Memory Reactivation Enables Long-Term Prevention of Interference

Brief memory reactivation may not improve visual perception

Visual perceptual learning often requires a substantial number of trials to observe significant learning effects. Previously Amar-Halpert et al. (2017) have shown that brief reactivation (5 trials/day) is sufficient to improve the performance of the texture discrimination task (TDT), yielding comparable improvements to those achieved through full practice (252 trials/day). The finding is important since it would refine our understanding of learning mechanisms and applications. In the current study, we attempted to replicate these experiments using a larger number of observers and an improved experimental design. Using between-group comparison, we did find significant improvements in the reactivation group and the full-practice group as Amar-Halpert et al. (2017) showed. However, these improvements were comparable to those of the no-reactivation group with no exposure to the TDT task over the same period. Importantly, our within-group comparison showed that both the reactivation and no-reactivation groups exhibited additional significant improvements after further practicing the TDT task for an additional three days, demonstrating that the full-practice effect was significantly superior to the effects of brief memory reactivation or simple test-retest. Besides, when refining the constant stimuli method with fewer stimulus levels and more trials per level, we still observed comparable improvements brought by the reactivation and no-reactivation groups. Therefore, our results suggested that brief memory reactivation may not significantly contribute to the improvement of perceptual learning, and traditional perceptual training could still be a necessary and effective approach for substantial improvements.

Receive, Retain and Retrieve: Psychological and Neurobiological Perspectives on Memory Retrieval

Memory and learning are interdependent processes that involve encoding, storage, and retrieval. Especially memory retrieval is a fundamental cognitive ability to recall memory traces and update stored memory with new information. For effective memory retrieval and learning, the memory must be stabilized from short-term memory to long-term memory. Hence, it is necessary to understand the process of memory retention and retrieval that enhances the process of learning. Though previous cognitive neuroscience research has focused on memory acquisition and storage, the neurobiological mechanisms underlying memory retrieval and its role in learning are less understood. Therefore, this article offers the viewpoint that memory retrieval is essential for selecting, reactivating, stabilizing, and storing information in long-term memory. In arguing how memories are retrieved, consolidated, transmitted, and strengthened for the long term, the article will examine the psychological and neurobiological aspects of memory and learning with synaptic plasticity, long-term potentiation, genetic transcription, and theta oscillation in the brain.

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.

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.

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.

Elevated integration within the reward network underlies vulnerability to distress

Distress tolerance (DT), the capability to persist under negative circumstances, underlies a range of psychopathologies. It has been proposed that DT may originate from the activity and connectivity in diverse neural networks integrated by the reward system. To test this hypothesis, we examined the link between DT and integration and segregation in the reward network as derived from resting-state functional connectivity data. DT was measured in 147 participants from a large community sample using the Behavioral Indicator of Resiliency to Distress task. Prior to DT evaluation, participants underwent a resting-state functional magnetic resonance imaging scan. For each participant, we constructed a whole-brain functional connectivity network and calculated the degree of reward network integration and segregation based on the extent to which reward network nodes showed functional connections within and outside their network. We found that distress-intolerant participants demonstrated heightened reward network integration relative to the distress-tolerant participants. In addition, these differences in integration were higher relative to the rest of the brain and, more specifically, the somatomotor network, which has been implicated in impulsive behavior. These findings support the notion that increased integration in large-scale brain networks may constitute a risk for distress intolerance and its psychopathological correlates.

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.

Non-linear susceptibility to interferences in declarative memory formation

After encoding, memories go through a labile state followed by a stabilization process known as consolidation. Once consolidated they can enter a new labile state after the presentation of a reminder of the original memory, followed by a period of re-stabilization (reconsolidation). During these periods of lability the memory traces can be modified. Currently, some studies show a rapid stabilization after 30 min, while others show that stabilization occurs after longer periods (e.g. > 6 h). Here we investigate the effect of an interference treatment on declarative memory consolidation, comparing distinct time intervals after acquisition. On day 1, participants learned a list of non- syllable pairs (List 1). 5 min, 30 min, 3 h or 8 h later, they received an interference list (List 2) that acted as an amnesic agent. On day 2 (48 h after training) participants had to recall List 1 first, followed by List 2. We found that the List 1 memory was susceptible to interference when List 2 was administered 5 min or 3 h after learning but not when it was administered 30 min or 8 h after. We propose the possibility that this rapid memory protection could be induced by a fast and transient neocortical integration. Our results open a discussion about the contribution of molecular and systemic aspects to memory consolidation.

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.

Reactivation-induced motor skill learning

Learning motor skills commonly requires repeated execution to achieve gains in performance. Motivated by memory reactivation frameworks predominantly originating from fear-conditioning studies in rodents, which have extended to humans, we asked the following: Could motor skill learning be achieved by brief memory reactivations? To address this question, we had participants encode a motor sequence task in an initial test session, followed by brief task reactivations of only 30 s each, conducted on separate days. Learning was evaluated in a final retest session. The results showed that these brief reactivations induced significant motor skill learning gains. Nevertheless, the efficacy of reactivations was not consistent but determined by the number of consecutive correct sequences tapped during memory reactivations. Highly continuous reactivations resulted in higher learning gains, similar to those induced by full extensive practice, while lower continuity reactivations resulted in minimal learning gains. These results were replicated in a new independent sample of subjects, suggesting that the quality of memory reactivation, reflected by its continuity, regulates the magnitude of learning gains. In addition, the change in noninvasive brain stimulation measurements of corticospinal excitability evoked by transcranial magnetic stimulation over primary motor cortex between pre- and postlearning correlated with retest and transfer performance. These results demonstrate a unique form of rapid motor skill learning and may have far-reaching implications, for example, in accelerating motor rehabilitation following neurological injuries.

Explaining Individual Differences in Motor Behavior by Intrinsic Functional Connectivity and Corticospinal Excitability

Motor performance varies substantially between individuals. This variance is rooted in individuals' innate motor abilities, and should thus have a neural signature underlying these differences in behavior. Could these individual differences be detectable with neural measurements acquired at rest? Here, we tested the hypothesis that motor performance can be predicted by resting motor-system functional connectivity and motor-evoked-potentials (MEPs) induced by non-invasive brain stimulation. Twenty healthy right handed subjects performed structural and resting-state fMRI scans. On a separate day, MEPs were measured using transcranial magnetic stimulation (TMS) over the contrateral primary motor cortex (M1). At the end of the session, participants performed a finger-tapping task using their left non-dominant hand. Resting-state functional connectivity between the contralateral M1 and the supplementary motor area (SMA) predicted motor task performance, indicating that individuals with stronger resting M1-SMA functional connectivity exhibit better motor performance. This prediction was neither improved nor reduced by the addition of corticospinal excitability to the model. These results confirm that motor behavior can be predicted from neural measurements acquired prior to task performance, primarily relying on resting functional connectivity rather than corticospinal excitability. The ability to predict motor performance from resting neural markers, provides an opportunity to identify the extent of successful rehabilitation following neurological damage.

Susceptibility of consolidated procedural memory to interference is independent of its active task-based retrieval

Reconsolidation theory posits that upon retrieval, consolidated memories are destabilized and need to be restabilized in order to persist. It has been suggested that experience with a competitive task immediately after memory retrieval may interrupt these restabilization processes leading to memory loss. Indeed, using a motor sequence learning paradigm, we have recently shown that, in humans, interference training immediately after active task-based retrieval of the consolidated motor sequence knowledge may negatively affect its performance levels. Assessing changes in tapping pattern before and after interference training, we also demonstrated that this performance deficit more likely indicates a genuine memory loss rather than an initial failure of memory retrieval. Here, applying a similar approach, we tested the necessity of the hypothetical retrieval-induced destabilization of motor memory to allow its impairment. The impact of memory retrieval on performance of a new motor sequence knowledge acquired during the interference training was also evaluated. Similar to the immediate post-retrieval interference, interference training alone without the preceding active task-based memory retrieval was also associated with impairment of the pre-established motor sequence memory. Performance levels of the sequence trained during the interference training, on the other hand, were impaired only if this training was given immediately after memory retrieval. Noteworthy, an 8-hour interval between memory retrieval and interference allowed to express intact performance levels for both sequences. The current results suggest that susceptibility of the consolidated motor memory to behavioral interference is independent of its active task-based retrieval. Differential effects of memory retrieval on performance levels of the new motor sequence encoded during the interference training further suggests that memory retrieval may influence the way new information is stored by facilitating its integration within the retrieved memory trace. Thus, impairment of the pre-established motor memory may reflect interference from a competing memory trace rather than involve interruption of reconsolidation.

Neuromodulation of reinforced skill learning reveals the causal function of prefrontal cortex

Accumulating evidence has suggested functional interactions between prefrontal cortex (PFC) and dissociable large-scale networks. However, how these networks interact in the human brain to enable complex behaviors is not well-understood. Here, using a combination of behavioral, brain stimulation and neuroimaging paradigms, we tested the hypothesis that human PFC is required for successful reinforced skill formation. We additionally tested the extent to which PFC-dependent skill formation is related to intrinsic functional communication with this region. We report that inhibitory noninvasive transcranial magnetic stimulation over lateral PFC, a hub region with a diverse connectivity profile, causally modulated effective reinforcement-based motor skill acquisition. Furthermore, PFC-dependent skill formation was strongly related to the strength of functional connectivity between the PFC and regions in the sensorimotor network. These results point to the involvement of lateral PFC in the neural architecture that underlies the acquisition of complex skills, and suggest that, in relation to skill acquisition, this region may be involved in functional interactions with sensorimotor networks.