Targeting targeted memory reactivation: Characteristics of cued reactivation in sleep

First-night effect reduces the beneficial effects of sleep on visual plasticity and modifies the underlying neurochemical processes

Individuals experience difficulty falling asleep in a new environment, termed the first night effect (FNE). However, the impact of the FNE on sleep-induced brain plasticity remains unclear. Here, using a within-subject design, we found that the FNE significantly reduces visual plasticity during sleep in young adults. Sleep-onset latency (SOL), an indicator of the FNE, was significantly longer during the first sleep session than the second session, confirming the FNE. We assessed performance gains in visual perceptual learning after sleep and increases in the excitatory-to-inhibitory neurotransmitter (E/I) ratio in early visual areas during sleep using magnetic resonance spectroscopy and polysomnography. These parameters were significantly smaller in sleep with the FNE than in sleep without the FNE; however, these parameters were not correlated with SOL. These results suggest that while the neural mechanisms of the FNE and brain plasticity are independent, sleep disturbances temporarily block the neurochemical process fundamental for brain plasticity.

Episodic long-term memory formation during slow-wave sleep

We are unresponsive during slow-wave sleep but continue monitoring external events for survival. Our brain wakens us when danger is imminent. If events are non-threatening, our brain might store them for later consideration to improve decision-making. To test this hypothesis, we examined whether novel vocabulary consisting of simultaneously played pseudowords and translation words are encoded/stored during sleep, and which neural-electrical events facilitate encoding/storage. An algorithm for brain-state-dependent stimulation selectively targeted word pairs to slow-wave peaks or troughs. Retrieval tests were given 12 and 36 hr later. These tests required decisions regarding the semantic category of previously sleep-played pseudowords. The sleep-played vocabulary influenced awake decision-making 36 hr later, if targeted to troughs. The words' linguistic processing raised neural complexity. The words' semantic-associative encoding was supported by increased theta power during the ensuing peak. Fast-spindle power ramped up during a second peak likely aiding consolidation. Hence, new vocabulary played during slow-wave sleep was stored and influenced decision-making days later.

Recurring memory reactivation: The offline component of learning

One can be aware of the effort needed to memorize a new fact or to recall the name of a new acquaintance. Because of experiences like this, learning can seem to have only two components, encoding information and, after some delay, retrieving information. To the contrary, learning entails additional, intervening steps that sometimes are hidden from the learner. For firmly acquiring fact and event knowledge in particular, learners are generally not cognizant of the necessity of offline consolidation. The memories that persist to be available reliably at a later time, according to the present conceptualization, are the ones we repeatedly rehearse and integrate with other knowledge, whether we do this intentionally or unknowingly, awake or asleep. This article examines the notion that learning is not a function of waking brain activity alone. What happens in the brain while we sleep also impacts memory storage, and consequently is a critical component of learning. The idea that memories can change over time and become enduring has long been present in memory research and is foundational for the concept of memory consolidation. Nevertheless, the notion that memory consolidation happens during sleep faced much resistance before eventually being firmly established. Research is still needed to elucidate the operation and repercussions of repeated reactivation during sleep. Comprehensively understanding how offline memory reactivation contributes to learning is vital for both theoretical and practical considerations.

An update on recent advances in targeted memory reactivation during sleep

Targeted Memory Reactivation (TMR) is a noninvasive tool to manipulate memory consolidation during sleep. TMR builds on the brain's natural processes of memory reactivation during sleep and aims to facilitate or bias these processes in a certain direction. The basis of this technique is the association of learning content with sensory cues, such as odors or sounds, that are presented during subsequent sleep to promote memory reactivation. Research on TMR has drastically increased over the last decade with rapid developments. The aim of the present review is to highlight the most recent advances of this research. We focus on effects of TMR on the strengthening of memories in the declarative, procedural and emotional memory domain as well as on ways in which TMR can be used to promote forgetting. We then discuss advanced technical approaches to determine the optimal timing of TMR within the ongoing oscillatory activity of the sleeping brain as well as the specificity of TMR for certain memory contents. We further highlight the specific effects of TMR during REM sleep and in influencing dream content. Finally, we discuss recent evidence for potential applications of TMR for mental health, educational purposes and in the home setting. In conclusion, the last years of research have provided substantial advances in TMR that can guide future endeavors in research and application.

J, Tandoc M, Antony J, Schapiro A. Memory reactivation during sleep does not act holistically on object memory

Memory reactivation during sleep is thought to facilitate memory consolidation. Most sleep reactivation research has examined how reactivation of specific facts, objects, and associations benefits their overall retention. However, our memories are not unitary, and not all features of a memory persist in tandem over time. Instead, our memories are transformed, with some features strengthened and others weakened. Does sleep reactivation drive memory transformation? We leveraged the Targeted Memory Reactivation technique in an object category learning paradigm to examine this question. Participants (20 female, 14 male) learned three categories of novel objects, where each object had unique, distinguishing features as well as features shared with other members of its category. We used a real-time EEG protocol to cue the reactivation of these objects during sleep at moments optimized to generate reactivation events. We found that reactivation improved memory for distinguishing features while worsening memory for shared features, suggesting a differentiation process. The results indicate that sleep reactivation does not act holistically on object memories, instead supporting a transformation process where some features are enhanced over others.

Memory reactivation in slow wave sleep enhances relational learning in humans

Sleep boosts the integration of memories, and can thus facilitate relational learning. This benefit may be due to memory reactivation during non-REM sleep. We set out to test this by explicitly cueing reactivation using a technique called targeted memory reactivation (TMR), in which sounds are paired with learned material in wake and then softly played during subsequent sleep, triggering reactivation of the associated memories. We specifically tested whether TMR in slow wave sleep leads to enhancements in inferential thinking in a transitive inference task. Because the Up-phase of the slow oscillation is more responsive to cues than the Down-phase, we also asked whether Up-phase stimulation is more beneficial for such integration. Our data show that TMR during the Up-Phase boosts the ability to make inferences, but only for the most distant inferential leaps. Up-phase stimulation was also associated with detectable memory reinstatement, whereas Down-phase stimulation led to below-chance performance the next morning. Detection of memory reinstatement after Up-state stimulation was negatively correlated with performance on the most difficult inferences the next morning. These findings demonstrate that cueing memory reactivation at specific time points in sleep can benefit difficult relational learning problems.

Auditory stimulation during REM sleep modulates REM electrophysiology and cognitive performance

REM sleep is critical for memory, emotion, and cognition. Manipulating brain activity during REM could improve our understanding of its function and benefits. Earlier studies have suggested that auditory stimulation in REM might modulate REM time and reduce rapid eye movement density. Building on this, we studied the cognitive effects and electroencephalographic responses related to such stimulation. We used acoustic stimulation locked to eye movements during REM and compared two overnight conditions (stimulation and no-stimulation). We evaluated the impact of this stimulation on REM sleep duration and electrophysiology, as well as two REM-sensitive memory tasks: visual discrimination and mirror tracing. Our results show that this auditory stimulation in REM decreases the rapid eye movements that characterize REM sleep and improves performance on the visual task but is detrimental to the mirror tracing task. We also observed increased beta-band activity and decreased theta-band activity following stimulation. Interestingly, these spectral changes were associated with changes in behavioural performance. These results show that acoustic stimulation can modulate REM sleep and suggest that different memory processes underpin its divergent impacts on cognitive performance.

A classification-based generative approach to selective targeting of global slow oscillations during sleep

Background

Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability.

Objective/Hypothesis

This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile.

Methods

We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance.

Results

Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization.

Conclusion

Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.

Effects of Targeted Memory Reactivation on Cortical Networks

Sleep is a complex physiological process with an important role in memory consolidation characterised by a series of spatiotemporal changes in brain activity and connectivity. Here, we investigate how task-related responses differ between pre-sleep wake, sleep, and post-sleep wake. To this end, we trained participants on a serial reaction time task using both right and left hands using Targeted Memory Reactivation (TMR), in which auditory cues are associated with learned material and then re-presented in subsequent wake or sleep periods in order to elicit memory reactivation. The neural responses just after each cue showed increased theta band connectivity between frontal and other cortical regions, as well as between hemispheres, in slow wave sleep compared to pre- or post-sleep wake. This pattern was consistent across the cues associated with both right- and left-handed movements. We also searched for hand-specific connectivity and found that this could be identified in within-hemisphere connectivity after TMR cues during sleep and post-sleep sessions. The fact that we could identify which hand had been cued during sleep suggests that these connectivity measures could potentially be used to determine how successfully memory is reactivated by our manipulation. Collectively, these findings indicate that TMR modulates the brain cortical networks showing clear differences between wake and sleep connectivity patterns.

First-night effect reduces the beneficial effects of sleep on visual plasticity and modifies the underlying neurochemical processes

Individuals experience difficulty falling asleep in a new environment, termed the first night effect (FNE). However, the impact of the FNE on sleep-induced brain plasticity remains unclear. Here, using a within-subject design, we found that the FNE significantly reduces visual plasticity during sleep in young adults. Sleep-onset latency (SOL), an indicator of the FNE, was significantly longer during the first sleep session than the second session, confirming the FNE. We assessed performance gains in visual perceptual learning after sleep and increases in the excitatory-to-inhibitory neurotransmitter (E/I) ratio in early visual areas during sleep using magnetic resonance spectroscopy and polysomnography. These parameters were significantly smaller in sleep with the FNE than in sleep without the FNE; however, these parameters were not correlated with SOL. These results suggest that while the neural mechanisms of the FNE and brain plasticity are independent, sleep disturbances temporarily block the neurochemical process fundamental for brain plasticity.

Targeted memory reactivation in human REM sleep elicits detectable reactivation

It is now well established that memories can reactivate during non-rapid eye movement (non-REM) sleep, but the question of whether equivalent reactivation can be detected in rapid eye movement (REM) sleep is hotly debated. To examine this, we used a technique called targeted memory reactivation (TMR) in which sounds are paired with learned material in wake, and then re-presented in subsequent sleep, in this case REM, to trigger reactivation. We then used machine learning classifiers to identify reactivation of task-related motor imagery from wake in REM sleep. Interestingly, the strength of measured reactivation positively predicted overnight performance improvement. These findings provide the first evidence for memory reactivation in human REM sleep after TMR that is directly related to brain activity during wakeful task performance.