The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

Sleep oscillations related to memory consolidation during aromatases inhibitors for breast cancer

Aromatase inhibitors (AIs) are associated with sleep difficulties in breast cancer (BC) patients. Sleep is known to favor memory consolidation through the occurrence of specific oscillations, i.e., slow waves (SW) and sleep spindles, allowing a dialogue between prefrontal cortex and the hippocampus. Interestingly, neuroimaging studies in BC patients have consistently shown structural and functional modifications in these two brain regions. With the aim to evaluate sleep oscillations related to memory consolidation during AIs, we collected polysomnography data in BC patients treated (AI+, n = 17) or not (AI-, n = 17) with AIs compared to healthy controls (HC, n = 21). None of the patients had received chemotherapy and radiotherapy was finished since at least 6 months, that limit the confounding effects of other treatments than AIs. Fast and slow spindles were detected during sleep stage 2 at centro-parietal and frontal electrodes respectively. SW were detected at frontal electrodes during stage 3. Here, we show lower frontal SW densities in AI + patients compared to HC. These results concord with previous reports about frontal cortical alterations in cancer following AIs administration. Moreover, AI + patients tended to have lower spindle density at C4 electrode. Regression analyses showed that, in both patient groups, spindle density at C4 electrode explained a large variance of memory performances. Slow spindle characteristics did not differ between groups and sleep oscillations characteristics of AI- patients did not differ significantly from those of both AI + patients and HC. Overall, our results add to the compelling evidence of the systemic effects of AIs previously reported in animals, with deleterious effects on cortical activity during sleep and associated memory consolidation in the current study. There is thus a need to further investigate sleep modifications during AIs administration. Longitudinal studies are needed to confirm these findings and investigation in other cancers on this topic should be conducted.

A personalized semi-automatic sleep spindle detection (PSASD) framework

BACKGROUND

Sleep spindles are distinct electroencephalogram (EEG) patterns of brain activity that have been posited to play a critical role in development, learning, and neurological disorders. Manual scoring for sleep spindles is labor-intensive and tedious but could supplement automated algorithms to resolve challenges posed with either approaches alone.

NEW METHODS

A Personalized Semi-Automatic Sleep Spindle Detection (PSASD) framework was developed to combine the strength of automated detection algorithms and visual expertise of human scorers. The underlying model in the PSASD framework assumes a generative model for EEG sleep spindles as oscillatory components, optimized to EEG amplitude, with remaining signals distributed into transient and low-frequency components.

RESULTS

A single graphical user interface (GUI) allows both manual scoring of sleep spindles (model training data) and verification of automatically detected spindles. A grid search approach allows optimization of parameters to balance tradeoffs between precision and recall measures.

COMPARISON WITH EXISTING METHODS

PSASD outperformed DETOKS in F1-score by 19% and 4% on the DREAMS and P-DROWS-E datasets, respectively. It also outperformed YASA in F1-score by 25% in the P-DROWS-E dataset. Further benchmarking analysis showed that PSASD outperformed four additional widely used sleep spindle detectors in F1-score in the P-DROWS-E dataset. Titration analysis revealed that four 30-second epochs are sufficient to fine-tune the model parameters of PSASD. Associations of frequency, duration, and amplitude of detected sleep spindles matched those previously reported with automated approaches.

CONCLUSIONS

Overall, PSASD improves detection of sleep spindles in EEG data acquired from both younger healthy and older adult patient populations.

Thalamic contributions to the state and contents of consciousness

Consciousness can be conceptualized as varying along at least two dimensions: the global state of consciousness and the content of conscious experience. Here, we highlight the cellular and systems-level contributions of the thalamus to conscious state and then argue for thalamic contributions to conscious content, including the integrated, segregated, and continuous nature of our experience. We underscore vital, yet distinct roles for core- and matrix-type thalamic neurons. Through reciprocal interactions with deep-layer cortical neurons, matrix neurons support wakefulness and determine perceptual thresholds, whereas the cortical interactions of core neurons maintain content and enable perceptual constancy. We further propose that conscious integration, segregation, and continuity depend on the convergent nature of corticothalamic projections enabling dimensionality reduction, a thalamic reticular nucleus-mediated divisive normalization-like process, and sustained coherent activity in thalamocortical loops, respectively. Overall, we conclude that the thalamus plays a central topological role in brain structures controlling conscious experience.

Sleep pressure modulates single-neuron synapse number in zebrafish

Sleep is a nearly universal behaviour with unclear functions1. The synaptic homeostasis hypothesis proposes that sleep is required to renormalize the increases in synaptic number and strength that occur during wakefulness2. Some studies examining either large neuronal populations3 or small patches of dendrites4 have found evidence consistent with the synaptic homeostasis hypothesis, but whether sleep merely functions as a permissive state or actively promotes synaptic downregulation at the scale of whole neurons is unclear. Here, by repeatedly imaging all excitatory synapses on single neurons across sleep-wake states of zebrafish larvae, we show that synapses are gained during periods of wake (either spontaneous or forced) and lost during sleep in a neuron-subtype-dependent manner. However, synapse loss is greatest during sleep associated with high sleep pressure after prolonged wakefulness, and lowest in the latter half of an undisrupted night. Conversely, sleep induced pharmacologically during periods of low sleep pressure is insufficient to trigger synapse loss unless adenosine levels are boosted while noradrenergic tone is inhibited. We conclude that sleep-dependent synapse loss is regulated by sleep pressure at the level of the single neuron and that not all sleep periods are equally capable of fulfilling the functions of synaptic homeostasis.

Assessing sleep architecture and cognition in older adults with depressive symptoms attending a memory clinic

BACKGROUND

While depression is intrinsically and bidirectionally linked with both sleep disturbance and cognition, the inter-relationships between sleep, cognition, and brain integrity in older people with depression, especially those with late-onset depression are undefined.

METHODS

One hundred and seventy-two older adults (mean age 64.3 ± 6.9 years, Depression: n = 66, Control: n = 106) attending a memory clinic underwent a neuropsychological battery of declarative memory, executive function tasks, cerebral magnetic resonance imaging and overnight polysomnography with quantitative electroencephalography.

RESULTS

The time spent in slow-wave sleep (SWS) and rapid eye movement (REM) sleep, slow-wave activity, sleep spindles, hippocampal volume and prefrontal cortex thickness did not differ between depression and control and depression onset groups. However, sleep onset latency (p = 0.005) and REM onset latency (p = 0.02) were later in the Depression group compared to controls. Less SWS was associated with poorer memory (r = 0.31, p = 0.023) in the depression group, and less SWS was related to better memory in the control group (r = -0.20, p = 0.043; Fishers r-to-z = -3.19).

LIMITATIONS

Longitudinal studies are needed to determine if changes in sleep in those with depressive symptoms predict cognitive decline and illness trajectory.

CONCLUSION

Older participants with depressive symptoms had delayed sleep initiation, suggestive of delayed sleep phase. The association between SWS and memory suggests SWS may be a useful target for cognitive intervention in older adults with depression symptoms. Reduced hippocampal volumes did not mediate this relationship, indicating a broader distributed neural network may underpin these associations.

Orexin Receptor Antagonism: Normalizing Sleep Architecture in Old Age and Disease

Sleep is essential for human well-being, yet the quality and quantity of sleep reduce as age advances. Older persons (>65 years old) are more at risk of disorders accompanied and/or exacerbated by poor sleep. Furthermore, evidence supports a bidirectional relationship between disrupted sleep and Alzheimer's disease (AD) or related dementias. Orexin/hypocretin neuropeptides stabilize wakefulness, and several orexin receptor antagonists (ORAs) are approved for the treatment of insomnia in adults. Dysregulation of the orexin system occurs in aging and AD, positioning ORAs as advantageous for these populations. Indeed, several clinical studies indicate that ORAs are efficacious hypnotics in older persons and dementia patients and, as in adults, are generally well tolerated. ORAs are likely to be more effective when administered early in sleep/wake dysregulation to reestablish good sleep/wake-related behaviors and reduce the accumulation of dementia-associated proteinopathic substrates. Improving sleep in aging and dementia represents a tremendous opportunity to benefit patients, caregivers, and health systems.

Cortical miR-709 links glutamatergic signaling to NREM sleep EEG slow waves in an activity-dependent manner

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression that have been implicated in a plethora of neuronal processes. Nevertheless, their role in regulating brain activity in the context of sleep has so far received little attention. To test their involvement, we deleted mature miRNAs in post-mitotic neurons at two developmental ages, i.e., in early adulthood using conditional Dicer knockout (cKO) mice and in adult mice using an inducible conditional Dicer cKO (icKO) line. In both models, electroencephalographic (EEG) activity was affected and the response to sleep deprivation (SD) altered; while the rapid-eye-movement sleep (REMS) rebound was compromised in both, the increase in EEG delta (1 to 4 Hz) power during non-REMS (NREMS) was smaller in cKO mice and larger in icKO mice compared to controls. We subsequently investigated the effects of SD on the forebrain miRNA transcriptome and found that the expression of 48 miRNAs was affected, and in particular that of the activity-dependent miR-709. In vivo inhibition of miR-709 in the brain increased EEG power during NREMS in the slow-delta (0.75 to 1.75 Hz) range, particularly after periods of prolonged wakefulness. Transcriptome analysis of primary cortical neurons in vitro revealed that miR-709 regulates genes involved in glutamatergic neurotransmission. A subset of these genes was also affected in the cortices of sleep-deprived, miR-709-inhibited mice. Our data implicate miRNAs in the regulation of EEG activity and indicate that miR-709 links neuronal activity during wakefulness to brain synchrony during sleep through the regulation of glutamatergic signaling.

Epilepsy and sleep characteristics are associated with diminished 24-h memory retention in older adults with epilepsy

OBJECTIVE

Individuals with epilepsy often have memory difficulties, and older adults with epilepsy are especially vulnerable, due to the additive effect of aging. The goal of this study was to assess factors that are associated with 24-h memory retention in older adults with epilepsy.

METHODS

Fifty-five adults with epilepsy, all aged >50 years, performed a declarative memory task involving the recall of the positions of 15 card pairs on a computer screen prior to a 24-h ambulatory electroencephalogram (EEG). We assessed the percentage of encoded card pairs that were correctly recalled after 24 h (24-h retention rate). EEGs were evaluated for the presence and frequency of scalp interictal epileptiform activity (IEA) and scored for total sleep. Global slow wave activity (SWA) power during non-rapid eye movement sleep was also calculated.

RESULTS

Forty-four participants successfully completed the memory task. Two were subsequently excluded due to seizures on EEG. The final cohort (n = 42) had a mean age of 64.3 ± 7.5 years, was 52% female, and had an average 24-h retention rate of 70.9% ± 30.2%. Predictors of 24-h retention based on multivariate regression analysis when controlling for age, sex, and education included number of antiseizure medications (β = -.20, p = .013), IEA frequency (β = -.08, p = .0094), and SWA power (β = +.002, p = .02).

SIGNIFICANCE

In older adults with epilepsy, greater frequency of IEA, reduced SWA power, and higher burden of antiseizure medications correlated with worse 24-h memory retention. These factors represent potential treatment targets to improve memory in older adults with epilepsy.

Regulation of dendritic spines in the amygdala following sleep deprivation

The amygdala is a hub of emotional circuits involved in the regulation of cognitive and emotional behaviors and its critically involved in emotional reactivity, stress regulation, and fear memory. Growing evidence suggests that the amygdala plays a key role in the consolidation of emotional memories during sleep. Neuroimaging studies demonstrated that the amygdala is selectively and highly activated during rapid eye movement sleep (REM) and sleep deprivation induces emotional instability and dysregulation of the emotional learning process. Regulation of dendritic spines during sleep represents a morphological correlate of memory consolidation. Several studies indicate that dendritic spines are remodeled during sleep, with evidence for broad synaptic downscaling and selective synaptic upscaling in several cortical areas and the hippocampus. Currently, there is a lack of information regarding the regulation of dendritic spines in the amygdala during sleep. In the present work, we investigated the effect of 5 h of sleep deprivation on dendritic spines in the mouse amygdala. Our data demonstrate that sleep deprivation results in differential dendritic spine changes depending on both the amygdala subregions and the morphological subtypes of dendritic spines. We observed decreased density of mushroom spines in the basolateral amygdala of sleep deprived mice, together with increased neck length and decreased surface area and volume. In contrast, we observed greater densities of stubby spines in sleep deprived mice in the central amygdala, indicating that downscaling selectively occurs in this spine type. Greater neck diameters for thin spines in the lateral and basolateral nuclei of sleep deprived mice, and decreases in surface area and volume for mushroom spines in the basolateral amygdala compared to increases in the cental amygdala provide further support for spine type-selective synaptic downscaling in these areas during sleep. Our findings suggest that sleep promotes synaptic upscaling of mushroom spines in the basolateral amygdala, and downscaling of selective spine types in the lateral and central amygdala. In addition, we observed decreased density of phosphorylated cofilin immunoreactive and growth hormone immunoreactive cells in the amygdala of sleep deprived mice, providing further support for upscaling of dendritic spines during sleep. Overall, our findings point to region-and spine type-specific changes in dendritic spines during sleep in the amygdala, which may contribute to consolidation of emotional memories during sleep.

Sleep-mediated regulation of reward circuits: implications in substance use disorders

Our modern society suffers from both pervasive sleep loss and substance abuse-what may be the indications for sleep on substance use disorders (SUDs), and could sleep contribute to the individual variations in SUDs? Decades of research in sleep as well as in motivated behaviors have laid the foundation for us to begin to answer these questions. This review is intended to critically summarize the circuit, cellular, and molecular mechanisms by which sleep influences reward function, and to reveal critical challenges for future studies. The review also suggests that improving sleep quality may serve as complementary therapeutics for treating SUDs, and that formulating sleep metrics may be useful for predicting individual susceptibility to SUDs and other reward-associated psychiatric diseases.

Neural circuit plasticity for complex non-declarative sensorimotor memory consolidation during sleep

Evidence is accumulating that the brain actively consolidates long-term memory during sleep. Motor skill memory is a form of non-declarative procedural memory and can be coordinated with multi-sensory processing such as visual, tactile, and, auditory. Conversely, perception is affected by body movement signal from motor brain regions. Although both cortical and subcortical brain regions are involved in memory consolidation, cerebral cortex activity can be recorded and manipulated noninvasively or minimally invasively in humans and animals. NREM sleep, which is important for non-declarative memory consolidation, is characterized by slow and spindle waves representing thalamo-cortical population activity. In animals, electrophysiological recording, optical imaging, and manipulation approaches have revealed multi-scale cortical dynamics across learning and sleep. In the sleeping cortex, neural activity is affected by prior learning and neural circuits are continually reorganized. Here I outline how sensorimotor coordination is formed through awake learning and subsequent sleep.

Correlating electroconvulsive therapy response to electroencephalographic markers: Study protocol

Introduction

Electroconvulsive therapy (ECT) is an effective intervention for patients with major depressive disorder (MDD). Despite longstanding use, the underlying mechanisms of ECT are unknown, and there are no objective prognostic biomarkers that are routinely used for ECT response. Two electroencephalographic (EEG) markers, sleep slow waves and sleep spindles, could address these needs. Both sleep microstructure EEG markers are associated with synaptic plasticity, implicated in memory consolidation, and have reduced expression in depressed individuals. We hypothesize that ECT alleviates depression through enhanced expression of sleep slow waves and sleep spindles, thereby facilitating synaptic reconfiguration in pathologic neural circuits.

Methods

Correlating ECT Response to EEG Markers (CET-REM) is a single-center, prospective, observational investigation. Wireless wearable headbands with dry EEG electrodes will be utilized for at-home unattended sleep studies to allow calculation of quantitative measures of sleep slow waves (EEG SWA, 0.5-4 Hz power) and sleep spindles (density in number/minute). High-density EEG data will be acquired during ECT to quantify seizure markers.

Discussion

This innovative study focuses on the longitudinal relationships of sleep microstructure and ECT seizure markers over the treatment course. We anticipate that the results from this study will improve our understanding of ECT.

Mutual interaction between visual homeostatic plasticity and sleep in adult humans

Sleep and plasticity are highly interrelated, as sleep slow oscillations and sleep spindles are associated with consolidation of Hebbian-based processes. However, in adult humans, visual cortical plasticity is mainly sustained by homeostatic mechanisms, for which the role of sleep is still largely unknown. Here, we demonstrate that non-REM sleep stabilizes homeostatic plasticity of ocular dominance induced in adult humans by short-term monocular deprivation: the counterintuitive and otherwise transient boost of the deprived eye was preserved at the morning awakening (>6 hr after deprivation). Subjects exhibiting a stronger boost of the deprived eye after sleep had increased sleep spindle density in frontopolar electrodes, suggesting the involvement of distributed processes. Crucially, the individual susceptibility to visual homeostatic plasticity soon after deprivation correlated with the changes in sleep slow oscillations and spindle power in occipital sites, consistent with a modulation in early occipital visual cortex.

Is the role of sleep in memory consolidation overrated?

Substantial empirical evidence suggests that sleep benefits the consolidation and reorganization of learned information. Consequently, the concept of "sleep-dependent memory consolidation" is now widely accepted by the scientific community, in addition to influencing public perceptions regarding the functions of sleep. There are, however, numerous studies that have presented findings inconsistent with the sleep-memory hypothesis. Here, we challenge the notion of "sleep-dependency" by summarizing evidence for effective memory consolidation independent of sleep. Plasticity mechanisms thought to mediate or facilitate consolidation during sleep (e.g., neuronal replay, reactivation, slow oscillations, neurochemical milieu) also operate during non-sleep states, particularly quiet wakefulness, thus allowing for the stabilization of new memories. We propose that it is not sleep per se, but the engagement of plasticity mechanisms, active during both sleep and (at least some) waking states, that constitutes the critical factor determining memory formation. Thus, rather than playing a "critical" role, sleep falls along a continuum of behavioral states that vary in their effectiveness to support memory consolidation at the neural and behavioral level.

Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus

Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.

A Biologically Inspired Neural Network Model to Gain Insight Into the Mechanisms of Post-Traumatic Stress Disorder and Eye Movement Desensitization and Reprocessing Therapy

Eye movement desensitization and reprocessing (EMDR) therapy is a well-established therapeutic method to treat post-traumatic stress disorder (PTSD). However, how EMDR exerts its therapeutic action has been studied in many types of research but still needs to be completely understood. This is in part due to limited knowledge of the neurobiological mechanisms underlying EMDR, and in part to our incomplete understanding of PTSD. In order to model PTSD, we used a biologically inspired computational model based on firing rate units, encompassing the cortex, hippocampus, and amygdala. Through the modulation of its parameters, we fitted real data from patients treated with EMDR or classical exposure therapy. This allowed us to gain insights into PTSD mechanisms and to investigate how EMDR achieves trauma remission.

Timely coupling of sleep spindles and slow waves is linked to early amyloid-β burden and predicts memory decline

Sleep alteration is a hallmark of ageing and emerges as a risk factor for Alzheimer’s disease (AD). While the fine-tuned coalescence of sleep microstructure elements may influence age-related cognitive trajectories, its association with AD processes is not fully established. Here, we investigated whether the coupling of spindles and slow waves (SW) is associated with early amyloid-β (Aβ) brain burden, a hallmark of AD neuropathology, and cognitive change over 2 years in 100 healthy individuals in late-midlife (50–70 years; 68 women). We found that, in contrast to other sleep metrics, earlier occurrence of spindles on slow-depolarisation SW is associated with higher medial prefrontal cortex Aβ burden (p=0.014, r²_β*=0.06) and is predictive of greater longitudinal memory decline in a large subsample (p=0.032, r²_β*=0.07, N=66). These findings unravel early links between sleep, AD-related processes, and cognition and suggest that altered coupling of sleep microstructure elements, key to its mnesic function, contributes to poorer brain and cognitive trajectories in ageing.

Tonic excitation of nucleus reuniens decreases prefrontal-hippocampal coordination during slow-wave states

The nucleus reuniens of the thalamus (RE) is an important node between the medial prefrontal cortex (mPFC) and the hippocampus (HPC). Previously, we have shown that its mode of activity and its influence in mPFC-HPC communication is dependent upon brain state. During slow-wave states, RE units are closely and rhythmically coupled to the ongoing mPFC-slow oscillation (SO), while during activated (theta) states, RE neurons fire in an arrhythmic and tonically active manner. Inactivating the RE selectively impoverishes coordination of the SO between mPFC and HPC and interestingly, both mPFC and RE stimulation during the SO cause larger responses in the HPC than during theta. It is unclear if the activity patterns within the RE across states may play a role in both phenomena. Here, we optogenetically excited RE neurons in a tonic fashion to assess the impact on mPFC-HPC coupling. This stimulation decreased the influence of mPFC stimulation in the HPC during SO states, in a manner similar to what is observed across state changes into theta. Importantly, this type of stimulation had no effect on evoked responses during theta. Perhaps more interestingly, tonic optogenetic excitation of the RE also decreased mPFC-HPC SO coherence. Thus, it may not be the integrity of the RE per se that is responsible for efficient communication between mPFC and HPC, but rather the particular state in which RE neurons find themselves. Our results have direct implications for how distant brain regions can communicate most effectively, an issue that is ultimately important for activity-dependent processes occurring during slow-wave sleep-dependent memory consolidation.

Prefrontal-Hippocampal Pathways Through the Nucleus Reuniens Are Functionally Biased by Brain State

Circuit-level communication between disparate brain regions is fundamental for the complexities of the central nervous system operation. Co-ordinated bouts of rhythmic activity between the prefrontal cortex (PFC) and hippocampus (HPC), in particular, are important for mnemonic processes. This is true during awake behavior, as well as during offline states like sleep. We have recently shown that the anatomically interposed thalamic nucleus reuniens (RE) has a role in coordinating slow-wave activity between the PFC and HPC. Here, we took advantage of spontaneous brain state changes occurring during urethane anesthesia in order to assess if PFC-HPC communication was modified during activated (theta) vs. deactivated (slow oscillation: SO) states. These forebrain states are highly similar to those expressed during rapid eye movement (REM) and non-REM stages of natural sleep, respectively. Evoked potentials and excitatory current sinks in the HPC were consistently larger during SO states, regardless of whether PFC or RE afferents were stimulated. Interestingly, PFC stimulation during theta appeared to preferentially use a cortico-cortical pathway, presumably involving the entorhinal cortex as opposed to the more direct RE to HPC conduit. Optogenetic and chemogenetic manipulations of the RE suggested that this state-dependent biasing was mediated by responding in the RE itself. Finally, the phase of both ongoing rhythms also appeared to be an important factor in modulating HPC responses, with maximal field excitatory postsynaptic potentials (EPSPs) occurring during the negative-going phase of both rhythms. Thus, forebrain state plays an important role in how communication takes place across the PFC and HPC, with the RE as a determining factor in how this is shaped. Furthermore, ongoing sleep-like rhythms influence the coordination and perhaps potentiate excitatory processing in this extended episodic memory circuit. Our results have direct implications for activity-dependent processes relevant to sleep-dependent memory consolidation.

Subthreshold membrane potential dynamics of posterior parietal cortical neurons coupled with hippocampal ripples

During behavioral states of immobility, sleep, and anesthesia, the hippocampus generates high-frequency oscillations called ripples. Ripples occur simultaneously with synchronous neuronal activity in the neocortex, known as slow waves, and contribute to memory consolidation. During these ripples, various neocortical regions exhibit modulations in spike rates and local field activity irrespective of whether they receive direct synaptic inputs from the hippocampus. However, little is known about the subthreshold dynamics of the membrane potentials of neocortical neurons during ripples. We patch-clamped layer 2/3 pyramidal cells in the posterior parietal cortex (PPC), a neocortical region that is involved in allocentric spatial representation of behavioral exploration and sequential series of relevant action potentials during ripples. We simultaneously monitored the membrane potentials of post hoc-identified PPC neurons and the local field potentials of the hippocampus in anesthetized mice. More than 50% of the recorded PPC neurons exhibited significant depolarizations and/or hyperpolarizations during ripples. Histological inspections of the recorded neurons revealed that the ripple-modulated PPC neurons were distributed in the PPC in a spatially non-biased fashion. These results suggest that hippocampal ripples are widely but selectively associated with the subthreshold dynamics of the membrane potentials of PPC neurons even though there is no monosynaptic connectivity between the hippocampus and the PPC.

Learning poly-synaptic paths with traveling waves

Traveling waves are commonly observed across the brain. While previous studies have suggested the role of traveling waves in learning, the mechanism remains unclear. We adopted a computational approach to investigate the effect of traveling waves on synaptic plasticity. Our results indicate that traveling waves facilitate the learning of poly-synaptic network paths when combined with a reward-dependent local synaptic plasticity rule. We also demonstrate that traveling waves expedite finding the shortest paths and learning nonlinear input/output mapping, such as exclusive or (XOR) function.

There are approximately 10¹¹ neurons with 10¹⁴ connections in the human brain. Information transmission among neurons in this large network is considered crucial for our behavior. To achieve this, multiple synaptic connections along a poly-synaptic network path must be adjusted coherently during learning. Because the previously proposed reward-dependent synaptic plasticity rule requires coactivation of presynaptic and postsynaptic neurons, learning can fail if a subset of neurons along a distant network path is inactive at the beginning of learning. We suggest that traveling waves that are initiated at an information source can mitigate this problem. We performed computer simulations of spiking neural networks with reward-dependent local synaptic plasticity rules and traveling waves. Our results show that this combination facilitates the learning and refinement of synaptic network paths. We argue that these features are a general biological strategy for maintaining and optimizing our brain function. Our research provides new insights into how complex neural networks in the brain form during learning and memory consolidation.

Delta resting-state functional connectivity in the cognitive control network as a prognostic factor for maintaining abstinence: An eLORETA preliminary study

BACKGROUND

Cortical regions that support cognitive control are increasingly well recognized, but the functional mechanisms that promote such control over emotional and behavioral hyperreactivity to alcohol in recently abstinent alcohol-dependent patients are still insufficiently understood. This study aimed to identify neurophysiological biomarkers of maintaining abstinence in alcohol-dependent individuals after alcohol treatment by investigating the resting-state EEG-based functional connectivity in the cognitive control network (CCN).

METHODS

Lagged phase synchronization between CCN areas by means of eLORETA as well as the Barratt Impulsiveness Scale (BIS-11) and Beck Depression Inventory (BDI) were assessed in abstinent alcohol-dependent patients recruited from treatment centers. A preliminary prospective study design was used to classify participants into those who did and did not maintain abstinence during a follow-up period (median 12 months) after discharge from residential treatment.

RESULTS

Alcohol-dependent individuals, who maintained abstinence (N = 18), showed significantly increased lagged phase synchronization between the left dorsolateral prefrontal cortex (DLPFC) and the left posterior parietal cortex (IPL) as well as between the right anterior insula cortex/frontal operculum (IA/FO) and the right inferior frontal junction (IFJ) in the delta band compared to those who later relapsed (N = 16). Regression analysis showed that the increased left frontoparietal delta connectivity in the early period of abstinence significantly predicted maintaining abstinence over the ensuing 12 months. Furthermore, right frontoinsular delta connectivity correlated negatively with impulsivity and depression measures.

CONCLUSIONS

These results suggest that the increased delta resting-state functional connectivity in the CCN may be a promising neurophysiological predictor of maintaining abstinence in individuals with alcohol dependence.

Disruption of neocortical synchronisation during slow-wave sleep in the rotenone model of Parkinson's disease

Parkinson's disease motor dysfunctions are associated with improperly organised neural oscillatory activity. The presence of such disruption at the early stages of the disease in which altered sleep is one of the main features could be a relevant predictive feature. Based on this, we aimed to investigate the neocortical synchronisation dynamics during slow-wave sleep (SWS) in the rotenone model of Parkinson's disease. After rotenone administration within the substantia nigra pars compacta, one group of male Wistar rats underwent sleep-wake recording. Considering the association between SWS oscillatory activity and memory consolidation, another group of rats underwent a memory test. The fine temporal structure of synchronisation dynamics was evaluated by a recently developed technique called first return map. We observed that rotenone administration decreased the time spent in SWS and altered the power spectrum within different frequency bands, whilst it increased the transition rate from a synchronised to desynchronised state. This neurotoxin also increased the probability of longer and decreased the probability of shorter desynchronisation events. At the same time, we observed impairment in object recognition memory. These findings depict an electrophysiological fingerprint represented by a disruption in the typical oscillatory activity within the neocortex at the early stages of Parkinson's disease, concomitant with a decrease in the time spent in SWS and impairment in recognition memory.

The Bidirectional Relationship Between Sleep and Inflammation Links Traumatic Brain Injury and Alzheimer's Disease

Traumatic brain injury (TBI) and Alzheimer's disease (AD) are diseases during which the fine-tuned autoregulation of the brain is lost. Despite the stark contrast in their causal mechanisms, both TBI and AD are conditions which elicit a neuroinflammatory response that is coupled with physical, cognitive, and affective symptoms. One commonly reported symptom in both TBI and AD patients is disturbed sleep. Sleep is regulated by circadian and homeostatic processes such that pathological inflammation may disrupt the chemical signaling required to maintain a healthy sleep profile. In this way, immune system activation can influence sleep physiology. Conversely, sleep disturbances can exacerbate symptoms or increase the risk of inflammatory/neurodegenerative diseases. Both TBI and AD are worsened by a chronic pro-inflammatory microenvironment which exacerbates symptoms and worsens clinical outcome. Herein, a positive feedback loop of chronic inflammation and sleep disturbances is initiated. In this review, the bidirectional relationship between sleep disturbances and inflammation is discussed, where chronic inflammation associated with TBI and AD can lead to sleep disturbances and exacerbated neuropathology. The role of microglia and cytokines in sleep disturbances associated with these diseases is highlighted. The proposed sleep and inflammation-mediated link between TBI and AD presents an opportunity for a multifaceted approach to clinical intervention.

Sleep slow oscillations favour local cortical plasticity underlying the consolidation of reinforced procedural learning in human sleep

We investigated changes of slow-wave activity and sleep slow oscillations in the night following procedural learning boosted by reinforcement learning, and how these changes correlate with behavioural output. In the Task session, participants had to reach a visual target adapting cursor's movements to compensate an angular deviation introduced experimentally, while in the Control session no deviation was applied. The task was repeated at 13:00 hours, 17:00 hours and 23:00 hours before sleep, and at 08:00 hours after sleep. The deviation angle was set at 15° (13:00 hours and 17:00 hours) and increased to 45° (reinforcement) at 23:00 hours and 08:00 hours. Both for Task and Control nights, high-density electroencephalogram sleep recordings were carried out (23:30-19:30 hours). The Task night as compared with the Control night showed increases of: (a) slow-wave activity (absolute power) over the whole scalp; (b) slow-wave activity (relative power) in left centro-parietal areas; (c) sleep slow oscillations rate in sensorimotor and premotor areas; (d) amplitude of pre-down and up states in premotor regions, left sensorimotor and right parietal regions; (e) sigma crowning the up state in right parietal regions. After Task night, we found an improvement of task performance showing correlations with sleep slow oscillations rate in right premotor, sensorimotor and parietal regions. These findings suggest a key role of sleep slow oscillations in procedural memories consolidation. The diverse components of sleep slow oscillations selectively reflect the network activations related to the reinforced learning of a procedural visuomotor task. Indeed, areas specifically involved in the task stand out as those with a significant association between sleep slow oscillations rate and overnight improvement in task performance.

Low acetylcholine during early sleep is important for motor memory consolidation

The synaptic homeostasis theory of sleep proposes that low neurotransmitter activity in sleep optimizes memory consolidation. We tested this theory by asking whether increasing acetylcholine levels during early sleep would weaken motor memory consolidation. We trained separate groups of adult mice on the rotarod walking task and the single pellet reaching task, and after training, administered physostigmine, an acetylcholinesterase inhibitor, to increase cholinergic tone in subsequent sleep. Post-sleep testing showed that physostigmine impaired motor skill acquisition of both tasks. Home-cage video monitoring and electrophysiology revealed that physostigmine disrupted sleep structure, delayed non-rapid-eye-movement sleep onset, and reduced slow-wave power in the hippocampus and cortex. Additional experiments showed that: (1) the impaired performance associated with physostigmine was not due to its effects on sleep structure, as 1 h of sleep deprivation after training did not impair rotarod performance, (2) a reduction in cholinergic tone by inactivation of cholinergic neurons during early sleep did not affect rotarod performance, and (3) stimulating or blocking muscarinic and nicotinic acetylcholine receptors did not impair rotarod performance. Taken together, the experiments suggest that the increased slow wave activity and inactivation of both muscarinic and nicotinic receptors during early sleep due to reduced acetylcholine contribute to motor memory consolidation.

Autonomic/central coupling benefits working memory in healthy young adults

Working memory (WM) is an executive function that can improve with training. However, the precise mechanism for this improvement is not known. Studies have shown greater WM gains after a period of sleep than a similar period of wake, and correlations between WM improvement and slow wave activity (SWA; 0.5-1 Hz) during slow wave sleep (SWS). A different body of literature has suggested an important role for autonomic activity during wake for WM. A recent study from our group reported that the temporal coupling of Autonomic/CentralEvents (ACEs) during sleep was associated with memory consolidation. We found that heart rate bursts (HR bursts) during non-rapid eye movement (NREM) sleep are accompanied by increases in SWA and sigma (12-15 Hz) power, as well as increases in the high-frequency (HF) component of the RR interval, reflecting vagal rebound. In addition, ACEs predict long-term, episodic memory improvement. Building on these previous results, we examined whether ACEs also contribute to gains in WM. We tested 104 young adults in an operation span task (OSPAN) in the morning and evening, with either a nap (n = 53; with electroencephalography (EEG) and electrocardiography (ECG)) or wake (n = 51) between testing sessions. We identified HR bursts in the ECG and replicated the increases in SWA and sigma prior to peak of the HR burst, as well as vagal rebound after the peak. Furthermore, we showed sleep-dependent WM improvement, which was predicted by ACE activity. Using regression analyses, we discovered that significantly more variance in WM improvement could be explained with ACE variables than with overall sleep activity not time-locked with ECG. These results provide the first evidence that coordinated autonomic and central events play a significant role in sleep-related WM improvement and implicate the potential of autonomic interventions during sleep for cognitive enhancement.

Competing Roles of Slow Oscillations and Delta Waves in Memory Consolidation versus Forgetting

Sleep has been implicated in both memory consolidation and forgetting of experiences. However, it is unclear what governs the balance between consolidation and forgetting. Here, we tested how activity-dependent processing during sleep might differentially regulate these two processes. We specifically examined how neural reactivations during non-rapid eye movement (NREM) sleep were causally linked to consolidation versus weakening of the neural correlates of neuroprosthetic skill. Strikingly, we found that slow oscillations (SOs) and delta (δ) waves have dissociable and competing roles in consolidation versus forgetting. By modulating cortical spiking linked to SOs or δ waves using closed-loop optogenetic methods, we could, respectively, weaken or strengthen consolidation and thereby bidirectionally modulate sleep-dependent performance gains. We further found that changes in the temporal coupling of spindles to SOs relative to δ waves could account for such effects. Thus, our results indicate that neural activity driven by SOs and δ waves have competing roles in sleep-dependent memory consolidation.

Experience and sleep-dependent synaptic plasticity: from structure to activity

Synaptic plasticity is important for learning and memory. With increasing evidence linking sleep states to changes in synaptic strength, an emerging view is that sleep promotes learning and memory by facilitating experience-induced synaptic plasticity. In this review, we summarize the recent progress on the function of sleep in regulating cortical synaptic plasticity. Specifically, we outline the electroencephalogram signatures of sleep states (e.g. slow-wave sleep, rapid eye movement sleep, spindles), sleep state-dependent changes in gene and synaptic protein expression, synaptic morphology, and neuronal and network activity. We highlight studies showing that post-experience sleep potentiates experience-induced synaptic changes and discuss the potential mechanisms that may link sleep-related brain activity to synaptic structural remodelling. We conclude that both synapse formation or strengthening and elimination or weakening occur across sleep. This sleep-dependent synaptic plasticity plays an important role in neuronal circuit refinement during development and after learning, while sleep disorders may contribute to or exacerbate the development of common neurological diseases. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Preferential Consolidation of Emotional Memory During Sleep: A Meta-Analysis

It is uncertain whether sleep preferentially consolidates emotional over neutral material. Some studies suggest that sleep enhances emotional memory (i.e., that there are large differences in strength of memory for valenced material compared to neutral material after a sleep-filled interval, but that this difference is smaller after a wake-filled interval). Others find no such effect. We attempted to resolve this uncertainty by conducting a meta-analysis that compared valenced to neutral material after both sleep- and wake-filled delays. Standard search strategies identified 31 studies (containing 36 separate datasets) that met our inclusion criteria. Using random effects modeling, we conducted separate analyses for datasets comparing (a) negative vs. neutral material, (b) positive vs. neutral material, or (c) combined negative and positive vs. neutral material. We then specified several subgroup analyses to investigate potential moderators of the relationship between sleep and emotional memory consolidation. Results showed no overall effect for preferential sleep-dependent consolidation of emotional over neutral material. However, moderation analyses provided evidence for stronger effects when (a) studies used free recall rather than recognition outcome measures, or (b) delayed recall or recognition outcomes were controlled for initial learning. Those analyses also suggested that other methodological features (e.g., whether participants experience a full night of sleep and a regular daytime waking control condition rather than a nap and a night-time sleep deprivation control condition) and sample characteristics (e.g. all-male or not, young adult or not) should be carefully addressed in future research in this field. These findings suggest that sleep does enhance emotional memory, but that in the laboratory the effect is only observed under particular methodological conditions. The conditions we identify as being critical to consider are consistent with general theories guiding scientific understanding of memory consolidation during sleep.