Skill Memory: Mind the Ever-Decreasing Gap for Offline Processing

Transcranial alternating current stimulation does not affect microscale learning

A theory has been posited that microscale learning, which involves short intervals of a few seconds during explicit motor skill learning, considerably enhances performance. This phenomenon correlates with diminished beta-band activity in the frontal and parietal regions. However, there is a lack of neurophysiological studies regarding the relationship between microscale learning and implicit motor skill learning. In the present study, we aimed to determine the effects of transcranial alternating current stimulation (tACS) during short rest periods on microscale learning in an implicit motor task. We investigated the effects of 20-Hz β-tACS delivered during short rest periods while participants performed an implicit motor task. In Experiments 1 and 2, β-tACS targeted the right dorsolateral prefrontal cortex and the right frontoparietal network, respectively. The participants performed a finger-tapping task using their nondominant left hand, and microscale learning was separately analyzed for micro-online gains (MOnGs) and micro-offline gains (MOffGs). Contrary to our expectations, β-tACS exhibited no statistically significant effects on MOnGs or MOffGs in either Experiment 1 or Experiment 2. In addition, microscale learning during the performance of the implicit motor task was improved by MOffGs in the early learning phase and by MOnGs in the late learning phase. These results revealed that the stimulation protocol employed in this study did not affect microscale learning, indicating a novel aspect of microscale learning in implicit motor tasks. This is the first study to examine microscale learning in implicit motor tasks and may provide baseline information that will be useful in future studies.

Comparison of online, offline, and hybrid hypotheses of motor sequence learning using a quantitative model that incorporate reactive inhibition

Two hypotheses have been advanced for when motor sequence learning occurs: offline between bouts of practice or online concurrently with practice. A third possibility is that learning occurs both online and offline. A complication for differentiating between those hypotheses is a process known as reactive inhibition, whereby performance worsens over consecutively executed sequences, but dissipates during breaks. We advance a new quantitative modeling framework that incorporates reactive inhibition and in which the three learning accounts can be implemented. Our results show that reactive inhibition plays a far larger role in performance than is appreciated in the literature. Across four groups of participants in which break times and correct sequences per trial were varied, the best overall fits were provided by a hybrid model. The version of the offline model that does not account for reactive inhibition, which is widely assumed in the literature, had the worst fits. We discuss implications for extant hypotheses and directions for future research.

Behavioral and physiological fatigue-related factors influencing timing and force control learning in pianists

Optimizing the training regimen depending on neuromuscular fatigue is crucial for the well-being of professionals intensively practicing motor skills, such as athletes and musicians, as persistent fatigue can hinder learning and cause neuromuscular injuries. However, accurate assessment of fatigue is challenging because of the dissociation between subjective perception and its impact on motor and cognitive performance. To address this issue, we investigated the interplay between fatigue and learning development in 28 pianists during three hours of auditory-motor training, dividing them into two groups subjected to different resting conditions. Changes in behavior and muscle activity during training were measured to identify potential indicators capable of detecting fatigue before subjective awareness. Our results indicate that motor learning and fatigue development are independent of resting frequency and timing. Learning indices, such as reduction in force and timing errors throughout training, did not differ between the groups. No discernible distinctions emerged in fatigue-related behavioral and physiological indicators between the groups. Regression analysis revealed that several fatigue-related indicators, such as tapping speed variability and electromyogram amplitude per unit force, could explain the learning of timing and force control. Our findings suggest the absence of a universal resting schedule for optimizing auditory-motor learning.

Generalization of procedural motor sequence learning after a single practice trial

When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments (N = 2095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0-30 s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill.

Breaking the barriers to designing online experiments: A novel open-source platform for supporting procedural skill learning experiments

BACKGROUND

Motor learning experiments are typically performed in laboratory environments, which can be time-consuming and require dedicated equipment/personnel, thus limiting the ability to gather data from large samples. To address this problem, some researchers have transitioned to unsupervised online experiments, showing advantages in participant recruitment without losing validity. However, most online platforms require coding experience or time-consuming setups to create and run experiments, limiting their usage across the field.

METHOD

To tackle this issue, an open-source web-based platform was developed (https://experiments.neurro-lab.engin.umich.edu/) to create, run, and manage procedural skill learning experiments without coding or setup requirements. The feasibility of the platform and the comparability of the results between supervised (n = 17) and unsupervised (n = 24) were tested in 41 naive right-handed participants using an established sequential finger tapping task. The study also tested if a previously reported rapid form of offline consolidation (i.e., microscale learning) in procedural skill learning could be replicated with the developed platform and evaluated the extent of interlimb transfer associated with the finger tapping task.

RESULTS

The results indicated that the performance metrics were comparable between the supervised and unsupervised groups (all p's > 0.05). The learning curves, mean tapping speeds, and micro-scale learning were similar to previous studies. Training led to significant improvements in mean tapping speed (2.22 ± 1.48 keypresses/s, p < 0.001) and a significant interlimb transfer of learning (1.22 ± 1.43 keypresses/s, p < 0.05).

CONCLUSIONS

The results show that the presented platform may serve as a valuable tool for conducting online procedural skill-learning experiments.

An extended challenge-based framework for practice design in sports coaching

The challenge-point framework as a model for thinking about motor learning was first proposed in 2004. Although it has been well-cited, surprisingly this framework has not made its way into much of the applied sport science literature. One of the reasons for this omission is that the original framework had not been encapsulated into a paper accessible for sports practitioners. The framework had mostly a theoretical focus, providing a mechanistic summary of motor learning research. Our aims in this paper were to explain and elaborate on the challenge point framework to present an applied framework guiding practice design. We connect the framework to other theories that involve predictive coding, where information is attended when it disconfirms current predictions, providing a strong signal for learning. We also consider how two new dimensions (learners' motivation and practice specificity) need to be considered when designing practice settings. By moving around the different dimensions of functional difficulty, motivation, and specificity, coaches can optimize practice to achieve different learning goals. Specifically, we present three general "types" of practice: practice to learn, to transfer to competition, and to maintain current skills. Practical examples are given to illustrate how this framework can inform coach practice.

Consolidation of human skill linked to waking hippocampo-neocortical replay

The introduction of rest intervals interspersed with practice strengthens wakeful consolidation of skill. The mechanisms by which the brain binds discrete action representations into consolidated, highly temporally resolved skill sequences during waking rest are not known. To address this question, we recorded magnetoencephalography (MEG) during acquisition and rapid consolidation of a sequential motor skill. We report the presence of prominent, fast waking neural replay during the same rest periods in which rapid consolidation occurs. The observed replay is temporally compressed by approximately 20-fold relative to the acquired skill, is selective for the trained sequence, and predicts the magnitude of skill consolidation. Replay representations extend beyond the hippocampus and entorhinal cortex to the contralateral sensorimotor cortex. These results document the presence of robust hippocampo-neocortical replay supporting rapid wakeful consolidation of skill.

Acute exercise following skill practice promotes motor memory consolidation in Parkinson's disease

Acute cardiovascular exercise has shown to promote neuroplastic processes supporting the consolidation of newly acquired motor skills in healthy adults. First results suggest that this concept may be transferred to populations with motor and cognitive dysfunctions. In this context, Parkinson's disease (PD) is highly relevant since patients demonstrate deficits in motor learning. Hence, in the present study we sought to explore the effect of a single post-practice exercise bout on motor memory consolidation in PD. For this purpose, 17 patients with PD (Hoehn and Yahr: 1 - 2.5, age: 60.1 ± 7.9 y) practiced a whole-body skill followed by either (i) a moderate-intense bout of cycling, or (ii) seated rest for a total of 30 min. The motor skill required the participants to balance on a tiltable platform (stabilometer) for 30 s. During skill practice, participants performed 15 trials followed by a retention test 1 day and 7 days later. We calculated time in balance (platform within ± 5° from horizontal) for each trial and within- and between-group differences in memory consolidation (i.e. offline learning = skill change from last acquisition block to retention tests) were analyzed. Groups revealed similar improvements during skill practice (F_4,60 = 0.316, p = 0.866), but showed differences in offline learning, which were only evident after 7 days (F_1,14 = 5.602, p = 0.033). Our results suggest that a single post-practice exercise bout is effective in enhancing long-term motor memory consolidation in a population with motor learning impairments. This may point at unique promoting effects of exercise on dopamine neurotransmission involved in memory formation. Future studies should investigate the potential role of exercise-induced effects on the dopaminergic system.

Effects of acute cardiovascular exercise on motor memory encoding and consolidation: A systematic review with meta-analysis

Emerging evidence indicates that acute bouts of cardiovascular exercise promote motor memory formation. In this preregistered meta-analysis (CRD42018106288) we synthesize data from 22 studies published until February 2020, including a total of 862 participants. We calculated standardized mean differences (SMDs) with 95 % confidence intervals (CIs) to assess exercise effects on motor memory encoding and consolidation, respectively. The pooled data indicate that exercise mainly benefits the consolidation of memories, with exercise prior to motor practice improving early non-sleep consolidation (SMD, 0.58; 95 % CI, 0.30-0.86; p < 0.001), and post-practice exercise facilitating sleep-dependent consolidation (SMD, 0.62; 95 % CI, 0.34-0.90; p < 0.001). Strongest effects exist for high exercise intensities, and motor task nature appears to be another relevant modulator. We demonstrate that acute cardiovascular exercise particularly promotes the consolidation of acquired motor memories, and exercise timing, and intensity as well as motor task nature seem to critically modulate this relationship. These findings are discussed within currently proposed models of motor memory formation and considering molecular and systemic mechanisms of neural plasticity.

Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these "micro-offline" gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments = 951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N = 389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N = 118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N = 373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N = 71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning.

Memories replayed: reactivating past successes and new dilemmas

Our experiences continue to be processed 'offline' in the ensuing hours of both wakefulness and sleep. During these different brain states, the memory formed during our experience is replayed or reactivated. Here, we discuss the unique challenges in studying offline reactivation, the growth in both the experimental and analytical techniques available across different animals from rodents to humans to capture these offline events, the important challenges this innovation has brought, our still modest understanding of how reactivation drives diverse synaptic changes across circuits, and how these changes differ (if at all), and perhaps complement, those at memory formation. Together, these discussions highlight critical emerging issues vital for identifying how reactivation affects circuits, and, in turn, behaviour, and provides a broader context for the contributions in this special issue. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.