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

Astrocyte regulation of behavioral outputs: the versatile roles of calcium

Behavior arises from coordinated brain-wide neural and glial networks, enabling organisms to perceive, interpret, and respond to stimuli. Astrocytes play an important role in shaping behavioral output, yet the underlying molecular mechanisms are not fully understood. Astrocytes respond to intrinsic and extrinsic cues with calcium (Ca2+) fluctuations, which are highly heterogeneous across spatio-temporal scales, contexts, and brain regions. This heterogeneity allows astrocytes to exert dynamic regulatory effects on neuronal function but has made it challenging to understand the precise mechanisms and pathways linking astrocytic Ca2+ to specific behavioral outcomes, and the functional relevance of these signals remains unclear. Here, we review recent literature uncovering roles for astrocytic Ca2+ signaling in a wide array of behaviors, including cognitive, homeostatic, and affective focusing on its physiological roles, and potential pathological implications. We specifically highlight how different types of astrocytic Ca2+ signals are linked to distinct behavioral outcomes and discuss limitations and unanswered questions that remain to be addressed.

Sleep Alterations and Cognitive Decline

Sleep disturbances and cognitive decline are intricately connected, and both are prevalent in aging populations and individuals with neurodegenerative disorders such as Alzheimer's disease (AD) and other dementias. Sleep is vital for cognitive functions including memory consolidation, executive function, and attention. Disruption in these processes is associated with cognitive decline, although causal evidence is mixed. This review delves into the bidirectional relationship between alterations in sleep and cognitive impairment, exploring key mechanisms such as amyloid-β accumulation, tau pathology, synaptic homeostasis, neurotransmitter dysregulation, oxidative stress, and vascular contributions. Evidence from both experimental research and population-based studies underscores the necessity of early interventions targeting sleep to mitigate risks of neurodegenerative diseases. A deeper understanding of the interplay between sleep and cognitive health may pave the way for innovative strategies to prevent or reduce cognitive decline through improved sleep management.

Salient objects in a scene trigger enhanced perceptual selection and memory encoding

Rapidly detecting salient objects from surrounding environments is crucial for survival. Our study demonstrates that salient objects in visual search arrays trigger von Restorff-like effects. In a search task, participants detected a tilted target bar among distractors with EEG recordings. The results revealed that salient objects elicited the largest and earliest N2pc component, reflecting early attentional selection, which enhanced multivariate decoding of target location. Importantly, early selection of highly salient targets (25° tilt) triggered a cascade of preferential processing downstream, marked by stronger P3b components, neural synchronization, and phase-amplitude coupling between low- and high-frequency activity, along with better recall performance of target orientation. The strength of memory-related activity on the current trial predicted the vigor of the next selection event, indicating that salience-driven learning influences future attentional control. Overall, object salience in spatial arrays drives a cascade of processing, facilitating rapid learning of object relevance while humans search their environment.

Amygdalo-cortical dialogue underlies memory enhancement by emotional association

Emotional arousal plays a critical role in determining what is remembered from experiences. It is hypothesized that activation of the amygdala by emotional stimuli enhances memory consolidation in its downstream brain regions. However, the physiological basis of the inter-regional interaction and its functions remain unclear. Here, by adding emotional information to a perceptual recognition task that relied on a frontal-sensory cortical circuit in mice, we demonstrated that the amygdala not only associates emotional information with perceptual information but also enhances perceptual memory retention via amygdalo-frontal cortical projections. Furthermore, emotional association increased reactivation of coordinated activity across the amygdalo-cortical circuit during non-rapid eye movement (NREM) sleep but not during rapid eye movement (REM) sleep. Notably, this increased reactivation was associated with amygdala high-frequency oscillations. Silencing of amygdalo-cortical inputs during NREM sleep selectively disrupted perceptual memory enhancement. Our findings indicate that inter-regional reactivation triggered by the amygdala during NREM sleep underlies emotion-induced perceptual memory enhancement.

Electrophysiological signatures underlying variability in human memory consolidation

We experience countless pieces of new information each day, but remembering them later depends on firmly instilling memory storage in the brain. Numerous studies have implicated non-rapid eye movement (NREM) sleep in consolidating memories via interactions between hippocampus and cortex. However, the temporal dynamics of this hippocampal-cortical communication and the concomitant neural oscillations during memory reactivations remains unclear. To address this issue, the present study used the procedure of targeted memory reactivation (TMR) following learning of object-location associations to selectively reactivate memories during human NREM sleep. Cortical pattern reactivation and hippocampal-cortical coupling were measured with intracranial EEG recordings in patients with epilepsy. We found that TMR produced variable amounts of memory enhancement across a set of object-location associations. Successful TMR increased hippocampal ripples and cortical spindles, apparent during two discrete sweeps of reactivation. The first reactivation sweep was accompanied by increased hippocampal-cortical communication and hippocampal ripple events coupled to local cortical activity (cortical ripples and high-frequency broadband activity). In contrast, hippocampal-cortical coupling decreased during the second sweep, while increased cortical spindle activity indicated continued cortical processing to achieve long-term storage. Taken together, our findings show how dynamic patterns of item-level reactivation and hippocampal-cortical communication support memory enhancement during NREM sleep.

Sampling representational plasticity of simple imagined movements across days enables long-term neuroprosthetic control

The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what the representational stability of simple well-rehearsed actions is, particularly in humans, and their adaptability to new contexts. Using an electrocorticography brain-computer interface (BCI) in tetraplegic participants, we found that the low-dimensional manifold and relative representational distances for a repertoire of simple imagined movements were remarkably stable. The manifold's absolute location, however, demonstrated constrained day-to-day drift. Strikingly, neural statistics, especially variance, could be flexibly regulated to increase representational distances during BCI control without somatotopic changes. Discernability strengthened with practice and was BCI-specific, demonstrating contextual specificity. Sampling representational plasticity and drift across days subsequently uncovered a meta-representational structure with generalizable decision boundaries for the repertoire; this allowed long-term neuroprosthetic control of a robotic arm and hand for reaching and grasping. Our study offers insights into mesoscale representational statistics that also enable long-term complex neuroprosthetic control.

Infant sleep EEG features at 4 months as biomarkers of neurodevelopment at 18 months

BACKGROUND

Sleep parameters evolve in parallel with neurodevelopment. Sleep participates in synaptic homeostasis and memory consolidation and infant sleep parameters correlate with later aspects of early childhood cognition.

METHODS

Typically developing, term-born infants had a diurnal sleep-EEG at 4 months and Griffiths III developmental assessment at 18 months. EEG analysis included sleep macrostructure (i.e. durations of total sleep and sleep stages, and latencies to sleep and REM), sleep spindle features, and quantitative EEG features (qEEG): interhemispheric connectivity and spectral power. We assessed the correlations between these EEG features and Griffiths III quotients.

RESULTS

Sleep recordings from 92 infants were analyzed. Sleep latency was positively associated with the Griffiths III Foundations of Learning subscale and N3 sleep duration was positively correlated with the Personal-Social-Emotional subscale. Sleep spindle synchrony was negatively associated with Eye and Hand Coordination, Personal-Social-Emotional, Gross Motor, and General Development quotients. Sleep spindle duration was negatively associated with the Personal-Social-Emotional and Gross Motor subscales. In some sleep states, delta 1 and 2 EEG spectral power and interhemispheric coherence measures were correlated with subscale quotients.

CONCLUSION

Certain sleep features in the EEG of 4-month-old infants are associated with neurodevelopment at 18 months and may be useful early biomarkers of neurodevelopment.

IMPACT

This study shows that the EEG during infant sleep may provide insights into later neurodevelopmental outcomes. We have examined novel EEG sleep spindle features and shown that spindle duration and synchrony may help predict neurodevelopmental outcomes. Sleep macrostructure elements such as latency to sleep, N3 duration, and qEEG features such as interhemispheric coherence and spectral power measures at 4 months may be useful for the assessment of future neurodevelopmental outcomes. Due to exceptional neuroplasticity in infancy, EEG biomarkers of neurodevelopment may support early and targeted intervention to optimize outcomes.

The value of electroencephalography features in the prognostic evaluation of large hemispheric infarction patients at different time intervals

BACKGROUND

Large Hemispheric Infarction (LHI) is a devastating disease with high mortality. This study aimed to use electroencephalography (EEG) to evaluate the death risk of LHI patients and identify suitable evaluation time.

METHODS

This study retrospectively collected clinical and EEG data from 73 LHI patients, dividing them into death and survival group at discharge. EEG data was classified as 1-5 days and 6-14 days after onset according to the time intervals of cerebral edema. Regression and receiver operator characteristic curve (ROC) analysis were applied to explore the impact of temporal changes in various EEG and clinical features on death.

RESULTS

The areas under ROC curve (AUC) of death prediction for non-α frequency on non-infarct side at 6-14 days after onset was significantly higher than that at 1-5 days (p = 0.004). And there was no significant difference between the AUC of seizure activity for death prediction at 1-5 days and 6-14 days (p = 0.418). Multivariate regression analysis revealed that non-α frequency on non-infarct side and seizure activity at 6-14 days after onset were the independent risk factors for the death of LHI patients. Additionally, above two EEG features significantly improved the death predictive efficacy of clinical features in LHI patients with the integrated discrimination improvement index (IDI) of 0.174 (p = 0.015) and the net reclassification improvement (NRI) of 1.314 (p<0.001).

CONCLUSIONS

Non-α frequency on non-infarct side and seizure activity were reliable indicators for death prediction. 6-14 days after onset was the better time window for death evaluation of LHI patients through EEG.

Electrophysiological insights into Alzheimer's disease: A review of human and animal studies

This review highlights the crucial role of neuroelectrophysiology in illuminating the mechanisms underlying Alzheimer's disease (AD) pathogenesis and progression, emphasizing its potential to inform the development of effective treatments. Electrophysiological techniques provide unparalleled precision in exploring the intricate networks affected by AD, offering insights into the synaptic dysfunction, network alterations, and oscillatory abnormalities that characterize the disease. We discuss a range of electrophysiological methods, from non-invasive clinical techniques like electroencephalography and magnetoencephalography to invasive recordings in animal models. By drawing on findings from these studies, we demonstrate how electrophysiological research has deepened our understanding of AD-related network disruptions, paving the way for targeted therapeutic interventions. Moreover, we underscore the potential of electrophysiological modalities to play a pivotal role in evaluating treatment efficacy. Integrating electrophysiological data with clinical neuroimaging and longitudinal studies holds promise for a more comprehensive understanding of AD, enabling early detection and the development of personalized treatment strategies. This expanded research landscape offers new avenues for unraveling the complexities of AD and advancing therapeutic approaches.

Ensemble reactivations during brief rest drive fast learning of sequences

During motor learning, breaks in practice are known to facilitate behavioural optimizations. Although this process has traditionally been studied over long breaks that last hours to days1-6, recent studies in humans have demonstrated that rapid performance gains during early motor sequence learning are most pronounced after very brief breaks lasting seconds to minutes7-10. However, the precise causal neural mechanisms that facilitate performance gains after brief breaks remain poorly understood. Here we recorded neural ensemble activity in the motor cortex of macaques while they performed a visuomotor sequence learning task interspersed with brief breaks. We found that task-related neural cofiring patterns were reactivated during brief breaks. The rate and content of reactivations predicted the magnitude and pattern of subsequent performance gains. Of note, we found that performance gains and reactivations were positively correlated with cortical ripples (80-120 Hz oscillations) but anti-correlated with β bursts (13-30 Hz oscillations), which ultimately dominated breaks after the fast learning phase plateaued. We then applied 20 Hz epidural alternating current stimulation (ACS) to motor cortex, which reduced reactivation rates in a phase-specific and dose-dependent manner. Notably, 20 Hz ACS also eliminated performance gains. Overall, our results indicate that the reactivations of task ensembles during brief breaks are causal drivers of subsequent performance gains. β bursts compete with this process, possibly to support stable performance.

The stability of slow-wave sleep and EEG oscillations across two consecutive nights of laboratory polysomnography in cognitively normal older adults

Laboratory polysomnography provides gold-standard measures of sleep physiology, but multi-night investigations are resource intensive. We assessed the night-to-night stability via reproducibility metrics for sleep macrostructure and electroencephalography oscillations in a group of cognitively normal adults attending two consecutive polysomnographies. Electroencephalographies were analysed using an automatic algorithm for detection of slow-wave activity, spindle and K-complex densities. Average differences between nights for sleep macrostructure, electroencephalography oscillations and sleep apnea severity were assessed, and test-retest reliability was determined using two-way intraclass correlations. Agreement was calculated using the smallest real differences between nights for all measures. Night 2 polysomnographies showed significantly greater time in bed, total sleep time (6.3 hr versus 6.8 hr, p < 0.001) and percentage of rapid eye movement sleep (17.5 versus 19.7, p < 0.001). Intraclass correlations were low for total sleep time, percentage of rapid eye movement sleep and sleep efficiency, moderate for percentage of slow-wave sleep and percentage of non-rapid eye movement 2 sleep, good for slow-wave activity and K-complex densities, and excellent for spindles and apnea-hypopnea index with hypopneas defined according to 4% oxygen desaturation criteria only. The smallest real difference values were proportionally high for most sleep macrostructure measures, indicating moderate agreement, and proportionally lower for most electroencephalography microstructure variables. Slow waves, K-complexes, spindles and apnea severity indices are highly reproducible across two consecutive nights of polysomnography. In contrast, sleep macrostructure measures all demonstrated poor reproducibility as indicated by low intraclass correlation values and moderate agreement. Although there were average differences in percentage of rapid eye movement sleep and total sleep time, these were numerically small and perhaps functionally or clinically less significant. One night of in-laboratory polysomnography is enough to provide stable, reproducible estimates of an individual's sleep concerning measures of slow-wave activity, spindles, K-complex densities and apnea severity.

Finding Neural Biomarkers for Motor Learning and Rehabilitation using an Explainable Graph Neural Network

Human motor learning is a neural process essential for acquiring new motor skills and adapting existing ones, which is fundamental to everyday activities. Neurological disorders such as Parkinson's Disease (PD) and stroke can significantly affect human motor functions. Identifying neural biomarkers for human motor learning is essential for advancing therapeutic strategies for such disorders. However, identifying specific neural biomarkers associated with motor learning has been challenging due to the complex nature of brain activity and the limitations of traditional data analysis techniques. In response to these challenges, we developed a novel Spatial Graph Neural Network (SGNN) model to predict motor learning outcomes from electroencephalogram (EEG) data using the spatial-temporal dynamics of brain activity. We used it to analyse EEG data collected during a visuomotor rotation (VMR) task designed to elicit distinct types of learning: error-based and reward-based. By doing so, we establish a controlled environment that allows for precisely investigating neural signatures associated with these learning processes. To understand the features learned by the SGNN, we used a set of spatial, spectral, and temporal explainability methods to identify the brain regions and temporal dynamics crucial for learning. These approaches offer comprehensive insights into the neural biomarkers, aligning with current literature and ablation studies, and pave the way for applying this methodology to find biomarkers from various brain signals and tasks.

Mobile Sleep Lab: Comparison of polysomnographic parameters with a conventional sleep laboratory

In remote areas, visiting a laboratory for sleep testing is inconvenient. We, therefore, developed a Mobile Sleep Lab in a bus powered by fuel cells with two sleep measurement chambers. As the environment in the bus could affect sleep, we examined whether sleep testing in the Mobile Sleep Lab was as feasible as in a conventional sleep laboratory (Human Sleep Lab). We tested 15 healthy adults for four nights using polysomnography (the first two nights at the Human Sleep Lab or Mobile Sleep Lab with a switch to the other facility for the next two nights). Sleep variables of the four measurements were used to assess the discrepancy of different places or different nights. No significant differences were found between the laboratories other than the percentage of total sleep time in stage N3. Next, we analyzed the intraclass correlation coefficient to evaluate the test-retest reliability. The intraclass correlation coefficient between these two measurements: the Human Sleep Lab and Mobile Sleep Lab showed similar reliability for the same sleep variables. The intraclass correlation coefficient revealed that several sleep indexes, such as total sleep time, sleep efficiency, wake after sleep onset, percentage of stage N1, and stage R latency, showed poor reliabilities (<0.5) based on Koo and Li's criteria. In contrast, the percentage of stage N3 showed moderate (0.5-0.75) or good (0.75-0.9) reliabilities. As almost all sleep variables showed no difference and same level of test-retest reliability between the Mobile Sleep Lab and Human Sleep Lab, the Mobile Sleep Lab might be suitable for conducting polysomnography as a conventional sleep laboratory. The reduction in N3 in the Mobile Sleep Lab should be scrutinized in the larger sample, including sleep disorders. Practical application of the Mobile Sleep Lab can transform sleep medicine in remote areas.

Multi-region processing during sleep for memory and cognition

Over the past decades, the understanding of sleep has evolved to be a fundamental physiological mechanism integral to the processing of different types of memory rather than just being a passive brain state. The cyclic sleep substates, namely, rapid eye movement (REM) sleep and non-REM (NREM) sleep, exhibit distinct yet complementary oscillatory patterns that form inter-regional networks between different brain regions crucial to learning, memory consolidation, and memory retrieval. Technical advancements in imaging and manipulation approaches have provided deeper understanding of memory formation processes on multi-scales including brain-wide, synaptic, and molecular levels. The present review provides a short background and outlines the current state of research and future perspectives in understanding the role of sleep and its substates in memory processing from both humans and rodents, with a focus on cross-regional brain communication, oscillation coupling, offline reactivations, and engram studies. Moreover, we briefly discuss how sleep contributes to other higher-order cognitive functions.

Membrane potential states gate synaptic consolidation in human neocortical tissue

Synaptic mechanisms that contribute to human memory consolidation remain largely unexplored. Consolidation critically relies on sleep. During slow wave sleep, neurons exhibit characteristic membrane potential oscillations known as UP and DOWN states. Coupling of memory reactivation to these slow oscillations promotes consolidation, though the underlying mechanisms remain elusive. Here, we performed axonal and multineuron patch-clamp recordings in acute human brain slices, obtained from neurosurgeries, to show that sleep-like UP and DOWN states modulate axonal action potentials and temporarily enhance synaptic transmission between neocortical pyramidal neurons. Synaptic enhancement by UP and DOWN state sequences facilitates recruitment of postsynaptic action potentials, which in turn results in long-term stabilization of synaptic strength. In contrast, synapses undergo lasting depression if presynaptic neurons fail to recruit postsynaptic action potentials. Our study offers a mechanistic explanation for how coupling of neural activity to slow waves can cause synaptic consolidation, with potential implications for brain stimulation strategies targeting memory performance.

The claustrum and synchronized brain states

Cortical activity is constantly fluctuating between distinct spatiotemporal activity patterns denoted by changes in brain state. States of cortical desynchronization arise during motor generation, increased attention, and high cognitive load. Synchronized brain states comprise spatially widespread, coordinated low-frequency neural activity during rest and sleep when disengaged from the external environment or 'offline'. The claustrum is a small subcortical structure with dense reciprocal connections with the cortex suggesting modulation by, or participation in, brain state regulation. Here, we highlight recent work suggesting that neural activity in the claustrum supports cognitive processes associated with synchronized brain states characterized by increased low-frequency network activity. As an example, we outline how claustrum activity could support episodic memory consolidation during sleep.

Earable Multimodal Sensing and Stimulation: A Prospective Towards Unobtrusive Closed-Loop Biofeedback

The human ear has emerged as a bidirectional gateway to the brain's and body's signals. Recent advances in around-the-ear and in-ear sensors have enabled the assessment of biomarkers and physiomarkers derived from brain and cardiac activity using ear-electroencephalography (ear-EEG), photoplethysmography (ear-PPG), and chemical sensing of analytes from the ear, with ear-EEG having been taken beyond-the-lab to outer space. Parallel advances in non-invasive and minimally invasive brain stimulation techniques have leveraged the ear's access to two cranial nerves to modulate brain and body activity. The vestibulocochlear nerve stimulates the auditory cortex and limbic system with sound, while the auricular branch of the vagus nerve indirectly but significantly couples to the autonomic nervous system and cardiac output. Acoustic and current mode stimuli delivered using discreet and unobtrusive earables are an active area of research, aiming to make biofeedback and bioelectronic medicine deliverable outside of the clinic, with remote and continuous monitoring of therapeutic responsivity and long-term adaptation. Leveraging recent advances in ear-EEG, transcutaneous auricular vagus nerve stimulation (taVNS), and unobtrusive acoustic stimulation, we review accumulating evidence that combines their potential into an integrated earable platform for closed-loop multimodal sensing and neuromodulation, towards personalized and holistic therapies that are near, in- and around-the-ear.

Neural oscillations and memory: unraveling the mechanisms of anesthesia-induced amnesia

General anesthesia is a widely used medical practice, affecting more than 300 million patients annually. Despite its ubiquity, the underlying mechanisms through which anesthetic agents induce amnesia remain poorly understood. This review explores the impact of general anesthetics on memory function, with a particular focus on the role of neural oscillations in anesthesia-induced memory suppression. Neural oscillations, such as theta, gamma, delta oscillations, slow oscillations (SO), spindles, and sharp wave ripples (SWR), are critical for memory formation and consolidation. Various anesthetics modulate these oscillations in ways that affect memory, even at subanesthetic concentrations. We highlight recent findings on the molecular and electrophysiological mechanisms by which general anesthetics influence memory-related neural oscillations, including the inhibition of synaptic plasticity, alterations in spike-timing-dependent plasticity (STDP), and disruption of cross-frequency couplings like theta-gamma and SO-spindle-SWR. Additionally, the review addresses the significance of age in anesthesia-related memory loss, with elderly patients being particularly vulnerable to long-term cognitive decline. Electrophysiological techniques, such as Electroencephalography (EEG); and advanced neuromodulation techniques, such as chemogenetics, and optogenetics, have provided insights into the neural dynamics underpinning anesthesia-induced amnesia, yet the causal relationship between EEG rhythms and memory impairment remains to be fully elucidated. This review underscores the importance of further research into the interaction between anesthesia, neural oscillations, and memory. Understanding these mechanisms will not only advance theoretical knowledge of general anesthesia but also aid in the development of safer anesthetic strategies to mitigate postoperative cognitive dysfunction, especially in high-risk populations.

Selective Modulation of Fear Memory in Non-Rapid Eye Movement Sleep

Sleep stabilizes memories for their consolidation, but how to modify specific fear memory during sleep remains unclear. Here, it is reported that using targeted memory reactivation (TMR) to reactivate prior fear learning experience in non-slow wave sleep (NS) inhibits fear memory consolidation, while TMR during slow wave sleep (SWS) enhances fear memory in mice. Replaying conditioned stimulus (CS) during sleep affects sleep spindle occurrence, leading to the reduction or enhancement of slow oscillation-spindle (SO-spindle) coupling in NS and SWS, respectively. Optogenetic inhibition of pyramidal neurons in the frontal association cortex (FrA) during TMR abolishes the behavioral effects of NS-TMR and SWS-TMR by modulating SO-spindle coupling. Notably, calcium imaging of the L2/3 pyramidal neurons in the FrA shows that CS during SWS selectively enhances the activity of neurons previously activated during fear conditioning (FC+ neurons), which significantly correlates with CS-elicited spindle power spectrum density. Intriguingly, these TMR-induced calcium activity changes of FC+ neurons further correlate with mice freezing behavior, suggesting their contributions to the consolidation of fear memories. The findings indicate that TMR can selectively weaken or strengthen fear memory, in correlation with modulating SO-spindle coupling and the reactivation of FC+ neurons during substages of non-rapid eye movement (NREM) sleep.

Binaural beats at 0.25 Hz shorten the latency to slow-wave sleep during daytime naps

Binaural beats can entrain neural oscillations and modulate behavioral states. However, the effect of binaural beats, particularly those with slow frequencies (< 1 Hz), on sleep remains poorly understood. We hypothesized that 0.25-Hz beats can entrain neural oscillations and enhance slow-wave sleep by shortening its latency or increasing its duration. To investigate this, we included 12 healthy participants (six women; mean age, 25.4 ± 2.6 years) who underwent four 90-min afternoon nap sessions, comprising a sham condition (without acoustic stimulation) and three binaural-beat conditions (0, 0.25, or 1 Hz) with a 250-Hz carrier tone. The acoustic stimuli, delivered through earphones, were sustained throughout the 90-min nap period. Both N2- and N3- latencies were shorter in the 0.25-Hz binaural beats condition than in the sham condition. We observed no significant results regarding neural entrainment at slow frequencies, such as 0.25 and 1 Hz, and the modulation of sleep oscillations, including delta and sigma activity, by binaural beats. In conclusion, this study demonstrated the potential of binaural beats at slow frequencies, specifically 0.25 Hz, for inducing slow-wave sleep in generally healthy populations.

Coupling of Slow Oscillations in the Prefrontal and Motor Cortex Predicts Onset of Spindle Trains and Persistent Memory Reactivations

Sleep is known to drive the consolidation of motor memories. During nonrapid eye movement (NREM) sleep, the close temporal proximity between slow oscillations (SOs) and spindles ("nesting" of SO-spindles) is known to be essential for consolidation, likely because it is closely associated with the reactivation of awake task activity. Interestingly, recent work has found that spindles can occur in temporal clusters or "trains." However, it remains unclear how spindle trains are related to the nesting phenomenon. Here, we hypothesized that spindle trains are more likely when SOs co-occur in the prefrontal and motor cortex. We conducted simultaneous neural recordings in the medial prefrontal cortex (mPFC) and primary motor cortex (M1) of male rats training on the reach-to-grasp motor task. We found that intracortically recorded M1 spindles are organized into distinct temporal clusters. Notably, the occurrence of temporally precise SOs between mPFC and M1 was a strong predictor of spindle trains. Moreover, reactivation of awake task patterns is much more persistent during spindle trains in comparison with that during isolated spindles. Together, our work suggests that the precise coupling of SOs across mPFC and M1 may be a potential driver of spindle trains and persistent reactivation of motor memory during NREM sleep.

Temporal dynamics of negative emotional memory reprocessing during sleep

Memory reprocessing during sleep is a well-established phenomenon in numerous studies. However, it is unclear whether the intensity of memory reprocessing is consistently maintained throughout the night or exhibits dynamic changes. This study investigates the temporal dynamics of negative emotional memory reprocessing during sleep, with a specific focus on slow oscillation (SO)-spindle coupling and its role in memory reprocessing. In the first experiment (N = 40, mean age = 22.5 years), we detected the negative emotional memory reprocessing strength in each sleep cycle, we found that the 2nd sleep cycle after negative emotional memory learning constitute the most sensitive window for memory reprocessing, furthermore, SO-spindle coupling signals in this window plays a role in stabilizing negative emotional memory. To verify the role of SO-spindle coupling in negative emotional memory reprocessing, we utilized transcranial alternating current stimulation (tACS) to disrupt SO-spindle coupling during the 2nd sleep cycle (N = 21, mean age = 19.3 years). Notably, the outcomes of the tACS intervention demonstrated a significant reduction in the recognition of negative emotional memories. These findings offer new insights into the mechanisms that regulate emotional memory consolidation during sleep and may have implications for addressing psychiatric disorders associated with pathological emotional memory.

Louis EK, McCarter SJ, Bukartyk J, Przybelski SA, Kamykowski MG, Spychalla AJ, Machulda MM, Boeve BF, Petersen RC, Jack CR, Lowe VJ, Graff-Radford J, Worrell GA, Somers VK, Varga AW, Vemuri P. Non-rapid eye movement sleep slow-wave activity features are associated with amyloid accumulation in older adults with obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer's disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5-0.9 Hz) and delta (1-3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by -0.0082 (95% CI: -0.0143; -0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

Alzheimer's disease and sleep disorders: A bidirectional relationship

Alzheimer's disease (AD) is the most prevalent dementia, pathologically featuring abnormal accumulation of amyloid-β (Aβ) and hyperphosphorylated tau, while sleep, divided into rapid eye movement sleep (REM) and nonrapid eye movement sleep (NREM), plays a key role in consolidating social and spatial memory. Emerging evidence has revealed that sleep disorders such as circadian disturbances and disruption of neuronal rhythm activity are considered as both candidate risks and consequence of AD, suggesting a bidirectional relationship between sleep and AD. This review will firstly grasp basic knowledge of AD pathogenesis, then highlight macrostructural and microstructural alteration of sleep along with AD progression, explain the interaction between accumulation of Aβ and hyperphosphorylated tau, which are two critical neuropathological processes of AD, as well as neuroinflammation and sleep, and finally introduce several methods of sleep enhancement as strategies to reduce AD-associated neuropathology. Although theories about the bidirectional relationship and relevant therapeutic methods in mice have been well developed in recent years, the knowledge in human is still limited. More studies on how to effectively ameliorate AD pathology in patients by sleep enhancement and what specific roles of sleep play in AD are needed.

Coordinated NREM sleep oscillations among hippocampal subfields modulate synaptic plasticity in humans

The integration of hippocampal oscillations during non-rapid eye movement (NREM) sleep is crucial for memory consolidation. However, how cardinal sleep oscillations bind across various subfields of the human hippocampus to promote information transfer and synaptic plasticity remains unclear. Using human intracranial recordings from 25 epilepsy patients, we find that hippocampal subfields, including DG/CA3, CA1, and SUB, all exhibit significant delta and spindle power during NREM sleep. The DG/CA3 displays strong coupling between delta and ripple oscillations with all the other hippocampal subfields. In contrast, the regions of CA1 and SUB exhibit more precise coordination, characterized by event-level triple coupling between delta, spindle, and ripple oscillations. Furthermore, we demonstrate that the synaptic plasticity within the hippocampal circuit, as indexed by delta-wave slope, is linearly modulated by spindle power. In contrast, ripples act as a binary switch that triggers a sudden increase in delta-wave slope. Overall, these results suggest that different subfields of the hippocampus regulate one another through diverse layers of sleep oscillation synchronization, collectively facilitating information processing and synaptic plasticity during NREM sleep.

Sleep Consolidation Potentiates Sensorimotor Adaptation

Contrary to its well-established role in declarative learning, the impact of sleep on motor memory consolidation remains a subject of debate. Current literature suggests that while motor skill learning benefits from sleep, consolidation of sensorimotor adaptation (SMA) depends solely on the passage of time. This has led to the proposal that SMA may be an exception to other types of memories. Here, we addressed this ongoing controversy in humans through three comprehensive experiments using the visuomotor adaptation paradigm (N = 290, 150 females). In Experiment 1, we investigated the impact of sleep on memory retention when the temporal gap between training and sleep was not controlled. In line with the previous literature, we found that memory consolidates with the passage of time. In Experiment 2, we used an anterograde interference protocol to determine the time window during which SMA memory is most fragile and, thus, potentially most sensitive to sleep intervention. Our results show that memory is most vulnerable during the initial hour post-training. Building on this insight, in Experiment 3, we investigated the impact of sleep when it coincided with the critical first hour of memory consolidation. This manipulation unveiled a benefit of sleep (30% memory enhancement) alongside an increase in spindle density and spindle-SO coupling during NREM sleep, two well-established neural markers of sleep consolidation. Our findings reconcile seemingly conflicting perspectives on the active role of sleep in motor learning and point to common mechanisms at the basis of memory formation.

Auditory entrainment coordinates cortical-BNST-NAc triple time locking to alleviate the depressive disorder

Listening to music is a promising and accessible intervention for alleviating symptoms of major depressive disorder. However, the neural mechanisms underlying its antidepressant effects remain unclear. In this study on patients with depression, we used auditory entrainment to evaluate intracranial recordings in the bed nucleus of the stria terminalis (BNST) and nucleus accumbens (NAc), along with temporal scalp electroencephalogram (EEG). We highlight music-induced synchronization across this circuit. The synchronization initiates with temporal theta oscillations, subsequently inducing local gamma oscillations in the BNST-NAc circuit. Critically, the incorporated external entrainment induced a modulatory effect from the auditory cortex to the BNST-NAc circuit, activating the antidepressant response and highlighting the causal role of physiological entrainment in enhancing the antidepressant response. Our study explores the pivotal role of the auditory cortex and proposes a neural oscillation triple time-locking model, emphasizing the capacity of the auditory cortex to access the BNST-NAc circuit.

Slow wave activity disruptions and memory impairments in a mouse model of aging

The aging population suffers from memory impairments. Slow-wave activity (SWA) is composed of slow (0.5-1 Hz) and delta (1-4 Hz) oscillations, which play important roles in long-term memory and working memory function respectively. SWA disruptions might lead to memory disturbances often experienced by older adults. We conducted behavioral tests in young and older C57BL/6 J mice. SWA was monitored using wide-field imaging with voltage sensors. Cell-specific calcium imaging was used to monitor the activity of excitatory and inhibitory neurons in these mice. Older mice exhibited impairments in working memory but not memory consolidation. Voltage-sensor imaging revealed aberrant synchronization of neuronal activity in older mice. Notably, we found older mice exhibited no significant alterations in slow oscillations, whereas there was a significant increase in delta power compared to young mice. Calcium imaging revealed hypoactivity in inhibitory neurons of older mice. Combined, these results suggest that neural activity disruptions might correlate with aberrant memory performance in older mice.

Slow-wave sleep drives sleep-dependent renormalization of synaptic AMPA receptor levels in the hypothalamus

According to the synaptic homeostasis hypothesis (SHY), sleep serves to renormalize synaptic connections that have been potentiated during the prior wake phase due to ongoing encoding of information. SHY focuses on glutamatergic synaptic strength and has been supported by numerous studies examining synaptic structure and function in neocortical and hippocampal networks. However, it is unknown whether synaptic down-regulation during sleep occurs in the hypothalamus, i.e., a pivotal center of homeostatic regulation of bodily functions including sleep itself. We show that sleep, in parallel with the synaptic down-regulation in neocortical networks, down-regulates the levels of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) in the hypothalamus of rats. Most robust decreases after sleep were observed at both sites for AMPARs containing the GluA1 subunit. Comparing the effects of selective rapid eye movement (REM) sleep and total sleep deprivation, we moreover provide experimental evidence that slow-wave sleep (SWS) is the driving force of the down-regulation of AMPARs in hypothalamus and neocortex, with no additional contributions of REM sleep or the circadian rhythm. SWS-dependent synaptic down-regulation was not linked to EEG slow-wave activity. However, spindle density during SWS predicted relatively increased GluA1 subunit levels in hypothalamic synapses, which is consistent with the role of spindles in the consolidation of memory. Our findings identify SWS as the main driver of the renormalization of synaptic strength during sleep and suggest that SWS-dependent synaptic renormalization is also implicated in homeostatic control processes in the hypothalamus.

Hyperpolarization-activated currents drive neuronal activation sequences in sleep

Sequential neuronal patterns are believed to support information processing in the cortex, yet their origin is still a matter of debate. We report that neuronal activity in the mouse postsubiculum (PoSub), where a majority of neurons are modulated by the animal's head direction, was sequentially activated along the dorsoventral axis during sleep at the transition from hyperpolarized "DOWN" to activated "UP" states, while representing a stable direction. Computational modeling suggested that these dynamics could be attributed to a spatial gradient of hyperpolarization-activated currents (Ih), which we confirmed in ex vivo slice experiments and corroborated in other cortical structures. These findings open up the possibility that varying amounts of Ih across cortical neurons could result in sequential neuronal patterns and that traveling activity upstream of the entorhinal-hippocampal circuit organizes large-scale neuronal activity supporting learning and memory during sleep.

Prefrontal cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation

Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical slow and spindle oscillations during non-REM sleep. Recent evidence suggests that high-frequency cortical ripples can also coordinate with hippocampal SWRs in support of consolidation; however, the contribution of cortical ripples to reactivation remains unclear. We used high-density, continuous recordings in the hippocampus (area CA1) and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples dissociated from SWRs are prevalent in NREM sleep and predominantly suppress hippocampal activity. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation rather than coordination, and this suppression is stronger for assemblies that are reactivated during coordinated CA1-PFC ripples for consolidation of recent experiences. Further, we show non-canonical, serial coordination of independent cortical ripples with slow and spindle oscillations, which are known signatures of memory consolidation. These results establish a role for prefrontal cortical ripples in top-down regulation of behaviorally relevant hippocampal representations during consolidation.

Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain

Slow-wave sleep (SWS), characterized by slow oscillations (SOs, <1Hz) of alternating active and silent states in the thalamocortical network, is a primary brain state during Non-Rapid Eye Movement (NREM) sleep. In the last two decades, the traditional view of SWS as a global and uniform whole-brain state has been challenged by a growing body of evidence indicating that SO can be local and can coexist with wake-like activity. However, the mechanisms by which global and local SOs arise from micro-scale neuronal dynamics and network connectivity remain poorly understood. We developed a multi-scale, biophysically realistic human whole-brain thalamocortical network model capable of transitioning between the awake state and SWS, and we investigated the role of connectivity in the spatio-temporal dynamics of sleep SO. We found that the overall strength and a relative balance between long and short-range synaptic connections determined the network state. Importantly, for a range of synaptic strengths, the model demonstrated complex mixed SO states, where periods of synchronized global slow-wave activity were intermittent with the periods of asynchronous local slow-waves. An increase in the overall synaptic strength led to synchronized global SO, while a decrease in synaptic connectivity produced only local slow-waves that would not propagate beyond local areas. These results were compared to human data to validate probable models of biophysically realistic SO. The model producing mixed states provided the best match to the spatial coherence profile and the functional connectivity estimated from human subjects. These findings shed light on how the spatio-temporal properties of SO emerge from local and global cortical connectivity and provide a framework for further exploring the mechanisms and functions of SWS in health and disease.

Rescuing impaired hippocampal-cortical interactions and spatial reorientation learning and memory during sleep in a mouse model of Alzheimer's disease using hippocampal 40 Hz stimulation

In preclinical Alzheimer's disease (AD), spatial learning and memory is impaired. We reported similar impairments in 3xTg-AD mice on a virtual maze (VM) spatial-reorientation-task that requires using landmarks to navigate. Hippocampal (HPC)-cortical dysfunction during sleep (important for memory consolidation) is a potential mechanism for memory impairments in AD. We previously found deficits in HPC-cortical coordination during sleep coinciding with VM impairments the next day. Some forms of 40 Hz stimulation seem to clear AD pathology in mice, and improve functional connectivity in AD patients. Thus, we implanted a recording array targeting parietal cortex (PC) and HPC to assess HPC-PC coordination, and an optical fiber targeting HPC for 40 Hz or sham optogenetic stimulation in 3xTg/PV cre mice. We assessed PC delta waves (DW) and HPC sharp wave ripples (SWRs). In sham mice, SWR-DW cross-correlations were reduced, similar to 3xTg-AD mice. In 40 Hz mice, this phase-locking was rescued, as was performance on the VM. However, rescued HPC-PC coupling no longer predicted performance as in NonTg animals. Instead, DWs and SWRs independently predicted performance in 40 Hz mice. Thus, 40 Hz stimulation of HPC rescued functional interactions in the HPC-PC network, and rescued impairments in spatial navigation, but did not rescue the correlation between HPC-PC coordination during sleep and learning and memory. Together this pattern of results could inform AD treatment timing by suggesting that despite applying 40 Hz stimulation before significant tau and amyloid aggregation, pathophysiological processes led to brain changes that were not fully reversed even though cognition was recovered.

Significance Statement

One of the earliest symptoms of Alzheimer's disease (AD) is getting lost in space or experiencing deficits in spatial navigation, which involve navigation computations as well as learning and memory. We investigated cross brain region interactions supporting memory formation as a potential causative factor of impaired spatial learning and memory in AD. To assess this relationship between AD pathophysiology, brain changes, and behavioral alterations, we used a targeted approach for clearing amyloid beta and tau to rescue functional interactions in the brain. This research strongly connects brain activity patterns during sleep to tau and amyloid accumulation, and will aid in understanding the mechanisms underlying cognitive dysfunction in AD. Furthermore, the results offer insight for improving early identification and treatment strategies.

Sleep-dependent decorrelation of hippocampal spatial representations

Neuronal ensembles are crucial for episodic memory and spatial mapping. Sleep, particularly non-REM (NREM), is vital for memory consolidation, as it triggers plasticity mechanisms through brain oscillations that reactivate neuronal ensembles. Here, we assessed their role in consolidating hippocampal spatial representations during sleep. We recorded hippocampus activity in rats performing a spatial object-place recognition (OPR) memory task, during encoding and retrieval periods, separated by intervening sleep. Successful OPR retrieval correlated with NREM duration, during which cortical oscillations decreased in power and density as well as neuronal spiking, suggesting global downregulation of network excitability. However, neurons encoding specific spatial locations (i.e., place cells) or objects during OPR showed stronger synchrony with brain oscillations compared to non-encoding neurons, and the stability of spatial representations decreased proportionally with NREM duration. Our findings suggest that NREM sleep may promote flexible remapping in hippocampal ensembles, potentially aiding memory consolidation and adaptation to novel spatial contexts.

Thalamocortical Dynamics during Rapid Eye Movement Sleep in the Mouse Somatosensory Pathway

Rapid eye movement (REM) sleep, also referred to as paradoxical sleep for the striking resemblance of its electroencephalogram (EEG) to the one observed in wakefulness, is characterized by the occurrence of transient events such as limb twitches or facial and rapid eye movements. Here, we investigated the local activity of the primary somatosensory or barrel cortex (S1) in naturally sleeping head-fixed male mice during REM. Through local field potential recordings, we uncovered local appearances of spindle waves in the barrel cortex during REM concomitant with strong delta power, challenging the view of a wakefulness-like activity in REM. We further performed extra- and intracellular recordings of thalamic cells in head-fixed mice. Our data show high-frequency thalamic bursts of spikes and subthreshold spindle oscillations in approximately half of the neurons of the ventral posterior medial nucleus which further confirmed the thalamic origin of local cortical spindles in S1 in REM. Cortical spindle oscillations were suppressed, while thalamus spike firing increased, associated with rapid mouse whisker movements and S1 cortical activity transitioned to an activated state. During REM, the sensory thalamus and barrel cortex therefore alternate between high (wake-like) and low (non-REM sleep-like) activation states, potentially providing a neuronal substrate for mnemonic processes occurring during this paradoxical sleep stage.

Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain

Slow-wave sleep (SWS), characterized by slow oscillations (SO, <1Hz) of alternating active and silent states in the thalamocortical network, is a primary brain state during Non-Rapid Eye Movement (NREM) sleep. In the last two decades, the traditional view of SWS as a global and uniform whole-brain state has been challenged by a growing body of evidence indicating that SO can be local and can coexist with wake-like activity. However, the understanding of how global and local SO emerges from micro-scale neuron dynamics and network connectivity remains unclear. We developed a multi-scale, biophysically realistic human whole-brain thalamocortical network model capable of transitioning between the awake state and slow-wave sleep, and we investigated the role of connectivity in the spatio-temporal dynamics of sleep SO. We found that the overall strength and a relative balance between long and short-range synaptic connections determined the network state. Importantly, for a range of synaptic strengths, the model demonstrated complex mixed SO states, where periods of synchronized global slow-wave activity were intermittent with the periods of asynchronous local slow-waves. Increase of the overall synaptic strength led to synchronized global SO, while decrease of synaptic connectivity produced only local slow-waves that would not propagate beyond local area. These results were compared to human data to validate probable models of biophysically realistic SO. The model producing mixed states provided the best match to the spatial coherence profile and the functional connectivity estimated from human subjects. These findings shed light on how the spatio-temporal properties of SO emerge from local and global cortical connectivity and provide a framework for further exploring the mechanisms and functions of SWS in health and disease.

Interrelations and functional roles of key oscillatory activities during daytime sleep in older adults

Certain neurophysiological characteristics of sleep, in particular slow oscillations (SOs), sleep spindles, and their temporal coupling, have been well characterised and associated with human memory abilities. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SOs, and their interaction with spindles have only recently been found to play a critical role in memory processing of rodents, through a competitive interaction between SO-spindle and delta-spindle coupling. However, human studies that comprehensively address delta wave interactions with spindles and SOs, as well as their functional role for memory are still lacking. Electroencephalographic data were acquired across three naps of 33 healthy older human participants (17 female) to investigate delta-spindle coupling and the interplay between delta- and SO-related activity. Additionally, we determined intra-individual stability of coupling measures and their potential link to the ability to form novel memories in a verbal memory task. Our results revealed weaker delta-spindle compared to SO-spindle coupling. Contrary to our initial hypothesis, we found no evidence for an opposing dependency between SO- and delta-related activities during non-rapid eye movement sleep. Moreover, the ratio between SO- and delta-nested spindles rather than SO-spindle and delta-spindle coupling measures by themselves predicted the ability to form novel memories best. In conclusion, our results do not confirm previous findings in rodents on competitive interactions between delta activity and SO-spindle coupling in older adults. However, they support the hypothesis that SO, delta wave, and spindle activity should be jointly considered when aiming to link sleep physiology and memory formation.

Modulation of neural spiking in motor cortex-cerebellar networks during sleep spindles

Sleep spindles appear to play an important role in learning new motor skills. Motor skill learning engages several regions in the brain with two important areas being the motor cortex (M1) and the cerebellum. However, the neurophysiological processes in these areas during sleep, especially how spindle oscillations affect local and cross-region spiking, are not fully understood. We recorded activity from the M1 and cerebellar cortex in 8 rats during spontaneous activity to investigate how sleep spindles in these regions are related to local spiking as well as cross-region spiking. We found that M1 firing was significantly changed during both M1 and cerebellum spindles and this spiking occurred at a preferred phase of the spindle. On average, M1 and cerebellum neurons showed most spiking at the M1 or cerebellum spindle peaks. These neurons also developed a preferential phase-locking to local or cross-area spindles with the greatest phase-locking value at spindle peaks; however, this preferential phase-locking wasn't significant for cerebellar neurons when compared to cerebellum spindles. Additionally, we found the percentage of task-modulated cells in the M1 and cerebellum that fired with non-uniform spike-phase distribution during M1/ cerebellum spindle peaks were greater in the rats that learned a reach-to-grasp motor task robustly. Finally, we found that spindle-band LFP coherence (for M1 and cerebellum LFPs) showed a positive correlation with success rate in the motor task. These findings support the idea that sleep spindles in both the M1 and cerebellum recruit neurons that participate in the awake task to support motor memory consolidation.Significance Statement Neural processing during sleep spindles is linked to memory consolidation. However, little is known about sleep activity in the cerebellum and whether cerebellum spindles can affect spiking activity in local or distant areas. We report the effect of sleep spindles on neuron activity in the M1 and cerebellum-specifically their firing rate and phase-locking to spindle oscillations. Our results indicate that awake practice neuronal activity is tempered during local M1 and cerebellum spindles, and during cross-region spindles, which may support motor skill learning. We describe spiking dynamics in motor networks spindle oscillations that may aid in the learning of skills. Our results support the sleep reactivation hypothesis and suggest that awake M1 activity may be reactivated during cerebellum spindles.

Cortico-cerebellar coordination facilitates neuroprosthetic control

Temporally coordinated neural activity is central to nervous system function and purposeful behavior. Still, there is a paucity of evidence demonstrating how this coordinated activity within cortical and subcortical regions governs behavior. We investigated this between the primary motor (M1) and contralateral cerebellar cortex as rats learned a neuroprosthetic/brain-machine interface (BMI) task. In neuroprosthetic task, actuator movements are causally linked to M1 "direct" neurons that drive the decoder for successful task execution. However, it is unknown how task-related M1 activity interacts with the cerebellum. We observed a notable 3 to 6 hertz coherence that emerged between these regions' local field potentials (LFPs) with learning that also modulated task-related spiking. We identified robust task-related indirect modulation in the cerebellum, which developed a preferential relationship with M1 task-related activity. Inhibiting cerebellar cortical and deep nuclei activity through optogenetics led to performance impairments in M1-driven neuroprosthetic control. Together, these results demonstrate that cerebellar influence is necessary for M1-driven neuroprosthetic control.

Spindle oscillations in communicating axons within a reconstituted hippocampal formation are strongest in CA3 without thalamus

Spindle-shaped waves of oscillations emerge in EEG scalp recordings during human and rodent non-REM sleep. The association of these 10-16 Hz oscillations with events during prior wakefulness suggests a role in memory consolidation. Human and rodent depth electrodes in the brain record strong spindles throughout the cortex and hippocampus, with possible origins in the thalamus. However, the source and targets of the spindle oscillations from the hippocampus are unclear. Here, we employed an in vitro reconstruction of four subregions of the hippocampal formation with separate microfluidic tunnels for single axon communication between subregions assembled on top of a microelectrode array. We recorded spontaneous 400-1000 ms long spindle waves at 10-16 Hz in single axons passing between subregions as well as from individual neurons in those subregions. Spindles were nested within slow waves. The highest amplitudes and most frequent occurrence suggest origins in CA3 neurons that send feed-forward axons into CA1 and feedback axons into DG. Spindles had 50-70% slower conduction velocities than spikes and were not phase-locked to spikes suggesting that spindle mechanisms are independent of action potentials. Therefore, consolidation of declarative-cognitive memories in the hippocampus may be separate from the more easily accessible consolidation of memories related to thalamic motor function.

Neuroligin-2 shapes individual slow waves during slow-wave sleep and the response to sleep deprivation in mice

BACKGROUND

Sleep disturbances are a common comorbidity to most neurodevelopmental disorders and tend to worsen disease symptomatology. It is thus crucial to understand mechanisms underlying sleep disturbances to improve patients' quality of life. Neuroligin-2 (NLGN2) is a synaptic adhesion protein regulating GABAergic transmission. It has been linked to autism spectrum disorders and schizophrenia in humans, and deregulations of its expression were shown to cause epileptic-like hypersynchronized cerebral activity in rodents. Importantly, the absence of Nlgn2 (knockout: KO) was previously shown to alter sleep-wake duration and quality in mice, notably increasing slow-wave sleep (SWS) delta activity (1-4 Hz) and altering its 24-h dynamics. This type of brain oscillation is involved in memory consolidation, and is also a marker of homeostatic sleep pressure. Sleep deprivation (SD) is notably known to impair cognition and the physiological response to sleep loss involves GABAergic transmission.

METHODS

Using electrocorticographic (ECoG) recordings, we here first aimed to verify how individual slow wave (SW; 0.5-4 Hz) density and properties (e.g., amplitude, slope, frequency) contribute to the higher SWS delta activity and altered 24-h dynamics observed in Nlgn2 KO mice. We further investigated the response of these animals to SD. Finally, we tested whether sleep loss affects the gene expression of Nlgn2 and related GABAergic transcripts in the cerebral cortex of wild-type mice using RNA sequencing.

RESULTS

Our results show that Nlgn2 KO mice have both greater SW amplitude and density, and that SW density is the main property contributing to the altered 24-h dynamics. We also found the absence of Nlgn2 to accelerate paradoxical sleep recovery following SD, together with profound alterations in ECoG activity across vigilance states. Sleep loss, however, did not modify the 24-h distribution of the hypersynchronized ECoG events observed in these mice. Finally, RNA sequencing confirmed an overall decrease in cortical expression of Nlgn2 and related GABAergic transcripts following SD in wild-type mice.

CONCLUSIONS

This work brings further insight into potential mechanisms of sleep duration and quality deregulation in neurodevelopmental disorders, notably involving NLGN2 and GABAergic neurotransmission.

Coupled sleep rhythms for memory consolidation

How do passing moments turn into lasting memories? Sheltered from external tasks and distractions, sleep constitutes an optimal state for the brain to reprocess and consolidate previous experiences. Recent work suggests that consolidation is governed by the intricate interaction of slow oscillations (SOs), spindles, and ripples - electrophysiological sleep rhythms that orchestrate neuronal processing and communication within and across memory circuits. This review describes how sequential SO-spindle-ripple coupling provides a temporally and spatially fine-tuned mechanism to selectively strengthen target memories across hippocampal and cortical networks. Coupled sleep rhythms might be harnessed not only to enhance overnight memory retention, but also to combat memory decline associated with healthy ageing and neurodegenerative diseases.

Overnight neuronal plasticity and adaptation to emotional distress

Expressions such as 'sleep on it' refer to the resolution of distressing experiences across a night of sound sleep. Sleep is an active state during which the brain reorganizes the synaptic connections that form memories. This Perspective proposes a model of how sleep modifies emotional memory traces. Sleep-dependent reorganization occurs through neurophysiological events in neurochemical contexts that determine the fates of synapses to grow, to survive or to be pruned. We discuss how low levels of acetylcholine during non-rapid eye movement sleep and low levels of noradrenaline during rapid eye movement sleep provide a unique window of opportunity for plasticity in neuronal representations of emotional memories that resolves the associated distress. We integrate sleep-facilitated adaptation over three levels: experience and behaviour, neuronal circuits, and synaptic events. The model generates testable hypotheses for how failed sleep-dependent adaptation to emotional distress is key to mental disorders, notably disorders of anxiety, depression and post-traumatic stress with the common aetiology of insomnia.

Electrophysiological Properties of the Medial Mammillary Bodies across the Sleep-Wake Cycle

The medial mammillary bodies (MBs) play an important role in the formation of spatial memories; their dense inputs from hippocampal and brainstem regions makes them well placed to integrate movement-related and spatial information, which is then extended to the anterior thalamic nuclei and beyond to the cortex. While the anatomical connectivity of the medial MBs has been well studied, much less is known about their physiological properties, particularly in freely moving animals. We therefore carried out a comprehensive characterization of medial MB electrophysiology across arousal states by concurrently recording from the medial MB and the CA1 field of the hippocampus in male rats. In agreement with previous studies, we found medial MB neurons to have firing rates modulated by running speed and angular head velocity, as well as theta-entrained firing. We extended the characterization of MB neuron electrophysiology in three key ways: (1) we identified a subset of neurons (25%) that exhibit dominant bursting activity; (2) we showed that ∼30% of theta-entrained neurons exhibit robust theta cycle skipping, a firing characteristic that implicates them in a network for prospective coding of position; and (3) a considerable proportion of medial MB units showed sharp-wave ripple (SWR) responsive firing (∼37%). The functional heterogeneity of MB electrophysiology reinforces their role as an integrative node for mnemonic processing and identifies potential roles for the MBs in memory consolidation through propagation of SWR-responsive activity to the anterior thalamus and prospective coding in the form of theta cycle skipping.

Modulatory Effect of Low-Intensity Transcranial Ultrasound Stimulation on Behaviour and Neural Oscillation in Mouse Models of Alzheimer's Disease

Transcranial ultrasound stimulation (TUS) is a noninvasive brain neuromodulation technique. The application of TUS for Alzheimer's disease (AD) therapy has not been widely studied. In this study, a long-term course (28 days) of TUS was used to stimulate the hippocampus of APP/PS1 mice. We examined the modulatory effect of TUS on behavior and neural oscillation in AD mice. We found that TUS can 1) improve the learning and memory abilities of AD mice; 2) reduce the phase-amplitude coupling of delta-epsilon, delta-gamma and theta-gamma frequency bands of local field potential, and increase the relative power of epsilon frequency bands in AD mice; 3) reduce the spike firing rate of interneurons and inhibit the phase-locked angle deflection between the theta frequency bands and the spikes of the two types of neurons that develops with the progression of the disease in AD mice. In summary, we demonstrate that TUS could effectively improve cognitive behavior and modulate neural oscillation with AD.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults

Cross-frequency coupling (CFC) between brain oscillations during non-rapid-eye-movement (NREM) sleep (e.g. slow oscillations [SO] and spindles) may be a neural mechanism of overnight memory consolidation. Declines in CFC across the lifespan might accompany coinciding memory problems with ageing. However, there are few reports of CFC changes during sleep after learning in older adults, controlling for baseline effects. Our objective was to examine NREM CFC in healthy older adults, with an emphasis on spindle activity and SOs from frontal electroencephalogram (EEG), during a learning night after a declarative learning task, as compared to a baseline night without learning. Twenty-five older adults (M [SD] age = 69.12 [5.53] years; 64% female) completed a two-night study, with a pre- and post-sleep word-pair associates task completed on the second night. SO-spindle coupling strength and a measure of coupling phase distance from the SO up-state were both examined for between-night differences and associations with memory consolidation. Coupling strength and phase distance from the up-state peak were both stable between nights. Change in coupling strength between nights was not associated with memory consolidation, but a shift in coupling phase towards (vs. away from) the up-state peak after learning predicted better memory consolidation. Also, an exploratory interaction model suggested that associations between coupling phase closer to the up-state peak and memory consolidation may be moderated by higher (vs. lower) coupling strength. This study supports a role for NREM CFC in sleep-related memory consolidation in older adults.

Sleep restores an optimal computational regime in cortical networks

Sleep is assumed to subserve homeostatic processes in the brain; however, the set point around which sleep tunes circuit computations is unknown. Slow-wave activity (SWA) is commonly used to reflect the homeostatic aspect of sleep; although it can indicate sleep pressure, it does not explain why animals need sleep. This study aimed to assess whether criticality may be the computational set point of sleep. By recording cortical neuron activity continuously for 10-14 d in freely behaving rats, we show that normal waking experience progressively disrupts criticality and that sleep functions to restore critical dynamics. Criticality is perturbed in a context-dependent manner, and waking experience is causal in driving these effects. The degree of deviation from criticality predicts future sleep/wake behavior more accurately than SWA, behavioral history or other neural measures. Our results demonstrate that perturbation and recovery of criticality is a network homeostatic mechanism consistent with the core, restorative function of sleep.

A pilot time-in-bed restriction intervention behaviorally enhances slow-wave activity in older adults

Introduction

Identifying intervention methods that target sleep characteristics involved in memory processing is a priority for the field of cognitive aging. Older adults with greater sleep efficiency and non-rapid eye movement slow-wave activity (SWA) (0.5-4 Hz electroencephalographic activity) tend to exhibit better memory and cognitive abilities. Paradoxically, long total sleep times are consistently associated with poorer cognition in older adults. Thus, maximizing sleep efficiency and SWA may be a priority relative to increasing mere total sleep time. As clinical behavioral sleep treatments do not consistently enhance SWA, and propensity for SWA increases with time spent awake, we examined with a proof-of concept pilot intervention whether a greater dose of time-in-bed (TiB) restriction (75% of habitual TiB) would increase both sleep efficiency and SWA in older adults with difficulties staying asleep without impairing memory performance.

Methods

Participants were adults ages 55-80 with diary-reported sleep efficiency <90% and wake after sleep onset (WASO) >20 min. Sleep diary, actigraphy, polysomnography (PSG), and paired associate memory acquisition and retention were assessed before and after a week-long TiB restriction intervention (n = 30). TiB was restricted to 75% of diary-reported habitual TiB. A comparison group of n = 5 participants repeated assessments while following their usual sleep schedule to obtain preliminary estimates of effect sizes associated with repeated testing.

Results

Subjective and objective sleep measures robustly improved in the TiB restriction group for sleep quality, sleep depth, sleep efficiency and WASO, at the expense of TiB and time spent in N1 and N2 sleep. As hypothesized, SWA increased robustly with TiB restriction across the 0.5-4 Hz range, as well as subjective sleep depth, subjective and objective WASO. Despite increases in sleepiness ratings, no impairments were found in memory acquisition or retention.

Conclusion

A TiB restriction dose equivalent to 75% of habitual TiB robustly increased sleep continuity and SWA in older adults with sleep maintenance difficulties, without impairing memory performance. These findings may inform long-term behavioral SWA enhancement interventions aimed at improving memory performance and risk for cognitive impairments.

Centralising a loss of consciousness to the central medial thalamus

Although a role of the thalamus in different arousal and awareness states is well established, there is a surprising lack of knowledge on subregional specificity within this complex, multinucleated structure of the diencephalon. In their recent paper 'Extrasynaptic GABA-A receptors in central medial thalamus mediate anaesthesia in rats', Muheyati et al. evaluated whether GABAA receptors expressed in the central medial (CM), paraventricular (PV) or lateral mediodorsal (MD) nuclei of the thalamus contribute to the loss of the righting reflex (LORR) in rats. Deficits in this reflex have previously been interpreted as a surrogate marker of altered levels of consciousness. Using a range of convergent techniques, the authors report the novel finding that delta subunit-expressing GABAA receptors in the CM contribute to distinct awareness states. This important discovery implicates a tonic GABAA-mediated conductance in the CM that may be relevant for minimally conscious states and other conditions of altered awareness.