Reactivation-induced motor skill learning

Procedural Motor Memory Deficits in Patients With Long-COVID

BACKGROUND AND OBJECTIVES

At least 15% of patients who recover from acute severe acute respiratory syndrome coronavirus 2 infection experience lasting symptoms ("Long-COVID") including "brain fog" and deficits in declarative memory. It is not known if Long-COVID affects patients' ability to form and retain procedural motor skill memories. The objective was to determine the ability of patients with Long-COVID to acquire and consolidate a new procedural motor skill over 2 training days. The primary outcome was to determine difference in early learning, measured as the increase in correct sequence typing speed over the initial 11 practice trials of a new skill. The secondary outcomes were initial and final typing speed on days 1 and 2, learning rate, overnight consolidation, and typing accuracy.

METHODS

In this prospective, cross-sectional, online, case-control study, participants learned a sequential motor skill over 2 consecutive days (NCT05746624). Patients with Long-COVID (reporting persistent post-coronavirus disease 2019 [COVID-19] symptoms for more than 4 weeks) were recruited at the NIH. Patients were matched one-to-one by age and sex to controls recruited during the pandemic using a crowd-sourcing platform. Selection criteria included age 18-90 years, English speaking, right-handed, able to type with the left hand, denied active fever or respiratory infection, and no previous task exposure. Data were also compared with an age-matched and sex-matched control group who performed the task online before the COVID-19 pandemic (prepandemic controls).

RESULTS

In total, 105 of 236 patients contacted agreed to participate and completed the experiment (mean ± SD age 46 ± 12.8 years, 82% female). Both healthy control groups had 105 participants (mean age 46 ± 13.1 and 46 ± 11.9 years, 82% female). Early learning was comparable across groups (Long-COVID: 0.36 ± 0.24 correct sequences/second, pandemic controls: 0.36 ± 0.53 prepandemic controls: 0.38 ± 0.57, patients vs pandemic controls [CI -0.068 to 0.067], vs prepandemic controls [CI -0.084 to 0.052], and between controls [CI -0.083 to 0.053], p = 0.82). Initial and final typing speeds on days 1 and 2 were slower in patients than controls. Patients with Long-COVID showed a significantly reduced overnight consolidation and a nonsignificant trend to reduced learning rates.

DISCUSSION

Early learning was comparable in patients with Long-COVID and controls. Anomalous initial performance is consistent with executive dysfunction. Reduction in overnight consolidation may relate to deficits in procedural memory formation.

Early excitatory-inhibitory cortical modifications following skill learning are associated with motor memory consolidation and plasticity overnight

Consolidation of motor memories is vital to offline enhancement of new motor skills and involves short and longer-term offline processes following learning. While emerging evidence link glutamate and GABA dynamics in the primary motor cortex (M1) to online motor skill practice, its relationship with offline consolidation processes in humans is unclear. Using two-day repeated measures of behavioral and multimodal neuroimaging data before and following motor sequence learning, we show that short-term glutamatergic and GABAergic responses in M1 within minutes after learning were associated with longer-term learning-induced functional, structural, and behavioral modifications overnight. Furthermore, Glutamatergic and GABAergic modifications were differentially associated with different facets of motor memory consolidation. Our results point to unique and distinct roles of Glutamate and GABA in motor memory consolidation processes in the human brain across timescales and mechanistic levels, tying short-term changes on the neurochemical level to overnight changes in macroscale structure, function, and behavior.

Age-Related Differences in Motor Skill Transfer with Brief Memory Reactivation

Motor memories can be strengthened through online practice and offline consolidation. Offline consolidation involves the stabilization of memory traces in post-practice periods. Following initial consolidation of a motor memory, subsequent practice of the motor skill can lead to reactivation and reconsolidation of the memory trace. The length of motor memory reactivation may influence motor learning outcomes; for example, brief, as opposed to long, practice of a previously learned motor skill appears to optimize intermanual transfer in healthy young adults. However, the influence of aging on reactivation-based motor learning has been scarcely explored. Here, the effects of brief and long motor memory reactivation schedules on the retention and intermanual transfer of a visuomotor tracing task are explored in healthy older adults. Forty older adults practiced a virtual star-tracing task either three ("brief reactivation") or ten ("long reactivation") times per session over a two-week period. Comparison with a previously reported group of younger adults revealed significant age-related differences in the effect of the motor memory reactivation schedule on the intermanual transfer of the motor task. In older adults, unlike younger adults, no significant between-group differences were found by practice condition in the speed, accuracy, or skill of intermanual task transfer. That is, motor task transfer in healthy younger, but not older, adults appears to benefit from brief memory reactivation. These results support the use of age-specific motor training approaches and may inform motor practice scheduling, with possible implications for physical rehabilitation, sport, and music.

Plasticity-stability dynamics during post-training processing of learning

Learning continues beyond the end of training. Post-training learning is supported by changes in plasticity and stability in the brain during both wakefulness and sleep. However, the lack of a unified measure for assessing plasticity and stability dynamics during training and post-training periods has limited our understanding of how these dynamics shape learning. Focusing primarily on procedural learning, we integrate work using behavioral paradigms and a recently developed measure, the excitatory-to-inhibitory (E/I) ratio, to explore the delicate balance between plasticity and stability and its relationship to post-training learning. This reveals plasticity-stability cycles during both wakefulness and sleep that enhance learning and protect it from new learning during post-training processing.

Increased cortical inhibition following brief motor memory reactivation supports reconsolidation and overnight offline learning gains

Practicing motor skills stabilizes and strengthens motor memories by repeatedly reactivating and reconsolidating them. The conventional view, by which a repetitive practice is required for substantially improving skill performance, has been recently challenged by behavioral experiments, in which even brief reactivations of the motor memory have led to significant improvements in skill performance. However, the mechanisms which facilitate brief reactivation-induced skill improvements remain elusive. While initial memory consolidation has been repeatedly associated with increased neural excitation and disinhibition, reconsolidation has been shown to involve a poorly understood mixture of both excitatory and inhibitory alterations. Here, we followed a 3-d reactivation-reconsolidation framework to examine whether the excitatory/inhibitory mechanisms which underlie brief reactivation and repetitive practice differ. Healthy volunteers practiced a motor sequence learning task using either brief reactivation or repetitive practice and were assessed using ultrahigh field (7T) magnetic resonance spectroscopy at the primary motor cortex (M1). We found that increased inhibition (GABA concentrations) and decreased excitation/inhibition (glutamate/GABA ratios) immediately following the brief reactivation were associated with overnight offline performance gains. These gains were on par with those exhibited following repetitive practice, where no correlations with inhibitory or excitatory changes were observed. Our findings suggest that brief reactivation and repetitive practice depend on fundamentally different neural mechanisms and that early inhibition-and not excitation-is particularly important in supporting the learning gains exhibited by brief reactivation.

Prefrontal stimulation as a tool to disrupt hippocampal and striatal reactivations underlying fast motor memory consolidation

BACKGROUND

Recent evidence suggests that hippocampal replay in humans support rapid motor memory consolidation during epochs of wakefulness interleaved with task practice.

OBJECTIVES/HYPOTHESES

The goal of this study was to test whether such reactivation patterns can be modulated with experimental interventions and in turn influence fast consolidation. We hypothesized that non-invasive brain stimulation targeting hippocampal and striatal networks via the prefrontal cortex would influence brain reactivation and the rapid form of motor memory consolidation.

METHODS

Theta-burst stimulation was applied to a prefrontal cluster functionally connected to both the hippocampus and striatum of young healthy participants before they learned a motor sequence task in a functional magnetic resonance imaging (fMRI) scanner. Neuroimaging data acquired during task practice and the interleaved rest epochs were analyzed to comprehensively characterize the effect of stimulation on the neural processes supporting fast motor memory consolidation.

RESULTS

Our results collectively show that active, as compared to control, theta-burst stimulation of the prefrontal cortex hindered fast motor memory consolidation. Converging evidence from both univariate and multivariate analyses of fMRI data indicate that active stimulation disrupted hippocampal and caudate responses during inter-practice rest, presumably altering the reactivation of learning-related patterns during the micro-offline consolidation episodes. Last, stimulation altered the link between the brain and the behavioral markers of the fast consolidation process.

CONCLUSION

These results suggest that stimulation targeting deep brain regions via the prefrontal cortex can be used to modulate hippocampal and striatal reactivations in the human brain and influence motor memory consolidation.

Initial motor skill performance predicts future performance, but not learning

People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants' future performance and learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We used machine learning to predict future performance and learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. Strong correlations were observed between initial and final performance, and individual learning was not predicted. While canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, development of novel tasks may shed light on the underlying mechanism of individual skill learning, relevant for real-life scenarios.

Reactivation-induced memory integration prevents proactive interference in perceptual learning

We acquire perceptual skills through experience to adapt ourselves to the changing environment. Accomplishing an effective skill acquisition is a main purpose of perceptual learning research. Given the often observed learning effect specificity, multiple perceptual learnings with shared parameters could serve to improve the generalization of the learning effect. However, the interference between the overlapping memory traces of different learnings may impede this effort. Here, we trained human participants on an orientation discrimination task. We observed a proactive interference effect that the first training blocked the second training at its untrained location. This was a more pronounced effect than the well-known location specificity in perceptual learning. We introduced a short reactivation of the first training before the second training and successfully eliminated the proactive interference when the second training was inside the reconsolidation time window of the reactivated first training. Interestingly, we found that practicing an irrelevant task at the location of the second training immediately after the reactivation of the first training could also restore the effect of the second training but in a smaller magnitude, even if the second training was conducted outside of the reconsolidation window. We proposed a two-level mechanism of reactivation-induced memory integration to account for these results. The reactivation-based procedure could integrate either the previously trained and untrained locations or the two trainings at these locations, depending on the activated representations during the reconsolidation process. The findings provide us with new insight into the roles of long-term memory mechanisms in perceptual learning.

Reactivation-induced motor skill modulation does not operate at a rapid micro-timescale level

Abundant evidence shows that consolidated memories are susceptible to modifications following their reactivation. Processes of memory consolidation and reactivation-induced skill modulation have been commonly documented after hours or days. Motivated by studies showing rapid consolidation in early stages of motor skill acquisition, here we asked whether motor skill memories are susceptible to modifications following brief reactivations, even at initial stages of learning. In a set of experiments, we collected crowdsourced online motor sequence data to test whether post-encoding interference and performance enhancement occur following brief reactivations in early stages of learning. Results indicate that memories forming during early learning are not susceptible to interference nor to enhancement within a rapid reactivation-induced time window, relative to control conditions. This set of evidence suggests that reactivation-induced motor skill memory modulation might be dependent on consolidation at the macro-timescale level, requiring hours or days to occur.

Does Motor Memory Reactivation through Practice and Post-Learning Sleep Modulate Consolidation?

Retrieving previously stored information makes memory traces labile again and can trigger restabilization in a strengthened or weakened form depending on the reactivation condition. Available evidence for long-term performance changes upon reactivation of motor memories and the effect of post-learning sleep on their consolidation remains scarce, and so does the data on the ways in which subsequent reactivation of motor memories interacts with sleep-related consolidation. Eighty young volunteers learned (Day 1) a 12-element Serial Reaction Time Task (SRTT) before a post-training Regular Sleep (RS) or Sleep Deprivation (SD) night, either followed (Day 2) by morning motor reactivation through a short SRTT testing or no motor activity. Consolidation was assessed after three recovery nights (Day 5). A 2 × 2 ANOVA carried on proportional offline gains did not evidence significant Reactivation (Morning Reactivation/No Morning Reactivation; p = 0.098), post-training Sleep (RS/SD; p = 0.301) or Sleep*Reactivation interaction (p = 0.257) effect. Our results are in line with prior studies suggesting a lack of supplementary performance gains upon reactivation, and other studies that failed to disclose post-learning sleep-related effects on performance improvement. However, lack of overt behavioural effects does not detract from the possibility of sleep- or reconsolidation-related covert neurophysiological changes underlying similar behavioural performance levels.

Reconsolidation: A paradigm shift

This commentary is part of a special issue honoring Karim Nader and his focal role in igniting the reconsolidation field. The commentary describes in broad strokes the evolution of the field, its branches, major challenges, and future endeavors.

Brief memory reactivations induce learning in the numeric domain

Learning of arithmetic facts such as the multiplication table requires time-consuming, repeated practice. In light of evidence indicating that reactivation of encoded memories can modulate learning and memory processes at the synaptic, system and behavioral levels, we asked whether brief memory reactivations can induce human learning in the numeric domain. Adult participants performed a number-fact retrieval task in which they learned arbitrary numeric facts. Following encoding and a baseline test, 3 passive, brief reactivation sessions of only 40 s each were conducted on separate days. Learning was evaluated in a retest session. Results showed reactivations induced learning, with improved performance at retest relative to baseline test. Furthermore, performance was superior compared to a control group performing test-retest sessions without reactivations, who showed significant memory deterioration. A standard practice group completed active-retrieval sessions on 3 separate days, and showed significant learning gains. Interestingly, while these gains were higher than those of the reactivations group, subjects showing reactivation-induced learning were characterized by superior efficiency relative to standard practice subjects, with higher rate of improvement per practice time. A follow-up long-term retention experiment showed that 30 days following initial practice, weekly brief reactivations reduced forgetting, with participants performing superior to controls undergoing the same initial practice without reactivations. Overall, the results demonstrate that brief passive reactivations induce efficient learning and reduce forgetting within a numerical context. Time-efficient practice in the numeric domain carries implications for enhancement of learning strategies in daily-life settings.

A distinct route for efficient learning and generalization in autism

Visual skill learning is the process of improving responses to surrounding visual stimuli.¹ For individuals with autism spectrum disorders (ASDs), efficient skill learning may be especially valuable due to potential difficulties with sensory processing² and challenges in adjusting flexibly to changing environments.^3,4 Standard skill learning protocols require extensive practice with multiple stimulus repetitions,^5-7 which may be difficult for individuals with ASD and create abnormally specific learning with poor ability to generalize.⁴ Motivated by findings indicating that brief memory reactivations can facilitate skill learning,^8,9 we hypothesized that reactivation learning with few stimulus repetitions will enable efficient learning in individuals with ASD, similar to their learning with standard extensive practice protocols used in previous studies.^4,10,11 We further hypothesized that in contrast to experience-dependent plasticity often resulting in specificity, reactivation-induced learning would enable generalization patterns in ASD. To test our hypotheses, high-functioning adults with ASD underwent brief reactivations of an encoded visual learning task, consisting of only 5 trials each instead of hundreds. Remarkably, individuals with ASD improved their visual discrimination ability in the task substantially, demonstrating successful learning. Furthermore, individuals with ASD generalized learning to an untrained visual location, indicating a unique benefit of reactivation learning mechanisms for ASD individuals. Finally, an additional experiment showed that without memory reactivations ASD subjects did not demonstrate efficient learning and generalization patterns. Taken together, the results provide proof-of-concept evidence supporting a distinct route for efficient visual learning and generalization in ASD, which may be beneficial for skill learning in other sensory and motor domains.

The evidence for and against reactivation-induced memory updating in humans and nonhuman animals

Systematic investigation of reactivation-induced memory updating began in the 1960s, and a wave of research in this area followed the seminal articulation of "reconsolidation" theory in the early 2000s. Myriad studies indicate that memory reactivation can cause previously consolidated memories to become labile and sensitive to weakening, strengthening, or other forms of modification. However, from its nascent period to the present, the field has been beset by inconsistencies in researchers' abilities to replicate seemingly established effects. Here we review these many studies, synthesizing the human and nonhuman animal literature, and suggest that these failures-to-replicate reflect a highly complex and delicately balanced memory modification system, the substrates of which must be finely tuned to enable adaptive memory updating while limiting maladaptive, inaccurate modifications. A systematic approach to the entire body of evidence, integrating positive and null findings, will yield a comprehensive understanding of the complex and dynamic nature of long-term memory storage and the potential for harnessing modification processes to treat mental disorders driven by pervasive maladaptive memories.

Repetitive training of contralateral limb through reconsolidation strengthens motor skills

Consolidated memories become transiently labile after memory reactivation, allowing update through reconsolidation. Although previous reports have indicated that the effects of post-reactivation training depend on the type of practice, it is unclear whether post-reactivation motor skill training of one limb can enhance the performance of the opposite limb. The present study aimed to investigate whether post-reactivation training (performing an isometric pinch force task) under two different training conditions using the left limb would enhance motor skills of the right limb through reconsolidation. Motor skills were measured in 38 healthy right-handed young adults during three sessions (S): S1 (right-hand training), S2 (memory reactivation and left-hand training 6 h after S1), and S3 (right-hand motor skill test 24 h after S1). Participants were assigned to one of three groups according to the task performed during S2: untrained controls (no training), left-hand training (constant force conditions), or left-hand training (variable force conditions). Left-hand training after memory reactivation during S2 significantly enhanced the motor skills of the right hand. Notably, constant training conditions significantly increased performance compared to the control group. These findings suggest that post-reactivation training in one limb effectively enhances motor skills in the opposite limb, and the effects depend on the training strategy, which has important implications for motor rehabilitation.

Less practice makes just as perfect

How we can optimise behavioural gains from training is a key neuroscientific question. The role of consolidation has often been overlooked but offers a substantial potential target for therapeutic approaches. Here, we discuss the mechanisms underpinning off-line skill acquisition, as reported in a recent study by Herszage and colleagues.