Learning Of Movement Sequences Research Articles

Dancing without seeing: The influence of vision on movement sequence learning and motor imagery in dance

ABSTRACT Dance is commonly taught through model observation, aided by verbal and gestural cues. Trained dancers are also capable of learning dance movements from verbal instructions in the absence of a visual model, using elaborate multimodal movement representations in long-term memory acquired through training. The role of vision in this situation remains unclear. To investigate the influence of vision on dance sequence learning from verbal instruction, we conducted an online study with 76 professional-level dancers. Participants filmed themselves while learning and subsequently recalling and reproducing a dance phrase from spoken verbal instructions presented as pre-recorded audio. They were randomly assigned to one of two conditions: closing their eyes and wearing a blindfold or keeping their eyes open during learning. As a measure of learning success, recall performance was evaluated with quantitative movement criteria. Motor imagery during learning and recall was assessed via self-report questionnaires. Results showed no differences between the two conditions in recall performance or motor imagery; however, external and kinaesthetic motor imagery quality and quantity showed large to medium positive correlations with recall performance. The findings suggest that vision may not be crucial for successful learning of movement sequences from verbal instructions alone. Motor imagery, however, could be a powerful tool in dance learning as it may enhance memory for movement sequences. Further research should focus on the use of imagery (especially dynamic imagery) in dance during different phases of movement learning and recall under varying sensory and task-based (artistic) conditions.

Relationship Between Intelligence and Complex Motor Skills in Children With and Without Developmental Dyslexia

The study investigates the relation between developmental dyslexia, IQ and complex motor skills involving some cognitive and executive functions. The mechanisms underlying the co-existence of disabilities related to reading and writing on the one hand and motor skills on the other hand, still need to be clarified. In the current study it was hypothesised that the level of intelligence may contribute to complex motor skills in dyslexia. The study involved 58 students with developmental dyslexia (age 9.08 yrs; SD = .06) and 50 students constituting a control group (age 9.09 yrs; SD = .06). The measurements were performed using WISC-R, two subtests from the Dyslexia 3 Test, and four complex motor tasks. Children with dyslexia present problems in complex motor tasks, which involved learning of movement sequences and mental rotation. This finding may support the cerebellar deficit hypothesis in dyslexia. Complex motor skills are significantly related to children’s intelligence level or to the interaction of intelligence and dyslexia. Child’s intelligence explains from 7.5% to 35% of the variance in complex motor skills.

Movement Sequence Learning: Cognitive Processing Demands to Develop a Response Structure.

An experiment was designed to investigate the impact of a dual-task on the response structure of a 16-element movement sequence. The primary task was to move a lever to targets sequentially presented horizontally on the screen by elbow extension/flexion movements. The secondary task was a simple reaction time task triggered by moving the lever through targets at the middle and the end of the sequence. Participants were permitted to acquire the movement sequence on one day, and to perform the sequence on a second day under single-task and dual-task conditions. The results of the acquisition phase indicated that participants increased their performance over practice. Day 2 analysis indicated that performance of the repeated sequence was not deteriorated by the dual-task. This finding indicated that the response structure of the movement sequence performance was stable with regard to the secondary task. The current results are partially consistent with the theoretical assumption of an abstract representation for movement sequence execution.

The Cognitive Status of Older Adults: Do Reduced Time Constraints Enhance Sequence Learning?

Research has indicated that older adults perform movement sequences more slowly than young adults. The purpose of the present experiment was to compare movement sequence learning in young and older adults when the time to perform the sequence was extended, and how the elderly’s cognitive status (Montreal Cognitive Assessment [MoCA]) interacted with sequence learning. The task was to minimize the difference between a target sequence pattern and the sequence produced by elbow extension-flexion movements. On Day 1, participants (28 young adults; 28 older adults) practiced the sequence under two time windows: 1300 ms or 2000 ms. On Day 2, retention performance and the cognitive status were assessed. The results demonstrated that young adults performed superior compared to older adults. Additional time to perform the sequence did not improve retention performance for the older adults. The correlation between the error score and the MoCA score of r = –.38 (p < .05) in older adults indicated that a better cognitive status was associated with performance advantages in sequence learning.

Deconstructing skill learning and its physiological mechanisms

Acquiring complex motor skills involves learning a number of distinct motor components. Two fundamental elements that constitute a skill are the internal representation (i.e., the calibration of a sensorimotor map) and the sequence of movements needed to execute the task. Learning each of these likely rely on different neural substrates such as the cerebellum and primary motor cortex (M1), and physiological mechanisms. However, the specific neurophysiological processes underlying the acquisition of these components remains poorly understood. Here we used non-invasive brain stimulation to identify distinct physiological contributions arising from the cerebellum and M1 associated with learning the internal representation and the sequence of movements to execute a skill. Experiment one evaluated neurophysiological markers of the cerebellum and M1 while participants learned a sensorimotor map. Participants learned to calibrate the appropriate motor outputs to interact with a new device, prior to learning a new motor skill. We found that plastic changes in the cerebellum, but not in M1, are linked to learning the internal representation. Experiment two assessed the same neurophysiological markers while participants learned a sequence of movements, independent of acquiring a novel sensorimotor map. Here, both M1 LTP-like plasticity and cerebellar plasticity mediated movement sequence learning. Our findings indicate that learning the different components that will constitute a motor skill engages multiple nodes of a brain network in a concerted manner. In addition, it calls into question the expectation that targeting specific brain regions, such as M1, with brain stimulation to augment complex skill learning will have positive results.

Sequence learning in Parkinson's disease: Focusing on action dynamics and the role of dopaminergic medication

Previous studies on movement sequence learning in Parkinson's disease (PD) have produced mixed results. A possible explanation for the inconsistent findings is that some studies have taken dopaminergic medication into account while others have not. Additionally, in previous studies the response modalities did not allow for an investigation of the action dynamics of sequential movements as they unfold over time. In the current study we investigated sequence learning in PD by specifically considering the role of medication status in a sequence learning task where mouse movements were performed. The focus on mouse movements allowed us to examine the action dynamics of sequential movement in terms of initiation time, movement time, movement accuracy, and velocity. PD patients performed the sequence learning task once on their regular medication, and once after overnight withdrawal from their medication. Results showed that sequence learning as reflected in initiation times was impaired when PD patients performed the task ON medication compared to OFF medication. In contrast, sequence learning as reflected in the accuracy of movement trajectories was enhanced when performing the task ON compared to OFF medication. Our findings suggest that while medication enhances execution processes of movement sequence learning, it may at the same time impair planning processes that precede actual execution. Overall, the current study extends earlier findings on movement sequence learning in PD by differentiating between various components of performance, and further refines previous dopamine overdose effects in sequence learning.

The activity in the contralateral primary motor cortex, dorsal premotor and supplementary motor area is modulated by performance gains.

There is growing experimental evidence that the engagement of different brain areas in a given motor task may change with practice, although the specific brain activity patterns underlying different stages of learning, as defined by kinematic or dynamic performance indices, are not well understood. Here we studied the change in activation in motor areas during practice on sequences of handwriting-like trajectories, connecting four target points on a digitizing table “as rapidly and as accurately as possible” while lying inside an fMRI scanner. Analysis of the subjects' pooled kinematic and imaging data, acquired at the beginning, middle, and end of the training period, revealed no correlation between the amount of activation in the contralateral M1, PM (dorsal and ventral), supplementary motor area (SMA), preSMA, and Posterior Parietal Cortex (PPC) and the amount of practice per-se. Single trial analysis has revealed that the correlation between the amount of activation in the contralateral M1 and trial mean velocity was partially modulated by performance gains related effects, such as increased hand motion smoothness. Furthermore, it was found that the amount of activation in the contralateral preSMA increased when subjects shifted from generating straight point-to-point trajectories to their spatiotemporal concatenation into a smooth, curved trajectory. Altogether, our results indicate that the amount of activation in the contralateral M1, PMd, and preSMA during the learning of movement sequences is correlated with performance gains and that high level motion features (e.g., motion smoothness) may modulate, or even mask correlations between activity changes and low-level motion attributes (e.g., trial mean velocity).

Representations in a recurrent network model of motor sequence learning reveal unified view of procedural memory consolidation and structure learning

Event Abstract Back to Event Representations in a recurrent network model of motor sequence learning reveal unified view of procedural memory consolidation and structure learning Quan Wang1*, Constantin A. Rothkopf1 and Jochen Triesch1 1 Johann Wolfgang Goethe University, Frankfurt Institute for Advanced Studies (FIAS), Germany Humans can improve their performance in procedural movement tasks through practice, but such motor learning has shown puzzling and seemingly contradictory results. On the one hand, a wide variety of proactive and retroactive interference effects have been observed when multiple tasks have to be learned. On the other hand, some studies have reported facilitation and transfer of learning between different tasks, sometimes based on abstract structure similarities. Here we show how these different phenomena can all be understood based on generic learning principles in a recurrent neural network model. Specifically, we consider a self-organizing recurrent neural network model whose activity and connectivity is shaped by three plasticity mechanisms: spike timing-dependent plasticity (STDP), intrinsic plasticity, and synaptic scaling [1]. The network receives stimulus-specific input and is connected to a layer of motor neurons mediating the movement sequences through a winner-take-all mechanism. We use this network to model a series of experiments on movement sequence learning using a single set of parameters in all simulations. The network learns to carry out the correct movement sequences over trials and reproduces differences in behavior between training schedules such as blocked vs. random training. The network also shows striking similarity to human performance in tasks with similar training sequences but different training times. Previously we have shown the agreement between the output of the network and psychophysical performance across several tasks and training schedules with a single set of parameters for the recurrent network. The current work presents a detailed analysis of the underlying changes in the neuronal representations of the motor sequences across learning. Mutual information, PCA analysis of network activity, and measures of neuronal selectivity for parts of the motor sequences reveal how input representations and the trajectories of neural activity change with training. Finally, we provide testable experimental predictions. Thus, we show how training schedule and task similarity interact to produce a rich set of interference and facilitation effects thereby unifying procedural memory consolidation and structure learning in a recurrent network model with multiple plasticity mechanisms. Acknowledgements First authorship is shared between QW and CR. This research was funded in part by the BMBF through the Bernstein Focus: Neurotechnology in Frankfurt and by the European Union through FP7 project IM-CLeVeR.

Dopamine D2 receptor density in the limbic striatum is related to implicit but not explicit movement sequence learning

A large body of literature suggests that motor sequence learning involves dopamine-modulated plastic processes in the basal ganglia. Sequence learning can occur both implicitly, without conscious awareness and intention to learn, and explicitly, i.e., under conscious control. Here, we investigated whether individual differences in implicit and explicit sequence learning of movement sequences in a group of 15 healthy participants are related to dopamine D2 receptor densities in functional subregions of the striatum. Sequence learning was assessed using the serial reaction time task, and measures of implicit and explicit knowledge were estimated using a process dissociation procedure. Correlation analyses were performed between these measures and D2 receptor densities, which had been measured previously with positron emission tomography. Striatal D2 densities were negatively related to measures of sequence learning. In the limbic subregion, D2 densities were specifically related to implicit but not explicit learning. These findings suggest that individual differences in striatal DA function underlie differences in sequence learning ability and support that implicit and explicit sequence learning depend on partly distinct neural circuitry. The findings are also in line with the general view that implicit learning systems are evolutionarily primitive and tend to rely more on phylogenetically old neural circuitry than does explicit learning and cognition.

Short article: Effects of interlimb practice on coding and learning of movement sequences

An interlimb practice paradigm was designed to determine the role that visual-spatial (Cartesian) and motor (joint angles, activation patterns) coordinates play in the coding and learning of complex movement sequences. Participants practised a 16-element movement sequence by moving a lever to sequentially presented targets with one limb on Day 1 and the contralateral limb on Day 2. Practice involved the same sequence with either the same visual-spatial or motor coordinates on the two days. A unilateral practice condition (control) was also tested where both coordinate systems were changed but the same limb was used. Retention tests were conducted on Day 3. Regardless of the order in which the limbs were used during practice, results indicated that keeping the visual-spatial coordinates the same during acquisition resulted in superior retention. This provides strong evidence that the visual-spatial code plays a dominant role in complex movement sequences, and this code is represented in an effector-independent manner.

Eye movements are not a prerequisite for learning movement sequence timing through observation

The present experiment examined learning of a three-segment movement sequence using physical or observational practice, and whether permitting eye movements to be made during observation is a prerequisite for learning such a movement sequence. Specifically, participants were required to move a mouse cursor through a three-segment movement sequence in order to satisfy one of three movement time goals (800, 1000, 1200 ms). A yoked-participant design was used in which a physical practice group acted as a learning model, which was viewed simultaneously by two groups that carried out different observational practice procedures. An observation group was permitted to move their eyes whilst observing the model, whereas the fixation group was instructed to maintain fixation on a central target. The difference between pre-test and post-test data indicated that all the three experimental groups significantly altered their timing accuracy, variability and movement kinematics over practice, while the control group’s behaviour was unchanged. These data indicate that movement time as well as the underlying movement control was learned following observation of a movement with or without an explicit contribution from eye movements, albeit to a lesser extent during the final segment of the sequence when compared to the physical practice group. The implication is that while similar processes might normally be involved in physical and observational practice, information afforded by eye movements during observation (e.g., efference copy and eye proprioception) is not necessary for movement sequence learning.

Performing movement sequences with knowledge of results under different visual conditions in adults with Down syndrome

The purpose of this study was to examine the learning of movement sequences in individuals with Down syndrome under different visual information conditions. 10 adults with Down syndrome and 14 neurologically typical adults performed a sequence of movements under two different visual information conditions: full visual feedback of the limb and environment and no visual feedback of the limb. Participants were given knowledge of results of their total movement time after each trial. The entire task was presented as a game and movement time information was given as a "score" after each trial. Participants were also given verbal encouragement throughout the task. As expected, individuals with Down syndrome had significantly slower reaction and movement times than neurologically typical participants. Interestingly, however, mean reaction and movement time was not affected by the visual condition, in either group. Participants with Down syndrome improved their performance over the presented trials, in both visual information conditions. These findings indicate that providing knowledge of results of movement performance can facilitate the performance and coordination of movement sequences even under conditions where visual information of the moving limb is restricted.

Human brain activation accompanying explicitly directed movement sequence learning.

We examined brain activation patterns occurring during the production and encoding of a motor sequence. Participants performed a variant of the serial reaction-time task under two conditions. The first condition was designed to foster the engagement of explicit mechanisms of knowledge acquisition. The second condition was intended to encourage the engagement of implicit learning mechanisms that would be more typical of the standard serial reaction-time task. In the first condition, the acquisition of explicit knowledge about an 8-element ordered sequence led to a significant and rapid decline in reaction time. By contrast, the second condition, the task in which a sequence was presented unbeknownst to participants, did not yield changes in reaction time. Several brain regions, including prefrontal cortex, superior and inferior parietal lobules, and cerebellum, exhibited explicit learning-related activation. The prefrontal cortex and inferior parietal lobules increased their levels of activation between the beginning and end of the experiment, while primary motor, primary sensory, and cerebellar cortex decreased their levels of activation from the beginning to the end of the experiment. We propose a model in which two processes, a learning-related increase and a habituation process might interact to produce the activation patterns observed during movement sequence acquisition. In short, the prefrontal cortex and inferior parietal lobule together direct and recruit superior parietal lobule and cerebellum to encode and perform the sequence. The increased activation in prefrontal cortex and inferior parietal lobule may represent the activity of a working memory circuit that functions in the acquisition and recall of sequence information.

Predicting sensory events. The role of the cerebellum in motor learning.

There is growing evidence that the cerebellum is involved in the implicit learning of movement sequences. On the serial reaction time (RT) task patients with cerebellar lesions fail to demonstrate normal decreases in RT and we have shown a similar effect in monkeys with bilateral cerebellar lesions. However, it is not clear if this impairment is unique to sequence learning or whether the cerebellum is also involved in the learning of discrete responses to predictable visual targets. We investigated this possibility in another group of monkeys with bilateral lesions of the cerebellum centred on the lateral nuclei. Three animals were pre-operatively trained to make rapid manual responses to a single target appearing on a touch-sensitive VDU screen. In one condition, a target could appear at any of three possible locations (spatially unpredictable). In a second condition the target always appeared in the same place (spatially predictable). A third condition was similar to the second except that the onset of the target was temporally predictable whereas in the previous conditions this parameter was randomized. Following the lesions, the RT savings earned on the conditions in which the cues were predictable were abolished. This was despite a lack of significant increase in movement times. The results imply that the animals were either failing to predict the spatial location or time of presentation of the target, or that they were unable to use their prediction to improve their reaction times. The function of the cerebellum in motor sequence learning may therefore be part of a more general operation in learning to prepare responses to predictable sensory events.

Children's self-regulated learning of movement sequences.

The purpose of this study was to determine whether developmental differences exist in childrens' use of self-regulatory strategies while learning supra-memory-span movement sequences. Grade 1 and Grade 4 children were asked to study two movement sequences long enough to be absolutely certain that they would be able to recall the entire sequences correctly. The older group displayed superior recall readiness in comparison to the younger group. Older children used a greater variety of strategies and also displayed significantly greater numbers of strategy orchestration patterns. In addition, Grade 4 children more frequently used overt encoding and self-checking strategies. Further, evidence suggests that Grade 4 children used language to encode movement components or to regulate their own learning more frequently than Grade 1 children.

Learning of movement sequences.

Learning of movement sequences.

Learning of movement sequences.

Learning of movement sequences.