Cued reactivation during slow-wave sleep induces brain connectivity changes related to memory stabilization

Forgetting unwanted memories in sleep

Memories are sometimes best forgotten, but how do our brains weaken unwanted details of the past? We propose a theoretical framework in which memory reactivation during sleep supports adaptive forgetting. This mnemonic rebalancing underpins the affective benefits of sleep by ensuring that our memories remain aligned with our emotional goals.

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.

Item-specific neural representations during human sleep support long-term memory

Understanding how individual memories are reactivated during sleep is essential in theorizing memory consolidation. Here, we employed the targeted memory reactivation (TMR) paradigm to unobtrusively replaying auditory memory cues during human participants' slow-wave sleep (SWS). Using representational similarity analysis (RSA) on cue-elicited electroencephalogram (EEG), we found temporally segregated and functionally distinct item-specific neural representations: the early post-cue EEG activity (within 0 to 2,000 ms) contained comparable item-specific representations for memory cues and control cues, signifying effective processing of auditory cues. Critically, the later EEG activity (2,500 to 2,960 ms) showed greater item-specific representations for post-sleep remembered items than for forgotten and control cues, indicating memory reprocessing. Moreover, these later item-specific neural representations were supported by concurrently increased spindles, particularly for items that had not been tested prior to sleep. These findings elucidated how external memory cues triggered item-specific neural representations during SWS and how such representations were linked to successful long-term memory. These results will benefit future research aiming to perturb specific memory episodes during sleep.

Locating causal hubs of memory consolidation in spontaneous brain network in male mice

Memory consolidation after learning involves spontaneous, brain-wide network reorganization during rest and sleep, but how this is achieved is still poorly understood. Current theory suggests that the hippocampus is pivotal for this reshaping of connectivity. Using fMRI in male mice, we identify that a different set of spontaneous networks and their hubs are instrumental in consolidating memory during post-learning rest. We found that two types of spatial memory training invoke distinct functional connections, but that a network of the sensory cortex and subcortical areas is common for both tasks. Furthermore, learning increased brain-wide network integration, with the prefrontal, striatal and thalamic areas being influential for this network-level reconfiguration. Chemogenetic suppression of each hub identified after learning resulted in retrograde amnesia, confirming the behavioral significance. These results demonstrate the causal and functional roles of resting-state network hubs in memory consolidation and suggest that a distributed network beyond the hippocampus subserves this process.

3T vs. 7T fMRI: capturing early human memory consolidation after motor task utilizing the observed higher functional specificity of 7T

Objective

Functional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases. Yet, mapping the blood oxygen level dependent (BOLD) response to distinct neuronal processes continues to be challenging. Here, we investigated the characteristics of 7 T-fMRI compared to 3 T-fMRI in the human brain beyond the effect of increased SNR and verified the benefits of 7 T-fMRI in the detection of tiny, highly specific modulations of functional connectivity in the resting state following a motor task.

Methods

18 healthy volunteers underwent two resting state and a stimulus driven measurement using a finger tapping motor task at 3 and 7 T, respectively. The SNR for each field strength was adjusted by targeted voxel size variation to minimize the effect of SNR on the field strength specific outcome. Spatial and temporal characteristics of resting state ICA, network graphs, and motor task related activated areas were compared. Finally, a graph theoretical approach was used to detect resting state modulation subsequent to a simple motor task.

Results

Spatial extensions of resting state ICA and motor task related activated areas were consistent between field strengths, but temporal characteristics varied, indicating that 7 T achieved a higher functional specificity of the BOLD response than 3 T-fMRI. Following the motor task, only 7 T-fMRI enabled the detection of highly specific connectivity modulations representing an "offline replay" of previous motor activation. Modulated connections of the motor cortex were directly linked to brain regions associated with memory consolidation.

Conclusion

These findings reveal how memory processing is initiated even after simple motor tasks, and that it begins earlier than previously shown. Thus, the superior capability of 7 T-fMRI to detect subtle functional dynamics promises to improve diagnostics and therapeutic assessment of neurological diseases.

Developing customized NIRS-EEG for infant sleep research: methodological considerations

Significance

Studies using simultaneous functional near-infrared spectroscopy (fNIRS)-electroencephalography (EEG) during natural sleep in infancy are rare. Developments for combined fNIRS-EEG for sleep research that ensure optimal comfort as well as good coupling and data quality are needed.

Aim

We describe the steps toward developing a comfortable, wearable NIRS-EEG headgear adapted specifically for sleeping infants ages 5 to 9 months and present the experimental procedures and data quality to conduct infant sleep research using combined fNIRS-EEG.

Approach

N = 49 5- to 9-month-old infants participated. In phase 1, N = 26 (10 = slept) participated using the non-wearable version of the NIRS-EEG headgear with 13-channel-wearable EEG and 39-channel fiber-based NIRS. In phase 2, N = 23 infants (21 = slept) participated with the wireless version of the headgear with 20-channel-wearable EEG and 47-channel wearable NIRS. We used QT-NIRS to assess the NIRS data quality based on the good time window percentage, included channels, nap duration, and valid EEG percentage.

Results

The infant nap rate during phase 1 was ∼ 40 % (45% valid EEG data) and increased to 90% during phase 2 (100% valid EEG data). Infants slept significantly longer with the wearable system than the non-wearable system. However, there were more included good channels based on QT-NIRS in study phase 1 (61%) than phase 2 (50%), though this difference was not statistically significant.

Conclusions

We demonstrated the usability of an integrated NIRS-EEG headgear during natural infant sleep with both non-wearable and wearable NIRS systems. The wearable NIRS-EEG headgear represents a good compromise between data quality, opportunities of applications (home visits and toddlers), and experiment success (infants' comfort, longer sleep duration, and opportunities for caregiver-child interaction).

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.

Electrophysiological markers of memory consolidation in the human brain when memories are reactivated during sleep

Sleep contributes to memory consolidation, we presume, because memories are replayed during sleep. Understanding this aspect of consolidation can help with optimizing normal learning in many contexts and with treating memory disorders and other diseases. Here, we systematically manipulated sleep-based processing using targeted memory reactivation; brief sounds coupled with presleep learning were quietly presented again during sleep, producing 1) recall improvements for specific spatial memories associated with those sounds and 2) physiological responses in the sleep electroencephalogram. Neural activity in the hippocampus and adjacent medial temporal cortex was thus found in association with memory consolidation during sleep. These findings advance understanding of consolidation by linking beneficial memory changes during sleep to both memory reactivation and specific patterns of brain activity.

Human accomplishments depend on learning, and effective learning depends on consolidation. Consolidation is the process whereby new memories are gradually stored in an enduring way in the brain so that they can be available when needed. For factual or event knowledge, consolidation is thought to progress during sleep as well as during waking states and to be mediated by interactions between hippocampal and neocortical networks. However, consolidation is difficult to observe directly but rather is inferred through behavioral observations. Here, we investigated overnight memory change by measuring electrical activity in and near the hippocampus. Electroencephalographic (EEG) recordings were made in five patients from electrodes implanted to determine whether a surgical treatment could relieve their seizure disorders. One night, while each patient slept in a hospital monitoring room, we recorded electrophysiological responses to 10 to 20 specific sounds that were presented very quietly, to avoid arousal. Half of the sounds had been associated with objects and their precise spatial locations that patients learned before sleep. After sleep, we found systematic improvements in spatial recall, replicating prior results. We assume that when the sounds were presented during sleep, they reactivated and strengthened corresponding spatial memories. Notably, the sounds also elicited oscillatory intracranial EEG activity, including increases in theta, sigma, and gamma EEG bands. Gamma responses, in particular, were consistently associated with the degree of improvement in spatial memory exhibited after sleep. We thus conclude that this electrophysiological activity in the hippocampus and adjacent medial temporal cortex reflects sleep-based enhancement of memory storage.

Associations between cortical activation and network interaction during sleep

Cortical activation and network interaction, two characterizations of the cortical states, are separately studied in most previous studies. To further clarify the underlying mechanism, the association between these two indicators during sleep was investigated in this study. Twenty healthy individuals were enrolled and all of them underwent overnight polysomnography (PSG) recording. The relative spectral powers and the phase transfer entropy (PTE) of various frequency components were extracted from 6 electroencephalographic (EEG) channels, to assess the cortical activation and network interaction, respectively. Pearson correlation coefficient was employed to estimate their associations. The results suggested that there was a negative correlation between spectral power and phase transfer entropy in δ and α frequency bands during sleep. As the sleep deepened, an increased negative correlation in the δ frequency band was noted, but the negative correlation became less extreme in the α frequency band. The extremum of the correlation coefficient was noted in δ of N3, and α of Wake. Overall, this study provides a connection between these two cortical activity assessments, especially reveals the variable characteristics of different frequency components, which is conducive to better understand sleep state.

No consolidation without representation: Correspondence between neural and psychological representations in recent and remote memory

Memory systems consolidation is often conceived as the linear, time-dependent, neurobiological shift of memory from hippocampal-cortical to cortico-cortical dependency. We argue that contrary to this unidirectional view of memory reorganization, information about events may be retained in multiple forms (e.g., event-specific sensory-near episodic memory, event-specific gist information, event-general schematic information, or abstract semantic memory). These representations can all form at the time of the event and may continue to coexist for long durations. Their relative strength, composition, and dominance of expression change with time and experience, with task demands, and through their dynamic interaction with one another. These different psychological mnemonic representations depend on distinct functional and structural neurobiological substrates such that there is a neural-psychological representation correspondence (NPRC) among them. We discuss how the dynamics of psychological memory representations are reflected in multiple levels of neurobiological markers and their interactions. By this view, there are only variations of synaptic consolidation and memory dynamics without assuming a distinct systems consolidation process.

Post-learning micro- and macro-structural neuroplasticity changes with time and sleep

Neuroplasticity refers to the fact that our brain can partially modify both structure and function to adequately respond to novel environmental stimulations. Neuroplasticity mechanisms are not only operating during the acquisition of novel information (i.e., online) but also during the offline periods that take place after the end of the actual learning episode. Structural brain changes as a consequence of learning have been consistently demonstrated on the long term using non-invasive neuroimaging methods, but short-term changes remained more elusive. Fortunately, the swift development of advanced MR methods over the last decade now allows tracking fine-grained cerebral changes on short timescales beyond gross volumetric modifications stretching over several days or weeks. Besides a mere effect of time, post-learning sleep mechanisms have been shown to play an important role in memory consolidation and promote long-lasting changes in neural networks. Sleep was shown to contribute to structural modifications over weeks of prolonged training, but studies evidencing more rapid post-training sleep structural effects linked to memory consolidation are still scarce in human. On the other hand, animal studies convincingly show how sleep might modulate synaptic microstructure. We aim here at reviewing the literature establishing a link between different types of training/learning and the resulting structural changes, with an emphasis on the role of post-training sleep and time in tuning these modifications. Open questions are raised such as the role of post-learning sleep in macrostructural changes, the links between different MR structural measurement-related modifications and the underlying microstructural brain processes, and bidirectional influences between structural and functional brain changes.

Local Sleep and Alzheimer's Disease Pathophysiology

Even prior to the onset of the prodromal stages of Alzheimer's disease (AD), a constellation of sleep disturbances are apparent. A series of epidemiological studies indicate that multiple forms of these sleep disturbances are associated with increased risk for developing mild cognitive impairment (MCI) and AD, even triggering disease onset at an earlier age. Through the combination of causal manipulation studies in humans and rodents, as well as targeted examination of sleep disturbance with respect to AD biomarkers, mechanisms linking sleep disturbance to AD are beginning to emerge. In this review, we explore recent evidence linking local deficits in brain oscillatory function during sleep with local AD pathological burden and circuit-level dysfunction and degeneration. In short, three deficits in the local expression of sleep oscillations have been identified in relation to AD pathophysiology: (1) frequency-specific frontal deficits in slow wave expression during non-rapid eye movement (NREM) sleep, (2) deficits in parietal sleep spindle expression, and (3) deficits in the quality of electroencephalographic (EEG) desynchrony characteristic of REM sleep. These deficits are noteworthy since they differ from that seen in normal aging, indicating the potential presence of an abnormal aging process. How each of these are associated with β-amyloid (Aβ) and tau pathology, as well as neurodegeneration of circuits sensitive to AD pathophysiology, are examined in the present review, with a focus on the role of dysfunction within fronto-hippocampal and subcortical sleep-wake circuits. It is hypothesized that each of these local sleep deficits arise from distinct network-specific dysfunctions driven by regionally-specific accumulation of AD pathologies, as well as their associated neurodegeneration. Overall, the evolution of these local sleep deficits offer unique windows into the circuit-specific progression of distinct AD pathophysiological processes prior to AD onset, as well as their impact on brain function. This includes the potential erosion of sleep-dependent memory mechanisms, which may contribute to memory decline in AD. This review closes with a discussion of the remaining critical knowledge gaps and implications of this work for future mechanistic studies and studies implementing sleep-based treatment interventions.

Memory and Sleep: How Sleep Cognition Can Change the Waking Mind for the Better

The memories that we retain can serve many functions. They guide our future actions, form a scaffold for constructing the self, and continue to shape both the self and the way we perceive the world. Although most memories we acquire each day are forgotten, those integrated within the structure of multiple prior memories tend to endure. A rapidly growing body of research is steadily elucidating how the consolidation of memories depends on their reactivation during sleep. Processing memories during sleep not only helps counteract their weakening but also supports problem solving, creativity, and emotional regulation. Yet, sleep-based processing might become maladaptive, such as when worries are excessively revisited. Advances in research on memory and sleep can thus shed light on how this processing influences our waking life, which can further inspire the development of novel strategies for decreasing detrimental rumination-like activity during sleep and for promoting beneficial sleep cognition.

Autonomic Activity during a Daytime Nap Facilitates Working Memory Improvement

Recent investigations have implicated the parasympathetic branch of the autonomic nervous system in higher-order executive functions. These actions are purported to occur through autonomic nervous system's modulation of the pFC, with parasympathetic activity during wake associated with working memory (WM) ability. Compared with wake, sleep is a period with substantially greater parasympathetic tone. Recent work has reported that sleep may also contribute to improvement in WM. Here, we examined the role of cardiac parasympathetic activity during sleep on WM improvement in healthy young adults. Participants were tested in an operation span task in the morning and evening, and during the intertest period, participants experienced either a nap or wake. We measured high-frequency heart rate variability as an index of cardiac, parasympathetic activity during both wake and sleep. Participants showed the expected boost in parasympathetic activity during nap, compared with wake. Furthermore, parasympathetic activity during sleep, but not wake, was significantly correlated with WM improvement. Together, these results indicate that the natural boost in parasympathetic activity during sleep may benefit gains in prefrontal executive function in young adults. We present a conceptual model illustrating the interaction between sleep, autonomic activity, and prefrontal brain function and highlight open research questions that will facilitate understanding of the factors that contribute to executive abilities in young adults as well as in cognitive aging.

No effect of targeted memory reactivation during sleep on retention of vocabulary in adolescents

Re-exposure of newly acquired vocabulary during sleep improves later memory recall in healthy adults. The success of targeted memory reactivation (TMR) during sleep presumably depends on the presence of slow oscillations (i.e., EEG activity at a frequency of about 0.75 Hz). As slow oscillating activity is at its maximum during adolescence, we hypothesized that TMR is even more beneficial at this developmental stage. In the present study, adolescents aged 11 to 13 learnt Dutch vocabulary in the evening and were tested on recall performance the next morning. Half of the words were presented via loudspeakers during post-learning periods of NREM (Non Rapid Eye Movement) sleep in order to stimulate memory reactivation. Unexpectedly, TMR during sleep did not improve memory on the behavioral level in adolescents. On the oscillatory level, successful reactivation during sleep resulted in the characteristic increase in theta power over frontal brain regions, as reported in adults. However, we observed no increase in spindle power during successful reactivation. Possible factors that may explain the lacking effect of TMR in adolescents in this study such as differences in learning abilities and pre-sleep performance levels are discussed.

Promoting memory consolidation during sleep: A meta-analysis of targeted memory reactivation

Targeted memory reactivation (TMR) is a methodology employed to manipulate memory processing during sleep. TMR studies have great potential to advance understanding of sleep-based memory consolidation and corresponding neural mechanisms. Research making use of TMR has developed rapidly, with over 70 articles published in the last decade, yet no quantitative analysis exists to evaluate the overall effects. Here we present the first meta-analysis of sleep TMR, compiled from 91 experiments with 212 effect sizes (N = 2,004). Based on multilevel modeling, overall sleep TMR was highly effective (Hedges' g = 0.29, 95% CI [0.21, 0.38]), with a significant effect for two stages of non-rapid-eye-movement (NREM) sleep (Stage NREM 2: Hedges' g = 0.32, 95% CI [0.04, 0.60]; and slow-wave sleep: Hedges' g = 0.27, 95% CI [0.20, 0.35]). In contrast, TMR was not effective during REM sleep nor during wakefulness in the present analyses. Several analysis strategies were used to address the potential relevance of publication bias. Additional analyses showed that TMR improved memory across multiple domains, including declarative memory and skill acquisition. Given that TMR can reinforce many types of memory, it could be useful for various educational and clinical applications. Overall, the present meta-analysis provides substantial support for the notion that TMR can influence memory storage during NREM sleep, and that this method can be useful for understanding neurocognitive mechanisms of memory consolidation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Odor-evoked category reactivation in human ventromedial prefrontal cortex during sleep promotes memory consolidation

Slow-wave sleep is an optimal opportunity for memory consolidation: when encoding occurs in the presence of a sensory cue, delivery of that cue during sleep enhances retrieval of associated memories. Recent studies suggest that cues might promote consolidation by inducing neural reinstatement of cue-associated content during sleep, but direct evidence for such mechanisms is scant, and the relevant brain areas supporting these processes are poorly understood. Here, we address these gaps by combining a novel olfactory cueing paradigm with an object-location memory task and simultaneous EEG-fMRI recording in human subjects. Using pattern analysis of fMRI ensemble activity, we find that presentation of odor cues during sleep promotes reactivation of category-level information in ventromedial prefrontal cortex that significantly correlates with post-sleep memory performance. In identifying the potential mechanisms by which odor cues selectively modulate memory in the sleeping brain, these findings bring unique insights into elucidating how and what we remember.