Discrete Sequence Production Task Research Articles

Hypohydration alters pre-frontal cortex haemodynamics, but does not impair motor learning

It is unknown how hypohydration influences fine motor performance training and motor learning. Here, 30 participants (aged 19–46 years) were randomly assigned to a hypohydration (HYPO) or control (CON) group (both n = 15). Moderate hypohydration (~ 2.4% loss in body mass) was produced in HYPO via active dehydration before a 46 min fluid restricted rest period was undertaken. The conclusion of rest coincided with when CON attended the facilities. Both groups undertook a discrete sequence production task consisting of 6 training blocks, and returned ~ 300 min later to complete a delayed retention and transfer test while euhydrated. Bilateral pre-frontal cortex (PFC) haemodynamics were assessed using functional near-infrared spectroscopy throughout training and delayed learning assessments. Response time improved across training (P < 0.01) and was similar between the groups (both P = 0.22). Analysis of training PFC haemodynamics revealed a significant group by block interaction for oxygenated (O2Hb; P < 0.01), but not deoxygenated haemoglobin (P = 0.77). In training block 1, bilateral O2Hb was higher in HYPO (P = 0.02), while bilateral O2Hb increased in CON between blocks 2–3 and 5–6 (both P ≤ 0.03). During the delayed retention and transfer test, no group differences or interactions were found in response time, response error, or PFC haemodynamics (all P ≥ 0.27). Moderate hypohydration does increase PFC activation during motor skill learning, however, this appears to be transient and of little consequence to training or delayed retention or transfer performance.

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.

Consolidation of motor sequence learning eliminates susceptibility of SMAproper to TMS: a combined rTMS and cTBS study

Earlier research suggested that after 210 practice trials, the supplementary motor area (SMA) is involved in executing all responses of familiar 6-key sequences in a discrete sequence production (DSP) task (Verwey, Lammens, and van Honk, 2002). This was indicated by slowing of each response 20 and 25 min after the SMA had been stimulated for 20 min using repetitive transcranial magnetic stimulation (rTMS). The present study used a similar approach to assess the effects of TMS to the more posterior SMAproper at the end of practice and also 24 h later. As expected stimulation of SMAproper with 20 min of 1 Hz rTMS and 40 s of continuous theta burst stimulation (cTBS) immediately after practice slowed sequence execution relative to a sham TMS condition, but stimulation on the day following practice did not cause slowing. This indicates that offline consolidation makes learning robust against stimulation of SMAproper. Execution of all responses in the sequence was disrupted 0, 20, and 40 min after rTMS, but after cTBS, this occurred only after 40 min. The results suggest that it is implicit sequence knowledge that is processed by the SMAproper and that consolidates.

A multi-representation approach to the contextual interference effect: effects of sequence length and practice

The present study investigated the long-term benefit of Random-Practice (RP) over Blocked-Practice (BP) within the contextual interference (CI) effect for motor learning. We addressed the extent to which motor sequence length and practice amount factors moderate the CI effect given that previous reports, often in applied research, have reported no long-term advantage from RP. Based on predictions arising from the Cognitive framework of Sequential Motor Behavior (C-SMB) and using the Discrete Sequence Production (DSP) task, two experiments were conducted to compare limited and extended practice amounts of 4- and 7-key sequences under RP and BP schedules. Twenty-four-hour delayed retention performance confirmed the C-SMB prediction that the CI-effect occurs only with short sequences that receive little practice. The benefit of RP with limited practice was associated with overnight motor memory consolidation. Further testing with single-stimulus as well as novel and unstructured (i.e., random) sequences indicated that limited practice under RP schedules enhances both reaction and chunking modes of sequence execution with the latter mode benefitting from the development of implicit and explicit forms of sequence representation. In the case of 7-key sequences, extended practice with RP and BP schedules provided for equivalent development of sequence representations. Higher explicit awareness of sequence structures was associated with faster completion of practiced but also of novel and unstructured sequences.

Cognitive and Motor Learning in Internally-Guided Motor Skills.

Several canonical experimental paradigms (e.g., serial reaction time task, discrete sequence production task, m × n task) have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative of externally-specified sequencing—motor tasks where the environment or task paradigm extrinsically provides the sequence of stimuli, i.e., the responses are stimulus-driven. Previous studies utilizing such canonical paradigms have largely overlooked the learning behaviors in a more realistic class of motor tasks that involve internally-guided sequencing—where the sequence of motor actions is self-generated or internally-specified. In this work, we use the grid-navigation task as an instance of internally-guided sequencing to investigate the nature of learning in such paradigms. The participants performed Grid-Sailing Task (GST), which required navigating (by executing sequential keypresses) a 5 × 5 grid from start to goal (SG) position while using a particular key-mapping (KM) among the three cursor-movement directions and the three keyboard buttons. The participants performed two behavioral experiments—Single-SG and Mixed-SG condition. The Single-SG condition required performing GST on a single SG position repeatedly, whereas the Mixed-SG condition involved performing GST using the same KM on two novel SG positions presented in a random, inter-mixed manner. In the Single-SG condition, we show that motor learning contributes to the sequence-specific learning in GST with the repeated execution of the same trajectories. In the Mixed-SG condition, since the participants utilize the previously learned KM, we anticipate a transfer of learning from the Single-SG condition. The acquisition and transfer of a KM-specific internal model facilitates efficient trajectory planning on novel SG conditions. The acquisition of such a KM-specific internal model amounts to trajectory-independent cognitive learning in GST. We show that cognitive learning contributes to the learning in GST by showing transfer-related performance improvements in the Mixed-SG condition. In sum, we show the role of cognitive and motor learning processes in internally-guided sequencing and further make a case for using GST-like grid-navigation paradigms in investigating internally guided skill learning.

Regular participation in leisure time activities and high cardiovascular fitness improve motor sequence learning in older adults

IntroductionOlder adults show higher interindividual performance variability during the learning of new motor sequences than younger adults. It is largely unknown what factors contribute to this variability. This study aimed to, first, characterize age differences in motor sequence learning and, second, examine influencing factors for interindividual performance differences.Method30 young adults (age M = 21.89, SD = 2.08, 20 female) and 29 older adults (age M = 69.55, SD = 3.03, 18 female) participated in the study. Motor sequence learning was assessed with a discrete sequence production (DSP) task, requiring key presses to a sequence of visual stimuli. Three DSP practice phases (á 8 blocks × 16 sequences, two six-element sequences) and two transfer blocks (new untrained sequences) were performed. Older participants conducted the Mini-Mental Status Examination and a visuospatial working-memory task. All participants finished a questionnaire on everyday leisure activities and a cardiovascular fitness test.ResultsPerformance speed increased with practice in both groups, but young improved more than older adults (significant Group × Time effect for response time, F(1,5) = 4.353, p = 0.004, eta_{p}^{2} = 0.071). Accuracy did not change in any age group (non-significant Group × Time effect for error rates, F(1,5) = 2.130, p = 0.091, eta_{p}^{2} = 0.036). Older adults revealed lower transfer costs for performance speed (significant Time × Group effect, e.g., simple sequence, F(1,2) = 10.511, p = 0.002, eta_{p}^{2} = 0.156). High participation in leisure time activities (β = − 0.58, p = 0.010, R2 = 0.45) and high cardiovascular fitness (β = − 0.49, p = 0.011, R2 = 0.45) predicted successful motor sequence learning in older adults.DiscussionResults confirmed impaired motor learning in older adults. Younger adults seem to show a better implicit knowledge of the practiced sequences compared to older adults. Regular participation in leisure time activities and cardiovascular fitness seem to prevent age-related decline and to facilitate motor sequence performance and motor sequence learning in older adults.

0316 Emotion Regulation During Sleep Deprivation and Repeated Physiological Stress: Implications for Motor Skill Learning and Production

Abstract Introduction The ability to perform learned motor procedures under stress is a critical skill for many high-risk occupations. Explicit motor skills require top-down cognitive control, which both sleep loss and stress have been found to produce significant degradations, whereas implicit skills rely less on cognitive control and are more resilient to physiological stress. We investigated whether differences in emotion regulation attenuated the effects of sleep deprivation (SD) and acute stress on discrete motor learning. Methods 45 adults (21 F; 22 ± 3.4 years) participated in 28-hours of in-lab SD. Participants completed repeated batteries that included the Maastricht Acute Stress Test (MAST) Karolinska Sleepiness Scale (KSS), Psychomotor Vigilance Test (PVT), and Discrete Sequence Production Task (DSP). Stress response was quantified by salivary cortisol. We quantified DSP motor performance by total accurate sequences, and average movement time on accurate trials. Ability emotional intelligence (EI) was measured with the MSCEIT, while trait EI was measured with the Bar-On EQI. The CD-RISC was included as a measure of resilience. Results Using linear mixed effects models of motor performance indices, we found subjective, trait-based emotional intelligence (EQI) to be associated with worse motor performance over time, and objective, ability-based emotional intelligence (MSCEIT) to be associated with greater movement speed. We further found that greater psychological resilience (CD-RISC) but not emotional intelligence was predictive of stronger and less variable chunking structures during SD. Conclusion Emotional intelligence can influence motor learning under stressful SD, whereas psychological resilience can safeguard learning. Future work should further investigate how trait and ability metrics of EI have opposing effects on responses to stress under SD. Work in this direction could serve to identify difference factors that bolster motor skill production in operational environments where stress and SD are unavoidable. Support US Army Medical Research and Development Command: W81XWH-17-C-0088

The Simon effect in a discrete sequence production task: Key-specific stimuli cannot be ignored due to attentional capture

Two experiments examined whether practicing discrete key pressing sequences eventually leads to a disregard of the key-specific stimuli, as suggested by sequence learning models, or whether these stimuli continue to be relied upon because the associated luminance increase attracts visuospatial attention. Participants practiced two sequences by reacting to two fixed series of seven letter stimuli, each displayed at a location that did or did not correspond with the required response location. Stimulus use was indicated by a Simon effect in that key presses were slowed when stimulus and key locations did not correspond. Experiment 1 demonstrated that letter stimuli continued to be used as the Simon effect occurred with each sequence element, and this remained quite stable across practice and did not differ for familiar and unfamiliar sequences. Experiment 2 showed that the Simon effect remained present even with meaningless stimuli that were often even harmful. These findings suggest that even in motor sequences that can be executed without element-specific stimuli attention attraction enforces stimulus use. The data further supported the assumptions that S-R translation and sequencing systems are racing to trigger individual responses, and that explicit sequence representations include spatial and verbal knowledge.

Sequence learning is driven by improvements in motor planning.

The ability to perform complex sequences of movements quickly and accurately is critical for many motor skills. Although training improves performance in a large variety of motor sequence tasks, the precise mechanisms behind such improvements are poorly understood. Here we investigated the contribution of single-action selection, sequence preplanning, online planning, and motor execution to performance in a discrete sequence production task. Five visually presented numbers cued a sequence of five finger presses, which had to be executed as quickly and accurately as possible. To study how sequence planning influenced sequence production, we manipulated the amount of time that participants were given to prepare each sequence by using a forced-response paradigm. Over 4 days, participants were trained on 10 sequences and tested on 80 novel sequences. Our results revealed that participants became faster in selecting individual finger presses. They also preplanned three or four sequence items into the future, and the speed of preplanning improved for trained, but not for untrained, sequences. Because preplanning capacity remained limited, the remaining sequence elements had to be planned online during sequence execution, a process that also improved with sequence-specific training. Overall, our results support the view that motor sequence learning effects are best characterized by improvements in planning processes that occur both before and concurrently with motor execution. NEW & NOTEWORTHY Complex skills often require the production of sequential movements. Although practice improves performance, it remains unclear how these improvements are achieved. Our findings show that learning effects in a sequence production task can be attributed to an enhanced ability to plan upcoming movements. These results shed new light on planning processes in the context of movement sequences and have important implications for our understanding of the neural mechanisms that underlie skill acquisition.

Dose of remote limb ischemic conditioning for enhancing learning in healthy young adults.

Remote limb ischemic conditioning (RLIC) is a technique in which tissues distant from the target organ are exposed to brief, sub-lethal bouts of ischemia. The effects of remotely applied ischemic conditioning are systemically transferred to the target organ, and typically manifested as protection from subsequent ischemic injury. Previous studies in our lab have found and confirmed that RLIC enhances learning and retention during motor training on a balance task. The current study tested the effect of RLIC dose (number of cycles) on learning enhancement in young, healthy adults. Forty healthy participants age 18-40years were randomized to receive 5 cycles of sham conditioning (n = 9), 3 cycles of RLIC (n = 11), 4 cycles of RLIC (n = 10), or 5 cycles of RLIC (n = 10) using a blood pressure cuff around the upper arm once a day for 7 consecutive weekdays (Days 1-7). Participants concurrently trained on a balance task, bimanual cup stacking task, and a discrete sequence production task on Days 3-7. Change in performance on each of the three tasks was compared across groups. Participants in all four groups improved their performance on each of the three tasks over time. However, RLIC at any dose did not enhance learning on any of the three tasks. While RLIC is safe, inexpensive, and clinically feasible, reproducibility may be challenged by unidentified factors, raising critical challenges to the straightforward translation of RLIC for improving rehabilitation outcomes in individuals recovering from neurological injury.

Do musicians learn a fine sequential hand motor skill differently than non-musicians?

Do professional musicians learn a fine sequential hand motor skill more efficiently than non-musicians? Is this also the case when they perform motor imagery, which implies that they only mentally simulate these movements? Musicians and non-musicians performed a Go/NoGo discrete sequence production (DSP) task, which allows to separate sequence-specific from a-specific learning effects. In this task five stimuli, to be memorized during a preparation interval, signaled a response sequence. In a practice phase, different response sequences had to be either executed, imagined, or inhibited, which was indicated by different response cues. In a test phase, responses were required to familiar (previously executed, imagined, or inhibited) and unfamiliar sequences. In both phases, response times and response accuracy were measured while the electroencephalogram (EEG) was only registered during the practice phase to compare activity between motor imagery, motor execution, and motor inhibition for both groups. Results in the practice phase revealed that musicians learned the response sequences faster and more accurately than non-musicians although no difference in initiation time was found. EEG analyses revealed similar lateralized activity during learning a motor skill for both groups. Our results from the test phase showed better sequence-a-specific learning effects (i.e., faster response times and increased accuracy) for musicians than for non-musicians. Moreover, we revealed that non-musicians benefit more from physical execution while learning a required motor sequence, whereas sequence-specific learning effects due to learning with motor imagery were very similar for musicians and non-musicians.

Does Transcranial Direct Current Stimulation Affect the Learning of a Fine Sequential Hand Motor Skill with Motor Imagery?

Learning a fine sequential hand motor skill, like playing the piano or learning to type, improves not only due to physical practice, but also due to motor imagery. Previous studies revealed that transcranial direct current stimulation (tDCS) and motor imagery independently affect motor learning. In the present study, we investigated whether tDCS combined with motor imagery above the primary motor cortex influences sequence-specific learning. Four groups of participants were involved: an anodal, cathodal, sham stimulation, and a control group (without stimulation). A modified discrete sequence production (DSP) task was employed: the Go/NoGo DSP task. After a sequence of spatial cues, a response sequence had to be either executed, imagined, or withheld. This task allows to estimate both non-specific learning and sequence-specific learning effects by comparing the execution of unfamiliar sequences, familiar imagined, familiar withheld, and familiar executed sequences in a test phase. Results showed that the effects of anodal tDCS were already developing during the practice phase, while no effects of tDCS on sequence-specific learning were visible during the test phase. Results clearly showed that motor imagery itself influences sequence learning, but we also revealed that tDCS does not increase the influence of motor imagery on sequence learning.

Skill in discrete keying sequences is execution rate specific

The present study tested the hypothesis that in motor sequences, the interval between successive movements is critical for the type of representation that develops. Participants practiced two 7-key sequences in the context of a discrete sequence production (DSP) task. The 0-RSI group practiced these sequences with response stimulus intervals (RSIs) of 0, which is typical for the DSP task, while the long-RSI group practiced the same sequences with unpredictable RSIs between 500 and 2000 ms. The ensuing test phase examined performance of these familiar and of unfamiliar sequences for both groups under both RSI regimes. The results support our hypothesis that the motor chunks that 0-RSI participants developed could not be used with long RSIs, whereas the long-RSI participants developed sequence representations that cannot be used with 0 RSIs. A new, computerized, sequence awareness task showed that long-RSI participants had limited sequence knowledge. The sequencing skill developed by long-RSI participants can, therefore, not have been based on explicit knowledge.

Differences in chunking behavior between young and older adults diminish with extended practice

Previous research found reduced motor chunking behavior in older adults compared to young adults. However, it remains unclear whether older adults are unable to use a chunking strategy or whether they are just slower in developing them. Our goal was to investigate the effect of extended practice on the development of chunking behavior in healthy older adults. A group of young and a group of healthy older adults between 74 and 85 years of age visited the lab on 2 days. A sequence of 3 and a sequence of 6 elements were both practiced 432 times in a discrete sequence production task. We found that age differences in chunking behavior, as measured by the difference between initiation and execution of the sequence, diminish with extended practice. Furthermore, in older, but not in young adults, slow responses that are often interpreted as the first response of a next motor chunk were associated with a finger that was also slow during performance of the random sequences. This finding calls for more attention to biomechanical factors in future theory about aging and sequence learning.

Improving novel motor learning through prior high contextual interference training

The primary objective of the present experiment was to examine the influence of recent practice in a random and blocked format for future motor learning. First, individuals practiced three unique discrete sequence production tasks in either a blocked or random schedule. One day later, all individuals practiced a new motor sequence not previously practiced. On day three, mean total time for the test performance of the original three motor sequences was lower for individuals that practiced in a random format. This emerged as a significant reduction in mean total time from the completion of practice and the test trials implicating offline consolidation as a key contributor to the random practice performance advantage. A novel finding from the present work was that the acquisition of the novel discrete sequence production task practiced on Day 2 was better for individuals that had prior random rather than blocked practice experience. This benefit was robust appearing early during acquisition as significantly lower mean total time. This benefit from random practice experience remained during the delayed test trials administered on Day 3 for the novel motor sequence.

How effector-specific is the effect of sequence learning by motor execution and motor imagery?

The aim of the present study was twofold. First, we wanted to examine how effector specific the effect of sequence learning by motor execution is, and second, we wanted to compare this effect with learning by motor imagery. We employed a Go/NoGo discrete sequence production task in which in each trial a spatial sequence of five stimuli was presented. After a Go signal the corresponding spatial response sequence had to be executed, while after a NoGo signal, the response sequence had to be mentally imagined. For the training phase, participants were divided into two groups. In the index finger group, participants had to respond (physically or mentally) with the left or right index finger, while in the hand group they had to respond with four fingers of the left or right hand. In a final test phase both execution modes were compared and all trials had to be executed. Response times and the percentage of correct responses were determined to establish learning effects. Results showed that sequence learning effects as assessed in the test phase were independent of the effector used during the training phase. Results revealed the presence of aspecific learning effects in the case of learning a required motor task with an index finger, but sequence-specific learning effects, both due to motor execution and to motor imagery, were not effector specific.

To What Extent Can Motor Imagery Replace Motor Execution While Learning a Fine Motor Skill?

Motor imagery is generally thought to share common mechanisms with motor execution. In the present study, we examined to what extent learning a fine motor skill by motor imagery may substitute physical practice. Learning effects were assessed by manipulating the proportion of motor execution and motor imagery trials. Additionally, learning effects were compared between participants with an explicit motor imagery instruction and a control group. A Go/NoGo discrete sequence production (DSP) task was employed, wherein a five-stimulus sequence presented on each trial indicated the required sequence of finger movements after a Go signal. In the case of a NoGo signal, participants either had to imagine carrying out the response sequence (the motor imagery group), or the response sequence had to be withheld (the control group). Two practice days were followed by a final test day on which all sequences had to be executed. Learning effects were assessed by computing response times (RTs) and the percentages of correct responses (PCs). The electroencephalogram (EEG ) was additionally measured on this test day to examine whether motor preparation and the involvement of visual short term memory (VST M) depended on the amount of physical/mental practice. Accuracy data indicated strong learning effects. However, a substantial amount of physical practice was required to reach an optimal speed. EEG results suggest the involvement of VST M for sequences that had less or no physical practice in both groups. The absence of differences between the motor imagery and the control group underlines the possibility that motor preparation may actually resemble motor imagery.

Restricted transfer of learning between unimanual and bimanual finger sequences.

When training bimanual skills, such as playing piano, people sometimes practice each hand separately and at a later stage combine the movements of the two hands. This poses the critical question of whether motor skills can be acquired by separately practicing each subcomponent or should be trained as a whole. In the present study, we addressed this question by training human subjects for 4 days in a unimanual or bimanual version of the discrete sequence production task. Both groups were then tested on trained and untrained sequences on both unimanual and bimanual versions of the task. Surprisingly, we found no evidence of transfer from trained unimanual to bimanual or from trained bimanual to unimanual sequences. In half the participants, we also investigated whether cuing the sequences on the left and right hand with unique letters would change transfer. With these cues, untrained sequences that shared some components with the trained sequences were performed more quickly than sequences that did not. However, the amount of this transfer was limited to ∼10% of the overall sequence-specific learning gains. These results suggest that unimanual and bimanual sequences are learned in separate representations. Making participants aware of the interrelationship between sequences can induce some transferrable component, although the main component of the skill remains unique to unimanual or bimanual execution.NEW & NOTEWORTHY Studies in reaching movement demonstrated that approximately half of motor learning can transfer across unimanual and bimanual contexts, suggesting that neural representations for unimanual and bimanual movements are fairly overlapping at the level of elementary movement. In this study, we show that little or no transfer occurred across unimanual and bimanual sequential finger movements. This result suggests that bimanual sequences are represented at a level of the motor hierarchy that integrates movements of both hands.

Structural Pathways Supporting Swift Acquisition of New Visuomotor Skills.

Human skill learning requires fine-scale coordination of distributed networks of brain regions linked by white matter tracts to allow for effective information transmission. Yet how individual differences in these anatomical pathways may impact individual differences in learning remains far from understood. Here, we test the hypothesis that individual differences in structural organization of networks supporting task performance predict individual differences in the rate at which humans learn a visuomotor skill. Over the course of 6 weeks, 20 healthy adult subjects practiced a discrete sequence production task, learning a sequence of finger movements based on discrete visual cues. We collected structural imaging data, and using deterministic tractography generated structural networks for each participant to identify streamlines connecting cortical and subcortical brain regions. We observed that increased white matter connectivity linking early visual regions was associated with a faster learning rate. Moreover, the strength of multiedge paths between motor and visual modules was also correlated with learning rate, supporting the potential role of extended sets of polysynaptic connections in successful skill acquisition. Our results demonstrate that estimates of anatomical connectivity from white matter microstructure can be used to predict future individual differences in the capacity to learn a new motor–visual skill, and that these predictions are supported both by direct connectivity in visual cortex and indirect connectivity between visual cortex and motor cortex.

The influence of motor imagery on the learning of a fine hand motor skill.

Motor imagery has been argued to affect the acquisition of motor skills. The present study examined the specificity of motor imagery on the learning of a fine hand motor skill by employing a modified discrete sequence production task: the Go/NoGo DSP task. After an informative cue, a response sequence had either to be executed, imagined, or withheld. To establish learning effects, the experiment was divided into a practice phase and a test phase. In the latter phase, we compared mean response times and accuracy during the execution of unfamiliar sequences, familiar imagined sequences, and familiar executed sequences. The electroencephalogram was measured in the practice phase to compare activity between motor imagery, motor execution, and a control condition in which responses should be withheld. Event-related potentials (ERPs) and event-related lateralizations (ERLs) showed strong similarities above cortical motor areas on trials requiring motor imagery and motor execution, while a major difference was found with trials on which the response sequence should be withheld. Behavioral results from the test phase showed that response times and accuracy improved after physical and mental practice relative to unfamiliar sequences (so-called sequence-specific learning effects), although the effect of motor learning by motor imagery was smaller than the effect of physical practice. These findings confirm that motor imagery also resembles motor execution in the case of a fine hand motor skill.