Neuroscience: Memory modification without catastrophe.

Adaptive behaviour is supported by changes in neuronal networks. Insight into maintaining these memories - preventing their catastrophic loss - despite further network changes occurring due to novel learning is provided in a new study.

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.

Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit.

Once formed, the fate of memory is uncertain. Subsequent offline interactions between even different memory types (actions versus words) modify retention.1,2,3,4,5,6 These interactions may occur due to different oscillations functionally linking together different memory types within a circuit.7,8,9,10,11,12,13 With memory processing driving the circuit, it may become less susceptible to external influences.14 We tested this prediction by perturbing the human brain with single pulses of transcranial magnetic stimulation (TMS) and simultaneously measuring the brain activity changes with electroencephalography (EEG15,16,17). Stimulation was applied over brain areas that contribute to memory processing (dorsolateral prefrontal cortex, DLPFC; primary motor cortex, M1) at baseline and offline, after memory formation, when memory interactions are known to occur.1,4,6,10,18 The EEG response decreased offline (compared with baseline) within the alpha/beta frequency bands when stimulation was applied to the DLPFC, but not to M1. This decrease exclusively followed memory tasks that interact, revealing that it was due specifically to the interaction, not task performance. It remained even when the order of the memory tasks was changed and so was present, regardless of how the memory interaction was produced. Finally, the decrease within alpha power (but not beta) was correlated with impairment in motor memory, whereas the decrease in beta power (but not alpha) was correlated with impairment in word-list memory. Thus, different memory types are linked to different frequency bands within a DLPFC circuit, and the power of these bands shapes the balance between interaction and segregation between these memories.

Does Cardiorespiratory Fitness Protect Memory from Sleep Deprivation?

INTRODUCTION: Animal studies have demonstrated that physical exercise can protect memory from the effects of sleep deprivation (SD). We examined whether having a high cardiorespiratory fitness (V̇O 2peak ) is associated with an enhanced capacity to encode episodic memory after one night of SD. METHODS: Twenty-nine healthy young participants were allocated into either an SD group ( n = 19) that underwent 30 h of uninterrupted wakefulness, or a sleep control (SC) group ( n = 10) that followed a regular sleep routine. Following either the SD or SC period, participants were asked to view 150 images as the encoding part of the episodic memory task. Ninety-six hours after viewing the images, participants returned to the laboratory to perform the recognition part of the episodic memory task, which required the visual discrimination of the 150 images previously presented from 75 new images introduced as distractors. Cardiorespiratory fitness (V̇O 2peak ) was assessed with a bike ergometer graded exercise test. Group differences in memory performance were assessed with independent t tests and associations between V̇O 2peak and memory with multiple linear regression. RESULTS: The SD group showed a significant increase in subjective fatigue (mean difference [MD] [standard error {SE}] = 38.94 [8.82]; P = 0.0001) and a worse capacity to identify the original 150 images (MD [SE] = -0.18 [0.06]; P = 0.005) and discriminate them from distractors (MD [SE] = -0.78 [0.21] P = 0.001). When adjusted for fatigue, higher V̇O 2peak was significantly associated with better memory scores in the SD (R 2 = 0.41; ß [SE] = 0.03 [0.01]; P = 0.015) but not in the SC group ( R2 = 0.23; ß [SE] = 0.02 [0.03]; P = 0.408). CONCLUSIONS: These results confirm that SD before encoding impairs the capacity to create robust episodic memories and provide preliminary support to the hypothesis that maintaining high levels of cardiorespiratory fitness could have a protective effect against the disruptive effects of sleep loss on memory.

Acute evening high-intensity interval training may attenuate the detrimental effects of sleep restriction on long-term declarative memory.

Recent evidence shows that a nap and acute exercise synergistically enhanced memory. Additionally, human-based cross-sectional studies and animal experiments suggest that physical exercise may mitigate the cognitive impairments of poor sleep quality and sleep restriction, respectively. We evaluated whether acute exercise may offset sleep restriction's impairment of long-term declarative memory compared to average sleep alone. A total of 92 (82% females) healthy young adults (24.6 ± 4.2 years) were randomly allocated to one of four evening groups: sleep restriction only (S5, 5-6 h/night), average sleep only (S8, 8-9 h/night), high-intensity interval training (HIIT) before restricted sleep (HIITS5), or HIIT before average sleep (HIITS8). Groups either followed a 15-min remote HIIT video or rest period in the evening (7:00 p.m.) prior to encoding 80 face-name pairs. Participants completed an immediate retrieval task in the evening. The next morning a delayed retrieval task was given after their subjectively documented sleep opportunities. Long-term declarative memory performance was assessed with the discriminability index (d') during the recall tasks. While our results showed that the d' of S8 (0.58 ± 1.37) was not significantly different from those of HIITS5 (-0.03 ± 1.64, p = 0.176) and HIITS8 (-0.20 ± 1.28, p = 0.092), there was a difference in d' compared to S5 (-0.35 ± 1.64, p = 0.038) at the delayed retrieval. These results suggest that the acute evening HIIT partially reduced the detrimental effects of sleep restriction on long-term declarative memory.

Memory leaks: information shared across memory systems.

The brain is highly segregated. Multiple mechanisms ensure that different types of memories are processed independently. Nonetheless, information leaks out across these memory systems. Only recently has the diversity of these leaks been revealed. Different memory types (skills vs. facts) can interact in simple ways, either allowing or preventing their further processing, or in more complex ways, allowing the sharing of abstract information between memories. Leaks occur from memories dependent upon hippocampal circuits, which have properties critical for leaks and activity patterns related to memory interactions. This hippocampal contribution is likely achieved in concert with cortical areas. Leaks between memories enable the application of knowledge in novel situations, explain learning dynamics, and solve important problems inherent to memory formation.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus.

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation.

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

A Common Task Structure Links Together the Fate of Different Types of Memories.

Our memories frequently have features in common. For example, a learned sequence of words or actions can follow a common rule, which determines their serial order, despite being composed of very different events [1, 2]. This common abstract structure might link the fates of memories together. We tested this idea by creating different types of memory task: a sequence of words or actions that either did or did not have a common structure. Participants learned one of these memory tasks and then they learned another type of memory task 6 h later, either with or without the same structure. We then tested the newly formed memory's susceptibility to interference. We found that the newly formed memory was protected from interference when it shared a common structure with the earlier memory. Specifically, learning a sequence of words protected a subsequent sequence of actions learned hours later from interference, and conversely, learning a sequence of actions protected a subsequent sequence of words learned hours later from interference provided the sequences shared a common structure. Yet this protection of the newly formed memory came at a cost. The earlier memory had disrupted recall when it had the same rather than a different structure to the newly formed and protected memory. Thus, a common structure can determine what is retained (i.e., protected) and what is modified (i.e., disrupted). Our work reveals that a shared common structure links the fate of otherwise different types of memories together and identifies a novel mechanism for memory modification.

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'.

A consensus statement: defining terms for reactivation analysis.

During a two-day Royal Society meeting entitled 'Memory reactivation: replaying events past, present and future' held at Chicheley Hall in May, 2019, we discussed and defined a set of terms for investigating and reporting in memory reactivations to facilitate a common language and thus simplifying comparison of results. Here, we present the results of the discussion and supply a set of terms such as reactivation and replay, for which the authors have reached a common consensus. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Exercising before a nap benefits memory better than napping or exercising alone.

Sleep leads to the enhancement of memory, and physical exercise also improves memory along with beneficial effects on sleep quality. Potentially, sleep and exercise may operate independently upon memory; alternatively, they may operate synergistically to boost memory above and beyond exercise or sleep alone. We tested this hypothesis in 115 young healthy adults (23 ± 3.9 years) randomly allocated to one of the four conditions in a 2 (exercise vs. no exercise) × 2 (nap vs. no nap) design. The exercise intervention consisted of a 40-minute, moderate intensity cycling, while the no exercise condition was an equivalent period of rest. This was followed by a learning session in which participants memorized a set of 45 neutral pictures for a later test. Subsequently, participants were exposed to either a 60-minute sleep period (nap) or an equivalent time of resting wakefulness, followed by a visual recognition test. We found a significant interaction between the effects of exercise and nap (p = 0.014, η p2 = 0.053), without significant main effects of exercise or nap conditions. Participants who experienced both exercise plus nap were significantly more accurate (83.8 ± 2.9) than those who only napped (81.1 ± 5.4, p = 0.027) and those who only exercised (78.6 ± 10.3, p = 0.012). Within the combined nap plus exercise group, higher recognition accuracies were associated with higher sleep spindle densities (r = 0.46, p = 0.015). Our results demonstrate that short-term exercise and a nap improve recognition memory over a nap or exercise alone. Exercise and sleep are not independent factors operating separately upon memory but work together to enhance long-term memory.

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

Skills continue to be enhanced even once practice has ceased. Such offline improvements were for a time regarded as the sole preserve of sleep, but recent work shows that they can occur within only a few seconds.

Memory instability as a gateway to generalization.

Our present frequently resembles our past. Patterns of actions and events repeat throughout our lives like a motif. Identifying and exploiting these patterns are fundamental to many behaviours, from creating grammar to the application of skill across diverse situations. Such generalization may be dependent upon memory instability. Following their formation, memories are unstable and able to interact with one another, allowing, at least in principle, common features to be extracted. Exploiting these common features creates generalized knowledge that can be applied across varied circumstances. Memory instability explains many of the biological and behavioural conditions necessary for generalization and offers predictions for how generalization is produced.

Exercising Control Over Memory Consolidation.

Exercise can improve human cognition. A mechanistic connection between exercise and cognition has been revealed in several recent studies. Exercise increases cortical excitability and this in turn leads to enhanced memory consolidation. Together these studies dovetail with our growing understanding of memory consolidation and how it is regulated through changes in motor cortical excitability.

Effects of tDCS on motor learning and memory formation: A consensus and critical position paper.

Motor skills are required for activities of daily living. Transcranial direct current stimulation (tDCS) applied in association with motor skill learning has been investigated as a tool for enhancing training effects in health and disease. Here, we review the published literature investigating whether tDCS can facilitate the acquisition, retention or adaptation of motor skills. Work in multiple laboratories is underway to develop a mechanistic understanding of tDCS effects on different forms of learning and to optimize stimulation protocols. Efforts are required to improve reproducibility and standardization. Overall, reproducibility remains to be fully tested, effect sizes with present techniques vary over a wide range, and the basis of observed inter-individual variability in tDCS effects is incompletely understood. It is recommended that future studies explicitly state in the Methods the exploratory (hypothesis-generating) or hypothesis-driven (confirmatory) nature of the experimental designs. General research practices could be improved with prospective pre-registration of hypothesis-based investigations, more emphasis on the detailed description of methods (including all pertinent details to enable future modeling of induced current and experimental replication), and use of post-publication open data repositories. A checklist is proposed for reporting tDCS investigations in a way that can improve efforts to assess reproducibility.

Dual enhancement mechanisms for overnight motor memory consolidation.

Our brains are constantly processing past events [1]. These off-line processes consolidate memories, leading in the case of motor skill memories to an enhancement in performance between training sessions. A similar magnitude of enhancement develops over a night of sleep following an implicit task, when a sequence of movements is acquired unintentionally, or following an explicit task, when the same sequence is acquired intentionally [2]. What remains poorly understood, however, is whether these similar offline improvements are supported by similar circuits, or through distinct circuits. We set out to distinguish between these possibilities by applying Transcranial Magnetic Stimulation (TMS), over the primary motor cortex (M1) or the inferior parietal lobule (IPL) immediately after learning in either the explicit or implicit task. These brain areas have both been implicated in encoding aspects of a motor sequence, and subsequently supporting offline improvements over sleep [3-5]. Here we show that offline improvements following the explicit task are dependent upon a circuit that includes M1 but not IPL. By contrast, offline improvements following the implicit task are dependent upon a circuit that includes IPL but not M1. Our work establishes the critical contribution made by M1 and IPL circuits to offline memory processing, and reveals that distinct circuits support similar offline improvements.

Memory Processing: Ripples in the Resting Brain.

Recent work has shown that, during sleep, a functional circuit is created amidst a general breakdown in connectivity following fast-frequency bursts of brain activity. The findings question the unconscious nature of deep sleep, and provide an explanation for its contribution to memory processing.

Unstable Memories Create a High-Level Representation that Enables Learning Transfer.

A memory is unstable, making it susceptible to interference and disruption, after its acquisition [1-4]. The function or possible benefit of a memory being unstable at its acquisition is not well understood. Potentially, instability may be critical for the communication between recently acquired memories, which would allow learning in one task to be transferred to the other subsequent task [1, 5]. Learning may be transferred between any memories that are unstable, even between different types of memory. Here, we test the link between a memory being unstable and the transfer of learning to a different type of memory task. We measured how learning in one task transferred to and thus improved learning in a subsequent task. There was transfer from a motor skill to a word list task and, vice versa, from a word list to a motor skill task. What was transferred was a high-level relationship between elements, rather than knowledge of the individual elements themselves. Memory instability was correlated with subsequent transfer, suggesting that transfer was related to the instability of the memory. Using different methods, we stabilized the initial memory, preventing it from being susceptible to interference, and found that these methods consistently prevented transfer to the subsequent memory task. This suggests that the transfer of learning across diverse tasks is due to a high-level representation that can only be formed when a memory is unstable. Our work has identified an important function of memory instability.