning using CWB-SRTT. 15 non-athletes (CG) and 16 football players (FG) performed the CWB-SRTT over 2 days separated by one week. Median reaction times and movement times were analyzed as well as differences in sequence-specific CWB-SRTT learning rates and retention. Our findings did not reveal any differences in sequence-specific or non-sequence-specific improvement, nor retention rates between CG and FG. We speculate that this might relate to a predominately cognitive-induced learning effect during CWB-SRTT which negates the assumed motor advantage of the football players.

Deep brain stimulation of the ventrointermediate nucleus of the thalamus to treat essential tremor improves motor sequence learning.

The network of brain structures engaged in motor sequence learning comprises the same structures as those involved in tremor, including basal ganglia, cerebellum, thalamus, and motor cortex. Deep brain stimulation (DBS) of the ventrointermediate nucleus of the thalamus (VIM) reduces tremor, but the effects on motor sequence learning are unknown. We investigated whether VIM stimulation has an impact on motor sequence learning and hypothesized that stimulation effects depend on the laterality of electrode location. Twenty patients (age: 38–81 years; 12 female) with VIM electrodes implanted to treat essential tremor (ET) successfully performed a serial reaction time task, varying whether the stimuli followed a repeating pattern or were selected at random, during which VIM‐DBS was either on or off. Analyses of variance were applied to evaluate motor sequence learning performance according to reaction times (RTs) and accuracy. An interaction was observed between whether the sequence was repeated or random and whether VIM‐DBS was on or off (F[1,18] = 7.89, p = .012). Motor sequence learning, reflected by reduced RTs for repeated sequences, was greater with DBS on than off (T[19] = 2.34, p = .031). Stimulation location correlated with the degree of motor learning, with greater motor learning when stimulation targeted the lateral VIM (n = 23, ρ = 0.46; p = .027). These results demonstrate the beneficial effects of VIM‐DBS on motor sequence learning in ET patients, particularly with lateral VIM electrode location, and provide evidence for a role for the VIM in motor sequence learning.

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

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