Explicit Motor Sequence Learning Research Articles

A Comparison of Implicit and Explicit Motor Sequence Learning in Patients with Relapsing-Remitting Multiple Sclerosis.

This study tends to assess implicit and explicit types of motor learning in patients with Multiple Sclerosis (MS) and normal peers by means of a serial reaction time. Sample size was 15 for each group and Samples included 30 patients with MS and 30 normal peers and were assigned to implicit and explicit learning groups. A repeated measures ANOVA was used for measuring reaction time and response error, and a paired samples t-test was used to compare regular and irregular sequence data in each group. Comparison of these two types of learning in speed (response time) and accuracy (number of errors) showed the number of errors (P = 0.012) and response time (P = 0.012) in the implicit motor learning group of MS patients and the number of errors (P = 0.096) and response time (P = 0.954) in the explicit motor learning group of MS patients. Moreover, comparison showed the number of errors (P = 0.008) and response time (P = 0.05) in the implicit group of normal peers and the number of errors (P = 0.011) and response time (P = 0.442) in the explicit group of normal peers. The results showed that explaining and describing the task is less effective at training the motor sequence of MS patients and that these patients benefit more from implicit learning.

Time for considering the possibility that sleep plays no unique role in motor memory consolidation: Reply to Adi-Japha and Karni (2016).

The hypothesis that sleep makes a unique contribution to motor memory consolidation has been debated in recent years. In the target article (Pan & Rickard, 2015), we reported results of a comprehensive meta-analysis of the explicit motor sequence learning literature in which evidence was evaluated for both enhanced performance after sleep and stabilization after sleep. After accounting for confounding variables, we found no compelling evidence for either empirical phenomenon, and hence no compelling evidence for sleep-specific consolidation. In their comment, Adi-Japha and Karni (2016) critiqued the target article on three primary grounds: (a) our unrealistic (in their view) assumption that, if sleep-specific consolidation occurs, it is mechanistically unitary across all variants of the motor sequence experiments included in the meta-analysis, (b) our inclusion of child groups, which they believe may have resulted in an underestimation of sleep effects among adult groups, and (c) our inclusion of several experiments with atypical experimental designs, which may have introduced unaccounted for heterogeneity. In this reply we address each of those potentially legitimate concerns. We show that the metaregression allowed for tests of multiple candidate variables that could engender separate consolidation mechanisms, yielding no behavioral evidence for it. We also show through reanalysis that the inclusion of child groups had virtually no impact on the parameter estimates among adults, and that the inclusion of experiments with atypical designs did not materially influence parameter estimates. (PsycINFO Database Record

P247 Reorganization of modular architectures in the corticospinal neuromuscular system by implicit and explicit learning

Introduction A large number of researches have investigated the mechanisms of implicit and explicit motor sequence learning. The functional changes in motor circuits, which involve the primary motor cortex (M1), are thought to play an important role in memory formation of implicit knowledge. However, it is unclear what functions in the motor circuits contribute to formation of implicit knowledge in the M1. The corticospinal neuromuscular system organizes the modular architectures for generating a variety of movements. Therefore, we hypothesized that performance improvement through implicit learning results from reorganization of the modular architectures. Objectives We used transcranial magnetic stimulation (TMS), data-grove system, and principal component analysis (PCA) to test the hypothesis. Materials and methods Seventeen healthy subjects learned a sequence of serial reaction time task (SRTT) implicitly, and explicitly. Before and after a training session, both TMS-evoked finger joint movements and voluntary finger joint movements during the SRTT were recorded. Results PCA extracted a set of principal components (PCs) from TMS-evoked finger joint movements before (pre-PCs) and after (post-PCs) the training session, respectively. To test an idea that post-PCs contain large amount of information on the learned task, we reconstructed the voluntary movements during SRTT in post-training session by linear combination of a selected subset of the PCs. We found that the quality of the movements reconstructed by the post-PCs was superior to that of the pre-PCs in the implicit condition. By contrast, in the explicit condition, there was no significant difference in the reconstruction quality between the pre-PCs and post-PCs. Conclusion Our results suggest that the implicit knowledge is acquired through learning-specific reorganization of the modular architectures in the corticospinal neuromuscular system. On the other hand, the reorganization of the modular architectures does not relate to acquiring the explicit knowledge.

T006 How might brain stimulation enhance consolidation of motor learning?

Performance increments following a training intervention are secured and sometimes generated by a process termed consolidation. As healthy older humans express lesser consolidation that young people this group might constitute a population particularly well suited to study consolidation. We will review the evidence whether and how brain stimulation enhances consolidation by modulating physiological mechanisms following the training. To demonstrate that brain stimulation is capable to modulate consolidation requires that its effects on performance indices be disambiguated from effects on performance. Transcranial direct current stimulation (tDCS) applied after motor training improved consolidation of explicit motor sequence learning in older controls. Anodal, but not cathodal, tDCS to M1, but not to PMd, led to performance improvements at retesting 8 h after initial learning. Only application of tDCS immediately after the end of training, but not after 1 or 2 h, enhanced offline consolidation. These results will be discussed against evidence provided by others (Tunovic et al., J Neurosci, 2014) that off-line stimulation may rescue consolidation through counteracting activity-dependent decreases of M1 excitability. These findings may suggest a model that brain stimulation may enhance consolidation by preventing post-training inhibitory action in M1 that may originate in premotor cortex.

Different Effects of Implicit and Explicit Motor Sequence Learning on Latency of Motor Evoked Potential Evoked by Transcranial Magnetic Stimulation on the Primary Motor Cortex.

Motor training induces plastic changes in the primary motor cortex (M1). However, it is unclear whether and how the latency of motor-evoked potentials (MEP) and MEP amplitude are affected by implicit and/or explicit motor learning. Here, we investigated the changes in M1 excitability and MEP latency induced by implicit and explicit motor learning. The subjects performed a serial reaction time task (SRTT) with their five fingers. In this task, visual cues were lit up sequentially along with a predetermined order. Through training, the subjects learned the order of sequence implicitly and explicitly. Before and after the SRTT, we recorded MEP at 25 stimulation points around the hot spot for the flexor pollicis brevis (FPB) muscle. Although no changes in MEP amplitude were observed in either session, we found increases in MEP latency and changes in histogram of MEP latency after implicit learning. Our results suggest that reorganization across the motor cortices occurs during the acquisition of implicit knowledge. In contrast, acquisition of explicit knowledge does not appear to induce the reorganization based on the measures we recorded. The fact that the above mentioned increases in MEP latency occurred without any alterations in MEP amplitude suggests that learning has different effects on different physiological signals. In conclusion, our results propose that analyzing a combination of some indices of M1 excitability, such as MEP amplitude and MEP latency, is encouraged in order to understand plasticity across motor cortices.

Explicit motor sequence learning with the paretic arm after stroke

Purpose: Motor sequence learning is important for stroke recovery, but experimental tasks require dexterous movements, which are impossible for people with upper limb impairment. This makes it difficult to draw conclusions about the impact of stroke on learning motor sequences. We aimed to test a paradigm requiring gross arm movements to determine whether stroke survivors with upper limb impairment were capable of learning a movement sequence as effectively as age-matched controls.Materials and methods: In this case-control study, 12 stroke survivors (10–138 months post-stroke, mean age 64 years) attempted the task once using their affected arm. Ten healthy controls (mean 66 years) used their non-dominant arm. A sequence of 10 movements was repeated 25 times. The variables were: time from target illumination until the cursor left the central square (onset time; OT), accuracy (path length), and movement speed.Results: OT reduced with training (p < 0.05) for both groups, with no change in movement speed or accuracy (p > 0.1). We quantified learning as the OT difference between the end of training and a random sequence; this was smaller for stroke survivors than controls (p = 0.015).Conclusions: Stroke survivors can learn a movement sequence with their paretic arm, but demonstrate impairments in sequence specific learning.Implications for RehabilitationMotor sequence learning is important for recovery of movement after stroke.Stroke survivors were found to be capable of learning a movement sequence with their paretic arm, supporting the concept of repetitive task training for recovery of movement.Stroke survivors showed impaired sequence specific learning in comparison with age-matched controls, indicating that they may need more repetitions of a sequence in order to re-learn movements.Further research is required into the effect of lesion location, time since stroke, hand dominance and gender on learning of motor sequences after stroke.

Implicit and explicit motor sequence learning in children born very preterm

BackgroundMotor skills can be learned explicitly (dependent on working memory (WM)) or implicitly (relatively independent of WM). Children born very preterm (VPT) often have working memory deficits. Explicit learning may be compromised in these children. AimsThis study investigated implicit and explicit motor learning and the role of working memory in VPT children and controls. MethodsThree groups (6–9 years) participated: 20 VPT children with motor problems, 20 VPT children without motor problems, and 20 controls. A nine button sequence was learned implicitly (pressing the lighted button as quickly as possible) and explicitly (discovering the sequence via trial-and-error). ResultsChildren learned implicitly and explicitly, evidenced by decreased movement duration of the sequence over time. In the explicit condition, children also reduced the number of errors over time. Controls made more errors than VPT children without motor problems. Visual WM had positive effects on both explicit and implicit performance. ConclusionVPT birth and low motor proficiency did not negatively affect implicit or explicit learning. Visual WM was positively related to both implicit and explicit performance, but did not influence learning curves. These findings question the theoretical difference between implicit and explicit learning and the proposed role of visual WM therein.

Enhancement of motor consolidation by post-training transcranial direct current stimulation in older people

Consolidation, by which performance increments after a training intervention are secured and sometimes generated, is reduced in elderly humans. The present study addressed the question whether transcranial direct current stimulation (tDCS) applied after motor training improves consolidation of explicit motor sequence learning in healthy older humans. In the first experiment, anodal or cathodal tDCS to the left primary motor cortex, anodal tDCS to premotor cortex, or sham tDCS was applied immediately after completion of a finger sequence learning task. Performance was retested at 8 and 22 hours after the initial training session. Whereas all groups achieved similar performance at the end of training, off-line improvements differed between groups at later retesting, depending on the type of intervention. Relative to the other 3 interventions, anodal tDCS to primary motor cortex (M1) led to performance improvements already at retesting 8 hours after initial learning and were maintained on the next day. In the second experiment, effects of the timing of post-training anodal tDCS to M1 with respect to the end of training were studied. Participants received anodal tDCS of M1 immediately or 60 or 120 minutes after training and were retested on sequence performance 8 hours post training. Only application of tDCS immediately after the end of training, but not after 1 or 2 hours, enhanced off-line consolidation. These findings suggest that anodal tDCS applied off-line immediately post training to M1 interacts specifically with early processes promoting consolidation of motor sequence learning in healthy older individuals.

P148. Timing of post-training transcranial direct current stimulation to enhance consolidation of motor sequence learning in older people

Objective Consolidation, by which performance improvements following a training intervention are secured and sometimes generated, is reduced in older adults and may thus represent an attractive therapeutic target. In a previous study (Rumpf et al., in preparation), we found that anodal transcranial direct current stimulation (tDCS) applied to the primary motor cortex (M1) immediately after a training session enhances consolidation of motor sequence learning in healthy older adults. The current study was designed to further investigate the effective time window of post-training tDCS with regards to consolidation. Methods 45 healthy elderly subjects (mean age 67.3 y, 27 female) were included. All participants performed a training session (14 blocks) of an explicit motor sequence learning task at 11 a.m. and were retested (4 blocks) 8 h later (7 p.m.) to assess offline-consolidation. Subjects were instructed to perform a five element sequence with their right hand as fast and accurate as possible. Each block was terminated after 60 movements. Therefore, a maximum of 12 correct sequences could be executed within one practice block. After training, all participants took part in 3 stimulation sessions. Verum anodal tDCS to left M1 was applied immediately after training (Stim0 group, n = 12), 60 min (Stim60 group, n = 11) or 120 min after training (Stim120 group, n = 11), while sham tDCS was administered during the two other stimulation sessions. The sham group (SHAM, n = 11) received sham tDCS in all three sessions. Speed (average time to complete a correct sequence per block, TCS) and accuracy (errors per block) measures were used to calculate a Performance Index (PI = exp−(TCS) ∗ exp−(errors/12) ∗ 100). Results To assess consolidation of motor sequence learning, retest performance (PI) was normalized to the end of training performance (EoT, last 3 training blocks), when asymptotic performance was reached. One-way ANOVA comparing the retest performance (mean normalized PI of the four retest blocks) revealed a significant difference between groups (F(3,44) = 3.062, p = 0.039). Post hoc t-tests show that this effect was driven by the improved performance of the Stim0 group relative to the other groups (Stim0 vs. SHAM: p = 0.021, Stim0 vs. Stim60: p = 0.041, Stim0 vs. Stim120: p = 0.01). No statistically significant differences between the SHAM, Stim60 and Stim120 groups were found. Within group, only Stim0 group showed significant retest improvements compared to EoT baseline (p = 0.021; SHAM, p = 0.99; Stim60, p = 0.60; Stim120, p = 0.68). Conclusions These results suggest that post training application of anodal tDCS effectively enhances off line consolidation in older adults by interaction with early post-training processes in M1.

The Structural Relationship Between Two Motor Sequences Practiced Close in Time Impacts Offline Facilitation

ABSTRACTRobust offline gains occur during explicit motor sequence learning. However practice of a motor sequence, other than the target sequence, within 4–6 hr after initial practice interferes with these gains. This work assessed if experiencing supplemental practice of spatially or motorically similar sequences influenced the extent of offline gain. A contemporary model of sequence learning assumes that exposure to a spatially but not motor-related sequence would not compromise stabilization of the memory for the target sequence, thus, would have minimal impact on the resultant offline gain and possibly amplify overnight gains. As anticipated, a reliable offline improvement was observed for the target motor sequence in the absence of practice with an alternative motor sequence. This gain was significantly reduced when the learner experienced additional practice with either a novel or motorically similar sequence. There was no evidence of heightened overnight gain for the target sequence from intervening practice with a spatially similar sequence. Thus, the expression of offline improvement is not necessarily eliminated if practice of an alternative motor sequence is encountered shortly after a target sequence. However, the structure of the motor sequence faced during intervening practice can impact the resultant postpractice consolidation processes reflected in the eventual expression of offline facilitation.

Comparison of implicit and explicit motor sequence learning in children with ADHD and their typical peers

Introduction: The aim of this study was to assess of both implicit and explicit motor sequence learning in children with attention deficit hyper activity disorder (ADHD) and typical peers , by serial reaction time task. Materials and Methods: The sample size for each group was 12. The study sample was included 24 children with ADHD, in explicit learning group and implicit learning group. and 24 typical children was included in implicit learning group, and explicit learning group. ANOVA repetitive measured for comparing response time and errors in different blocks, and paired t-test was used for comparing regular and irregular blocks. Results: The comparision of implicit and explicit learning on, accuracy (error response) and speed (response time) in ADHD explicit group would indicate accuracy (P-value=0/012), speed (P-value=0/012) and in ADHD implicit groop would indicate accuracy (P-value=0/094), speed (P-value=0/954). so in typical explicit group would indicate accuracy (P-value=0/008), speed (P-value=0/05) and in typical implicit group showed that accuracy (P-value=0/011), response times (P-value=0/442). Conclusion: This study showed that explain the task in motor sequence learning is more better in ADHD children. so before performing a task should be considered. Keywords: Motor Sequence, Explicit Learning, Implicit Learning, ADHD

Task-dependent interactions between Dopamine D2 receptor polymorphisms and L-DOPA in patients with Parkinson's disease

Variants in genes regulating dopamine transmission affect performance on tasks including working memory and executive function as well as temporal processing and sequence learning. In the current study, we determined whether a dopamine D2 receptor DNA sequence polymorphism interacts with L-DOPA during motor tasks in patients with Parkinson's disease (PD). Forty-five PD patients were genotyped for the DRD2 polymorphism (rs 1076560, G>T). Patients performed an explicit motor sequence learning task and the grooved pegboard test in both ON and OFF L-DOPA states. For motor sequence learning, DRD2 genotype mediated L-DOPA effects such that L-DOPA associated improvements were only observed in the minor T allele carriers (associated with lower D2 receptor availability, t10=−2.71, p=0.022), whereas G homozygotes showed no performance change with L-DOPA. For the grooved pegboard test, performance improved with L-DOPA independent of patients’ DRD2 genotype. Collectively these results demonstrate that common DRD2 allelic differences found in the human population may explain how dopamine differentially contributes to performance across tasks and individuals.

Cerebellar contributions to visuomotor adaptation and motor sequence learning: an ALE meta-analysis

Cerebellar contributions to motor learning are well-documented. For example, under some conditions, patients with cerebellar damage are impaired at visuomotor adaptation and at acquiring new action sequences. Moreover, cerebellar activation has been observed in functional MRI (fMRI) investigations of various motor learning tasks. The early phases of motor learning are cognitively demanding, relying on processes such as working memory, which have been linked to the cerebellum as well. Here, we investigated cerebellar contributions to motor learning using activation likelihood estimation (ALE) meta-analysis. This allowed us to determine, across studies and tasks, whether or not the location of cerebellar activation is constant across differing motor learning tasks, and whether or not cerebellar activation in early learning overlaps with that observed for working memory. We found that different regions of the anterior cerebellum are engaged for implicit and explicit sequence learning and visuomotor adaptation, providing additional evidence for the modularity of cerebellar function. Furthermore, we found that lobule VI of the cerebellum, which has been implicated in working memory, is activated during the early stages of explicit motor sequence learning. This provides evidence for a potential role for the cerebellum in the cognitive processing associated with motor learning. However, though lobule VI was activated across both early explicit sequence learning and working memory studies, there was no spatial overlap between these two regions. Together, our results support the idea of modularity in the formation of internal representations of new motor tasks in the cerebellum, and highlight the cognitive processing relied upon during the early phases of motor skill learning.

Differential working memory correlates for implicit sequence performance in young and older adults

Our recent work has revealed that visuospatial working memory (VSWM) relates to the rate of explicit motor sequence learning (Bo and Seidler in J Neurophysiol 101:3116-3125, 2009) and implicit sequence performance (Bo et al. in Exp Brain Res 214:73-81, 2011a) in young adults (YA). Although aging has a detrimental impact on many cognitive functions, including working memory, older adults (OA) still rely on their declining working memory resources in an effort to optimize explicit motor sequence learning. Here, we evaluated whether age-related differences in VSWM and/or verbal working memory (VWM) performance relates to implicit performance change in the serial reaction time (SRT) sequence task in OA. Participants performed two computerized working memory tasks adapted from change detection working memory assessments (Luck and Vogel in Nature 390:279-281, 1997), an implicit SRT task and several neuropsychological tests. We found that, although OA exhibited an overall reduction in both VSWM and VWM, both OA and YA showed similar performance in the implicit SRT task. Interestingly, while VSWM and VWM were significantly correlated with each other in YA, there was no correlation between these two working memory scores in OA. In YA, the rate of SRT performance change (exponential fit to the performance curve) was significantly correlated with both VSWM and VWM, while in contrast, OA's performance was only correlated with VWM, and not VSWM. These results demonstrate differential reliance on VSWM and VWM for SRT performance between YA and OA. OA may utilize VWM to maintain optimized performance of second-order conditional sequences.

L-DOPA changes ventral striatum recruitment during motor sequence learning in Parkinson's disease

We previously reported a differential effect of dopaminergic medication across the time course of motor sequence learning in early stage Parkinson's (PD) patients [1]. There was a medication-associated impairment specific to the early phase of learning. In the current study, we investigated the BOLD responses associated with this deleterious medication effect on motor sequence learning. We hypothesized that levodopa (l-DOPA) would negatively affect the recruitment of the ventral striatal circuitry during the early phase of learning. Seventeen early stage PD patients ON and OFF l-DOPA and 21 healthy control participants performed an explicit motor sequence learning task inside the MRI scanner. We observed sequence learning-specific activation during the early phase in the ventral putamen for controls and PD OFF but not for PD ON l-DOPA. A comparison of activation between PD OFF and PD ON showed that activation within the ventral putamen was decreased in PD ON compared to PD OFF. The extent of the l-DOPA associated activation decrease in the ventral putamen showed a small, positive correlation with the degree of sequence learning performance decrease in the early phase of learning (r=0.45–0.54 across measures, p<0.05, one-tailed). These findings provide evidence for the negative effects of l-DOPA in PD patients on the ventral putamen circuitry involved in early motor sequence learning, and provide support for a role of this structure in the sequence learning process.

Working memory capacity correlates with implicit serial reaction time task performance

We recently reported that visuospatial working memory capacity predicts the rate of explicit motor sequence learning (Bo and Seidler in J Neurophysiol 101:3116-3125, 2009). In the current study, we evaluated relationships between visuospatial and verbal working memory and implicit performance change in the serial reaction time (SRT) task. Participants performed two computerized working memory tasks adapted from change detection working memory assessments, an implicit SRT task, and several neuropsychological tests. We observed significant correlations between visuospatial working memory (VSWM) and verbal working memory (VWM) performance. VSWM, VWM, and card rotation task were each significantly correlated with the rate of reaction time improvement in the SRT task. Multiple linear regression analysis revealed that VSWM explained a significant portion of the variance in rate of SRT performance change (exponential fit to the performance curve) across individual participants, and the addition of VWM did not significantly improve the model. These findings suggest that VSWM plays a role in the implicit performance improvement of second-order conditional sequences.

P22.12 The role of ipsilateral hemisphere in explicit motor sequence learning. A TMS study

P22.12 The role of ipsilateral hemisphere in explicit motor sequence learning. A TMS study

Abnormal explicit but normal implicit sequence learning in premanifest and early Huntington's disease.

Learning may occur with or without awareness, as explicit (intentional) or implicit (incidental) learning. The caudate nucleus and the putamen, which are affected early in Huntington's disease (HD), are thought to be essential for motor sequence learning. However, the results of existing studies are inconsistent concerning presence/absence of deficits in implicit and explicit motor sequence learning in HD. We assessed implicit and explicit motor sequence learning using sequences of equivalent structure in 15 individuals with a positive HD genetic test (7 premanifest; 8 early stage disease) and 11 matched controls. The HD group showed evidence of normal implicit motor sequence learning, whereas explicit motor sequence learning was impaired in manifest and premanifest HD gene carriers, with progressive decline with progressive disease. Explicit sequence learning may be a useful cognitive biomarker for HD progression.

Effect of Dopaminergic Medications on the Time Course of Explicit Motor Sequence Learning in Parkinson's Disease

The capacity to learn new motor sequences is fundamental to adaptive motor behavior. The early phase of motor sequence learning relies on the ventral and anterior striatal circuitry, whereas the late phase relies on the dorsal and posterior striatal circuitry. Early Parkinson's disease (PD) is mainly characterized by dopaminergic denervation of the dorsal and posterior striatum while sparing anterior and ventral regions. Dopaminergic medication improves dorsal and posterior striatum function by compensating for the loss of dopamine. However, previous work has shown that dopaminergic medication interferes with the ventral and anterior striatum function by overdosing this relatively intact structure in early-state PD. Here we test whether these effects are also observed over the time course of motor sequence learning. Fourteen PD patients ON and OFF dopaminergic medications and 11 healthy age-matched control participants performed an explicit motor sequence learning task. When sequence learning was compared across different learning phases in patients ON and OFF medication, a significant impairment associated with medication was observed in the early relative to later phases of learning. The rate of learning in the early phase measured trial by trial in patients ON medication was significantly slower than that in controls and when patients were OFF medication. No significant impairment was found in the later learning phases. These results demonstrate that dopaminergic medications may selectively impair early-phase motor sequence learning. These results extend and generalize the dopamine overdose effects previously reported for (antero)ventral striatum-mediated cognitive tasks to motor sequence learning.

Age-Related Declines in Visuospatial Working Memory Correlate With Deficits in Explicit Motor Sequence Learning

Numerous studies have shown that older adults exhibit deficits in motor sequence learning, but the mechanisms underlying this effect remain unclear. Our recent work has shown that visuospatial working-memory capacity predicts the rate of motor sequence learning and the length of motor chunks formed during explicit sequence learning in young adults. In the current study, we evaluate whether age-related deficits in working memory explain the reduced rate of motor sequence learning in older adults. We found that older adults exhibited a correlation between visuospatial working-memory capacity and motor sequence chunk length, as we observed previously in young adults. In addition, older adults exhibited an overall reduction in both working-memory capacity and motor chunk length compared with that of young adults. However, individual variations in visuospatial working-memory capacity did not correlate with the rate of learning in older adults. These results indicate that working memory declines with age at least partially explain age-related differences in explicit motor sequence learning.