The sleep slow oscillation as a traveling wave

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.

Cerebral Gray Matter May Not Explain Sleep Slow-Wave Characteristics after Severe Brain Injury

Sleep slow waves are the hallmark of deeper non-rapid eye movement sleep. It is generally assumed that gray matter properties predict slow-wave density, morphology, and spectral power in healthy adults. Here, we tested the association between gray matter volume (GMV) and slow-wave characteristics in 27 patients with moderate-to-severe traumatic brain injury (TBI, 32.0 ± 12.2 years old, eight women) and compared that with 32 healthy controls (29.2 ± 11.5 years old, nine women). Participants underwent overnight polysomnography and cerebral MRI with a 3 Tesla scanner. A whole-brain voxel-wise analysis was performed to compare GMV between groups. Slow-wave density, morphology, and spectral power (0.4-6 Hz) were computed, and GMV was extracted from the thalamus, cingulate, insula, precuneus, and orbitofrontal cortex to test the relationship between slow waves and gray matter in regions implicated in the generation and/or propagation of slow waves. Compared with controls, TBI patients had significantly lower frontal and temporal GMV and exhibited a subtle decrease in slow-wave frequency. Moreover, higher GMV in the orbitofrontal cortex, insula, cingulate cortex, and precuneus was associated with higher slow-wave frequency and slope, but only in healthy controls. Higher orbitofrontal GMV was also associated with higher slow-wave density in healthy participants. While we observed the expected associations between GMV and slow-wave characteristics in healthy controls, no such associations were observed in the TBI group despite lower GMV. This finding challenges the presumed role of GMV in slow-wave generation and morphology.

Targeted memory reactivation to augment treatment in post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is a psychiatric disorder with traumatic memories at its core. Post-treatment sleep may offer a unique time window to increase therapeutic efficacy through consolidation of therapeutically modified traumatic memories. Targeted memory reactivation (TMR) enhances memory consolidation by presenting reminder cues (e.g., sounds associated with a memory) during sleep. Here, we applied TMR in PTSD patients to strengthen therapeutic memories during sleep after one treatment session with eye movement desensitization and reprocessing (EMDR). PTSD patients received either slow oscillation (SO) phase-targeted TMR, using modeling-based closed-loop neurostimulation (M-CLNS) with EMDR clicks as a reactivation cue (n = 17), or sham stimulation (n = 16). Effects of TMR on sleep were assessed through high-density polysomnography. Effects on treatment outcome were assessed through subjective, autonomic, and fMRI responses to script-driven imagery (SDI) of the targeted traumatic memory and overall PTSD symptom level. Compared to sham stimulation, TMR led to stimulus-locked increases in SO and spindle dynamics, which correlated positively with PTSD symptom reduction in the TMR group. Given the role of SOs and spindles in memory consolidation, these findings suggest that TMR may have strengthened the consolidation of the EMDR-treatment memory. Clinically, TMR vs. sham stimulation resulted in a larger reduction of avoidance level during SDI. TMR did not disturb sleep or trigger nightmares. Together, these data provide first proof of principle that TMR may be a safe and viable future treatment augmentation strategy for PTSD. The required follow-up studies may implement multi-night TMR or TMR during REM sleep to further establish the clinical effect of TMR for traumatic memories.

BDNF-TrkB signaling orchestrates the buildup process of local sleep

Sleep debt accumulates during wakefulness, leading to increased slow wave activity (SWA) during sleep, an encephalographic marker for sleep need. The use-dependent demands of prior wakefulness increase sleep SWA locally. However, the circuitry and molecular identity of this "local sleep" remain unclear. Using pharmacology and optogenetic perturbations together with transcriptomics, we find that cortical brain-derived neurotrophic factor (BDNF) regulates SWA via the activation of tyrosine kinase B (TrkB) receptor and cAMP-response element-binding protein (CREB). We map BDNF/TrkB-induced sleep SWA to layer 5 (L5) pyramidal neurons of the cortex, independent of neuronal firing per se. Using mathematical modeling, we here propose a model of how BDNF's effects on synaptic strength can increase SWA in ways not achieved through increased firing alone. Proteomic analysis further reveals that TrkB activation enriches ubiquitin and proteasome subunits. Together, our study reveals that local SWA control is mediated by BDNF-TrkB-CREB signaling in L5 excitatory cortical neurons.

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.

Reactivating cue approached positive personality traits during sleep promotes positive self-referential processing

People preferentially endorse positive personality traits as more self-descriptive than negative ones, a positivity self-referential bias. Here, we investigated how to enhance positive self-referential processing, integrating wakeful cue-approach training task (CAT) and sleep-based targeted memory reactivation (TMR). In the CAT, participants gave speeded motor responses to cued positive personality traits. In a subsequent nap, we unobtrusively re-played half of the trained positive traits during slow-wave sleep (TMR). Upon awakening, CAT+TMR facilitated participants' speed in endorsing positive traits in immediate tests, and rendered participants endorse more positive traits as self-descriptive after one week. Notably, these enhancements were associated with the directionality of cue-related 1-4 Hz slow traveling waves (STW) that propagate across brain regions. Specifically, anterior-to-posterior backward STW was positively associated with these benefits, whereas forward STW showed negative associations. These findings demonstrate the potential benefits of integrated wakeful cue-approach training and sleep-based memory reactivation in strengthening positive self-referential processing.

Amyloid beta-independent sleep markers associated with early regional tau burden and cortical thinning

INTRODUCTION

Sleep is crucial for memory consolidation and the clearance of toxic proteins associated with Alzheimer's disease (AD). We examined the association between sleep characteristics and imaging biomarkers of early amyloid beta (Aβ) and tau pathology as well as neurodegeneration in brain regions known to be affected in the incipient stages of AD.

METHODS

Thirty-nine cognitively unimpaired (CU) participants of the Harvard Aging Brain Study underwent at-home polysomnography as well as tau positron emission tomography (flortaucipir-PET), amyloid PET (Pittsburgh compound B [PiB]-PET), and magnetic resonance imaging-derived assessment of cortical thickness (CT).

RESULTS

Increased N1 sleep was associated with a higher tau PET signal (β = 0.009, p = 0.001) and lower CT in the temporal composite region of interest (β = -0.017, p = 0.007). Decreased slow-wave sleep (SWS) was associated with higher tau burden in the temporal composite (β = -0.008, p = 0.005) and lower CT (β = 0.008, p = 0.002), even after controlling for global PiB-PET.

DISCUSSION

In CU older adults, lower SWS and higher N1 sleep were associated with higher tau burden and lower CT in brain regions associated with early tau deposition and vulnerable to AD-related neurodegeneration through mechanisms dissociable from amyloid deposition.

Highlights

We report the results of an observational study, which leveraged -a well-characterized cohort of healthy aging (Harvard Aging Brain Study) by adding in-home full polysomnograms.By adding at-home polysomnograms to this unique and deeply phenotyped cohort, we examined variations in sleep architecture that are associated with Alzheimer's disease (AD) pathologic changes.Our results confirmed the association of sleep changes with early tau and cortical neurodegenerative changes that were independent of amyloid.The results will be of importance in monitoring sleep-related variations in relation to the natural history of AD pathology and in designing sleep-focused clinical trials.

Subjective sleep more predictive of global cognitive function than objective sleep in older adults: A specification curve analysis

OBJECTIVES

Sleep is associated with cognitive function in older adults. In the current study, we examined this relationship from subjective and objective perspectives, and determined the robustness and dimensional specificity of the associations using a comprehensive modelling approach.

METHODS

Multiple dimensions of subjective (sleep quality and daytime sleepiness) and objective sleep (sleep stages, sleep parameters, sleep spindles, and slow oscillations), as well as subjectively reported and objectively measured cognitive function were collected from 55 older adults. Specification curve analysis was used to examine the robustness of correlations for the effects of sleep on cognitive function.

RESULTS

Robust associations were found between sleep and objectively measured cognitive function, but not with subjective cognitive complaints. In addition, subjective sleep showed robust and consistent associations with global cognitive function, whereas objective sleep showed a more domain-specific association with episodic memory. Specifically, subjective sleep quality and daytime sleepiness correlated with global cognitive function, and objective sleep parameters correlated with episodic memory.

CONCLUSIONS

Overall, associations between sleep and cognitive function in older adults depend on how they are measured and which specific dimensions of sleep and domains of cognitive function are considered. It highlights the importance of focusing on specific associations to ameliorate the detrimental effects of sleep disturbance on cognitive function in later life.

NREM Slow-Wave Activity in Adolescents Is Differentially Associated With ADHD Levels and Normalized by Pharmacological Treatment

BACKGROUND

A compelling hypothesis about attention-deficit/hyperactivity disorder (ADHD) etiopathogenesis is that the ADHD phenotype reflects a delay in cortical maturation. Slow-wave activity (SWA) of non-rapid eye movement (NREM) sleep electroencephalogram (EEG) is an electrophysiological index of sleep intensity reflecting cortical maturation. Available data on ADHD and SWA are conflicting, and developmental differences, or the effect of pharmacological treatment, are relatively unknown.

METHODS

We examined, in samples (Mage = 16.4, SD = 1.2), of ever-medicated adolescents at risk for ADHD (n = 18; 72% boys), medication-naïve adolescents at risk for ADHD (n = 15, 67% boys), and adolescents not at risk for ADHD (n = 31, 61% boys) matched for chronological age and controlling for non-ADHD pharmacotherapy, whether ADHD pharmacotherapy modulates the association between NREM SWA and ADHD risk in home sleep.

RESULTS

Findings indicated medication-naïve adolescents at risk for ADHD exhibited greater first sleep cycle and entire night NREM SWA than both ever-medicated adolescents at risk for ADHD and adolescents not at risk for ADHD and no difference between ever-medicated, at-risk adolescents, and not at-risk adolescents.

CONCLUSIONS

Results support atypical cortical maturation in medication-naïve adolescents at risk for ADHD that appears to be normalized by ADHD pharmacotherapy in ever-medicated adolescents at risk for ADHD. Greater NREM SWA may reflect a compensatory mechanism in middle-later adolescents at risk for ADHD that normalizes an earlier occurring developmental delay.

A flexible and dissolving traditional Chinese medicine microneedle patch for sleep-aid intervention

About a quarter of the world's population suffers from insomnia, and the number of the insomniacs is gradually increasing. However, the current drug therapy and non-drug therapy sleep-aid methods have certain limitations. In general, the sleep-aid effect of drug therapy is better than that of Non-drug therapy, but western medicine may lead to some side effects and drug abuse. Although the side effects of Chinese Herbal Medicine (CHM) are relatively small, making the herbal decoction is complex and time-consuming. Therefore, exploring a novel sleep-aid method is very significant. In this paper, a flexible and dissolving Traditional Chinese Medicine (TCM) microneedle patch is proposed for sleep-aid intervention. The TCM microneedle patch is a micrometer-scale intrusive object, and the herbal extracts are carried by the patch. The materials, design method, and fabrication process of the microneedle patch have been described in detail. Besides, the mechanical characteristics of the microneedle patch, sleep-aid effect evaluation method, and experimental scheme have been presented. Three microneedle tips with radii of 5 μm, 15 μm, and 22 μm are selected for simulation analysis. Abaqus simulation results indicate that the smaller the radius of the microneedle tip, the smaller the piercing force. Considering that the microneedle should easily penetrate the skin without buckling, that is, the piercing force should be larger than the buckling force, thus 15 μm, instead of 5 μm or 22 μm, is more suitable to be adopted as the radius of the microneedle tip. For the microneedle with the radius of 15 μm, the piercing force is 0.033 N, and the difference between the piercing force and buckling force is 0.036 N. Experimental results demonstrate that the fracture force of the microneedle is about 0.29 N, which is far larger than the piercing force and buckling force. The single-lead EEG signals of the frontal lobe are used to evaluate the sleep-aid effect of the TCM microneedle patch. After sleep-aid intervention on the Anmian and Yintang acupoints using the patches, for most subjects, the ratios of the low-frequency brain wave energies to the high-frequency brain wave energies are increased obviously, indicating that the proposed sleep-aid method is effective.

Intracortical mechanisms of single pulse electrical stimulation (SPES) evoked excitations and inhibitions in humans

Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.

Brain states as wave-like motifs

There is ample evidence of wave-like activity in the brain at multiple scales and levels. This emerging literature supports the broader adoption of a wave perspective of brain activity. Specifically, a brain state can be described as a set of recurring, sequential patterns of propagating brain activity, namely a wave. We examine a collective body of experimental work investigating wave-like properties. Based on these works, we consider brain states as waves using a scale-agnostic framework across time and space. Emphasis is placed on the sequentiality and periodicity associated with brain activity. We conclude by discussing the implications, prospects, and experimental opportunities of this framework.

The direction of theta and alpha travelling waves modulates human memory processing

To support a range of behaviours, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a travelling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions. Although travelling waves are present across the brain in various species, their potential functional relevance has remained unknown. Here, using rare direct human brain recordings, we demonstrate a distinct functional role for travelling waves of theta- and alpha-band (2-13 Hz) oscillations in the cortex. Travelling waves propagate in different directions during separate cognitive processes. In episodic memory, travelling waves tended to propagate in a posterior-to-anterior direction during successful memory encoding and in an anterior-to-posterior direction during recall. Because travelling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain in different directions for separate behaviours. More broadly, our results suggest a fundamental role for travelling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behaviour.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

Neural assemblies coordinated by cortical waves are associated with waking and hallucinatory brain states

The relationship between sensory stimuli and perceptions is brain-state dependent: in wakefulness, suprathreshold stimuli evoke perceptions; under anesthesia, perceptions are abolished; and during dreaming and in dissociated states, percepts are internally generated. Here, we exploit this state dependence to identify brain activity associated with internally generated or stimulus-evoked perceptions. In awake mice, visual stimuli phase reset spontaneous cortical waves to elicit 3-6 Hz feedback traveling waves. These stimulus-evoked waves traverse the cortex and entrain visual and parietal neurons. Under anesthesia as well as during ketamine-induced dissociation, visual stimuli do not disrupt spontaneous waves. Uniquely, in the dissociated state, spontaneous waves traverse the cortex caudally and entrain visual and parietal neurons, akin to stimulus-evoked waves in wakefulness. Thus, coordinated neuronal assemblies orchestrated by traveling cortical waves emerge in states in which perception can manifest. The awake state is privileged in that this coordination is reliably elicited by external visual stimuli.

Multimodal neuroimaging correlates of spectral power in NREM sleep delta sub-bands in cognitively unimpaired older adults

STUDY OBJECTIVES

In aging, reduced delta power (0.5-4 Hz) during N2 and N3 sleep has been associated with gray matter (GM) atrophy and hypometabolism within frontal regions. Some studies have also reported associations between N2 and N3 sleep delta power in specific sub-bands and amyloid pathology. Our objective was to better understand the relationships between spectral power in delta sub-bands during N2-N3 sleep and brain integrity using multimodal neuroimaging.

METHODS

In-home polysomnography was performed in 127 cognitively unimpaired older adults (mean age ± SD: 69.0 ± 3.8 years). N2-N3 sleep EEG power was calculated in delta (0.5-4 Hz), slow delta (0.5-1 Hz), and fast delta (1-4 Hz) frequency bands. Participants also underwent magnetic resonance imaging and Florbetapir-PET (early and late acquisitions) scans to assess GM volume, brain perfusion, and amyloid burden. Amyloid accumulation over ~21 months was also quantified.

RESULTS

Higher delta power was associated with higher GM volume mainly in fronto-cingular regions. Specifically, slow delta power was positively correlated with GM volume and perfusion in these regions, while the inverse association was observed with fast delta power. Delta power was neither associated with amyloid burden at baseline nor its accumulation over time, whatever the frequency band considered.

CONCLUSIONS

Our results show that slow delta is particularly associated with preserved brain structure, and highlight the importance of analyzing delta power sub-bands to better understand the associations between delta power and brain integrity. Further longitudinal investigations with long follow-ups are needed to disentangle the associations among sleep, amyloid pathology, and dementia risk in older populations.

CLINICAL TRIAL INFORMATION

Name: Study in Cognitively Intact Seniors Aiming to Assess the Effects of Meditation Training (Age-Well). URL: https://clinicaltrials.gov/ct2/show/NCT02977819?term=Age-Well&draw=2&rank=1. See STROBE_statement_AGEWELL in supplemental materials.

REGISTRATION

EudraCT: 2016-002441-36; IDRCB: 2016-A01767-44; ClinicalTrials.gov Identifier: NCT02977819.

Adenosinergic Modulation of Layer 6 Microcircuitry in the Medial Prefrontal Cortex Is Specific to Presynaptic Cell Type

Adenosinergic modulation in the PFC is recognized for its involvement in various behavioral aspects including sleep homoeostasis, decision-making, spatial working memory and anxiety. While the principal cells of layer 6 (L6) exhibit a significant morphological diversity, the detailed cell-specific regulatory mechanisms of adenosine in L6 remain unexplored. Here, we quantitatively analyzed the morphological and electrophysiological parameters of L6 neurons in the rat medial prefrontal cortex (mPFC) using whole-cell recordings combined with morphological reconstructions. We were able to identify two different morphological categories of excitatory neurons in the mPFC of both juvenile and young adult rats with both sexes. These categories were characterized by a leading dendrite that was oriented either upright (toward the pial surface) or inverted (toward the white matter). These two excitatory neuron subtypes exhibited different electrophysiological and synaptic properties. Adenosine at a concentration of 30 µM indiscriminately suppressed connections with either an upright or an inverted presynaptic excitatory neuron. However, using lower concentrations of adenosine (10 µM) revealed that synapses originating from L6 upright neurons have a higher sensitivity to adenosine-induced inhibition of synaptic release. Adenosine receptor activation causes a reduction in the probability of presynaptic neurotransmitter release that could be abolished by specifically blocking A1 adenosine receptors (A1ARs) using 8-cyclopentyltheophylline (CPT). Our results demonstrate a differential expression level of A1ARs at presynaptic sites of two functionally and morphologically distinct subpopulations of L6 principal neurons, suggesting the intricate functional role of adenosine in neuronal signaling in the brain.

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.

Sleepiness and the transition from wakefulness to sleep

The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.

Proof-of-concept evidence for high-density EEG investigation of sleep slow wave traveling in First-Episode Psychosis

Schizophrenia is thought to reflect aberrant connectivity within cortico-cortical and reentrant thalamo-cortical loops, which physiologically integrate and coordinate the function of multiple cortical and subcortical structures. Despite extensive research, reliable biomarkers of such "dys-connectivity" remain to be identified at the onset of psychosis, and before exposure to antipsychotic drugs. Because slow waves travel across the brain during sleep, they represent an ideal paradigm to study pathological conditions affecting brain connectivity. Here, we provide proof-of-concept evidence for a novel approach to investigate slow wave traveling properties in First-Episode Psychosis (FEP) with high-density electroencephalography (EEG). Whole-night sleep recordings of 5 drug-naïve FEP and 5 age- and gender-matched healthy control subjects were obtained with a 256-channel EEG system. One patient was re-recorded after 6 months and 3 years of continuous clozapine treatment. Slow wave detection and traveling properties were obtained with an open-source toolbox. Slow wave density and slow wave traveled distance (measured as the line of longest displacement) were significantly lower in patients (p < 0.05). In the patient who was tested longitudinally during effective clozapine treatment, slow wave density normalized, while traveling distance only partially recovered. These preliminary findings suggest that slow wave traveling could be employed in larger samples to detect cortical "dys-connectivity" at psychosis onset.

Sequentially activated discrete modules appear as traveling waves in neuronal measurements with limited spatiotemporal sampling

Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations.

Neuronal dynamics direct cerebrospinal fluid perfusion and brain clearance

The accumulation of metabolic waste is a leading cause of numerous neurological disorders, yet we still have only limited knowledge of how the brain performs self-cleansing. Here we demonstrate that neural networks synchronize individual action potentials to create large-amplitude, rhythmic and self-perpetuating ionic waves in the interstitial fluid of the brain. These waves are a plausible mechanism to explain the correlated potentiation of the glymphatic flow1,2 through the brain parenchyma. Chemogenetic flattening of these high-energy ionic waves largely impeded cerebrospinal fluid infiltration into and clearance of molecules from the brain parenchyma. Notably, synthesized waves generated through transcranial optogenetic stimulation substantially potentiated cerebrospinal fluid-to-interstitial fluid perfusion. Our study demonstrates that neurons serve as master organizers for brain clearance. This fundamental principle introduces a new theoretical framework for the functioning of macroscopic brain waves.

Neural complexity and the spectral slope characterise auditory processing in wakefulness and sleep

Auditory processing and the complexity of neural activity can both indicate residual consciousness levels and differentiate states of arousal. However, how measures of neural signal complexity manifest in neural activity following environmental stimulation and, more generally, how the electrophysiological characteristics of auditory responses change in states of reduced consciousness remain under-explored. Here, we tested the hypothesis that measures of neural complexity and the spectral slope would discriminate stages of sleep and wakefulness not only in baseline electroencephalography (EEG) activity but also in EEG signals following auditory stimulation. High-density EEG was recorded in 21 participants to determine the spatial relationship between these measures and between EEG recorded pre- and post-auditory stimulation. Results showed that the complexity and the spectral slope in the 2-20 Hz range discriminated between sleep stages and had a high correlation in sleep. In wakefulness, complexity was strongly correlated to the 20-40 Hz spectral slope. Auditory stimulation resulted in reduced complexity in sleep compared to the pre-stimulation EEG activity and modulated the spectral slope in wakefulness. These findings confirm our hypothesis that electrophysiological markers of arousal are sensitive to sleep/wake states in EEG activity during baseline and following auditory stimulation. Our results have direct applications to studies using auditory stimulation to probe neural functions in states of reduced consciousness.

Cardio-audio synchronization elicits neural and cardiac surprise responses in human wakefulness and sleep

The human brain can encode auditory regularities with fixed sound-to-sound intervals and with sound onsets locked to cardiac inputs. Here, we investigated auditory and cardio-audio regularity encoding during sleep, when bodily and environmental stimulus processing may be altered. Using electroencephalography and electrocardiography in healthy volunteers (N = 26) during wakefulness and sleep, we measured the response to unexpected sound omissions within three regularity conditions: synchronous, where sound and heartbeat are temporally coupled, isochronous, with fixed sound-to-sound intervals, and a control condition without regularity. Cardio-audio regularity encoding manifested as a heartbeat deceleration upon omissions across vigilance states. The synchronous and isochronous sequences induced a modulation of the omission-evoked neural response in wakefulness and N2 sleep, the former accompanied by background oscillatory activity reorganization. The violation of cardio-audio and auditory regularity elicits cardiac and neural responses across vigilance states, laying the ground for similar investigations in altered consciousness states such as coma and anaesthesia.

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

Background

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

Objective/Hypothesis

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

Methods

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

Results

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

Conclusion

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

Linking brain structure, cognition, and sleep: insights from clinical data

STUDY OBJECTIVES

To use relatively noisy routinely collected clinical data (brain magnetic resonance imaging (MRI) data, clinical polysomnography (PSG) recordings, and neuropsychological testing), to investigate hypothesis-driven and data-driven relationships between brain physiology, structure, and cognition.

METHODS

We analyzed data from patients with clinical PSG, brain MRI, and neuropsychological evaluations. SynthSeg, a neural network-based tool, provided high-quality segmentations despite noise. A priori hypotheses explored associations between brain function (measured by PSG) and brain structure (measured by MRI). Associations with cognitive scores and dementia status were studied. An exploratory data-driven approach investigated age-structure-physiology-cognition links.

RESULTS

Six hundred and twenty-three patients with sleep PSG and brain MRI data were included in this study; 160 with cognitive evaluations. Three hundred and forty-two participants (55%) were female, and age interquartile range was 52 to 69 years. Thirty-six individuals were diagnosed with dementia, 71 with mild cognitive impairment, and 326 with major depression. One hundred and fifteen individuals were evaluated for insomnia and 138 participants had an apnea-hypopnea index equal to or greater than 15. Total PSG delta power correlated positively with frontal lobe/thalamic volumes, and sleep spindle density with thalamic volume. rapid eye movement (REM) duration and amygdala volume were positively associated with cognition. Patients with dementia showed significant differences in five brain structure volumes. REM duration, spindle, and slow-oscillation features had strong associations with cognition and brain structure volumes. PSG and MRI features in combination predicted chronological age (R2 = 0.67) and cognition (R2 = 0.40).

CONCLUSIONS

Routine clinical data holds extended value in understanding and even clinically using brain-sleep-cognition relationships.

Improving the detection of sleep slow oscillations in electroencephalographic data

Study objectives

We aimed to build a tool which facilitates manual labeling of sleep slow oscillations (SOs) and evaluate the performance of traditional sleep SO detection algorithms on such a manually labeled data set. We sought to develop improved methods for SO detection.

Method

SOs in polysomnographic recordings acquired during nap time from ten older adults were manually labeled using a custom built graphical user interface tool. Three automatic SO detection algorithms previously used in the literature were evaluated on this data set. Additional machine learning and deep learning algorithms were trained on the manually labeled data set.

Results

Our custom built tool significantly decreased the time needed for manual labeling, allowing us to manually inspect 96,277 potential SO events. The three automatic SO detection algorithms showed relatively low accuracy (max. 61.08%), but results were qualitatively similar, with SO density and amplitude increasing with sleep depth. The machine learning and deep learning algorithms showed higher accuracy (best: 99.20%) while maintaining a low prediction time.

Conclusions

Accurate detection of SO events is important for investigating their role in memory consolidation. In this context, our tool and proposed methods can provide significant help in identifying these events.

Distributed fMRI dynamics predict distinct EEG rhythms across sleep and wakefulness

The brain exhibits rich oscillatory dynamics that vary across tasks and states, such as the EEG oscillations that define sleep. These oscillations play critical roles in cognition and arousal, but the brainwide mechanisms underlying them are not yet described. Using simultaneous EEG and fast fMRI in subjects drifting between sleep and wakefulness, we developed a machine learning approach to investigate which brainwide fMRI dynamics predict alpha (8-12 Hz) and delta (1-4 Hz) rhythms. We predicted moment-by-moment EEG power from fMRI activity in held-out subjects, and found that information about alpha power was represented by a remarkably small set of regions, segregated in two distinct networks linked to arousal and visual systems. Conversely, delta rhythms were diffusely represented on a large spatial scale across the cortex. These results identify distributed networks that predict delta and alpha rhythms, and establish a computational framework for investigating fMRI brainwide dynamics underlying EEG oscillations.

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.

Widespread slow oscillations support interictal epileptiform discharge networks in focal epilepsy

Interictal epileptiform discharges (IEDs) often co-occur across spatially-separated cortical regions, forming IED networks. However, the factors prompting IED propagation remain unelucidated. We hypothesized that slow oscillations (SOs) might facilitate IED propagation. Here, the amplitude and phase synchronization of SOs preceding propagating and non-propagating IEDs were compared in 22 patients with focal epilepsy undergoing intracranial electroencephalography (EEG) evaluation. Intracranial channels were categorized into the irritative zone (IZ) and normal zone (NOZ) regarding the presence of IEDs. During wakefulness, we found that pre-IED SOs within the IZ exhibited higher amplitudes for propagating IEDs than non-propagating IEDs (delta band: p = 0.001, theta band: p < 0.001). This increase in SOs was also concurrently observed in the NOZ (delta band: p = 0.04). Similarly, the inter-channel phase synchronization of SOs prior to propagating IEDs was higher than those preceding non-propagating IEDs in the IZ (delta band: p = 0.04). Through sliding window analysis, we observed that SOs preceding propagating IEDs progressively increased in amplitude and phase synchronization, while those preceding non-propagating IEDs remained relatively stable. Significant differences in amplitude occurred approximately 1150 ms before IEDs. During non-rapid eye movement (NREM) sleep, SOs on scalp recordings also showed higher amplitudes before intracranial propagating IEDs than before non-propagating IEDs (delta band: p = 0.006). Furthermore, the analysis of IED density around sleep SOs revealed that only high-amplitude sleep SOs demonstrated correlation with IED propagation. Overall, our study highlights that transient but widely distributed SOs are associated with IED propagation as well as generation in focal epilepsy during sleep and wakefulness, providing new insight into the EEG substrate supporting IED networks.

Increase in NREM sleep slow waves following injections of sodium oxybate in the mouse cerebral cortex and the role of somatostatin-positive interneurons

The systemic administration of sodium oxybate (SXB), the sodium salt of gamma-hydroxybutyric acid, promotes slow wave activity (SWA, 0.5-4 Hz EEG power) and increases non-rapid eye movement (NREM) sleep. These effects are mediated by the widely expressed GABAb receptors, and thus, the brain areas targeted by SXB remain unclear. Because slow waves are mainly a cortical phenomenon, we tested here whether systemic SXB promotes SWA by acting directly on the cortex. Moreover, because somatostatin (SOM) + cortical interneurons play a key role in SWA generation, we also assessed their contribution to the effects of SXB. In adult SOM-Cre mice, the injection of SXB in left secondary motor cortex increased SWA during NREM sleep in the first 30 min post-injection (11 mice: either sex). SWA, the amplitude and frequency of the slow waves, and the frequency of the OFF periods increased ipsilaterally and contralaterally to the SXB injection in frontal and parietal cortex. All these changes disappeared when the intracortical injection of SXB was preceded by the chemogenetic inhibition of the SOM+ cells. Thus, SXB may promote the slow waves of NREM sleep, at least in part, by acting directly on the cortex, and this effect involves GABAergic SOM+ interneurons. Our working hypothesis is that SXB potentiates the ability of these cells to inhibit all other cortical cell types via a GABAb mechanism, thus promoting the transition from ON to OFF periods during NREM sleep.

A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets

Neuroscience is moving toward a more integrative discipline where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow-wave activity (<1 Hz), which occurs during unconscious brain states like sleep and general anesthesia and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications. Furthermore, we present the Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a concrete, reusable software implementation to perform broad, detailed, and rigorous comparisons of slow-wave characteristics across multiple, openly available electrocorticography (ECoG) and calcium imaging datasets.

The pros and cons of using automated sleep scoring in sleep research

Sleep scoring plays a pivotal role both in sleep research and in clinical practice. Traditionally, this process has relied on manual scoring by human experts, but it is marred by time constraints, and inconsistencies between different scorers. Consequently, the quest for more efficient and reliable approaches has sparked a great interest in the realm of automatic sleep-scoring methods. In this article, we provide an exploration of the merits and drawbacks of automatic sleep scoring, alongside the pressing challenges and critical considerations that demand attention in this evolving field.

Polysomnographic findings of myotonic dystrophy type 1/type 2: evidence from case-control studies

STUDY OBJECTIVES

This study explores polysomnographic and multiple sleep latency test (MSLT) differences between myotonic dystrophy type 1/type 2 (DM1/DM2) patients and controls.

METHODS

An electronic literature search was conducted in MEDLINE, EMBASE, All EBM databases, and Web of Science from inception to Aug 2023.

RESULTS

Meta-analyses revealed significant reductions in sleep efficiency, N2 percentage, mean SpO2, and MSLT measured mean sleep latency, and increases in N3 sleep, wake time after sleep onset, apnea hypopnea index, and periodic limb movement index in DM1 patients compared with controls. However, any differences of polysomnographic sleep change between DM2 patients and controls could not be established due to limited available studies.

CONCLUSIONS

Multiple significant polysomnographic abnormalities are present in DM1. More case-control studies evaluating polysomnographic changes in DM2 compared with controls are needed.

Maturation-dependent changes in cortical and thalamic activity during sleep slow waves: Insights from a combined EEG-fMRI study

INTRODUCTION

Studies using scalp EEG have shown that slow waves (0.5-4 Hz), the most prominent hallmark of NREM sleep, undergo relevant changes from childhood to adulthood, mirroring brain structural modifications and the acquisition of cognitive skills. Here we used simultaneous EEG-fMRI to investigate the cortical and subcortical correlates of slow waves in school-age children and determine their relative developmental changes.

METHODS

We analyzed data from 14 school-age children with self-limited focal epilepsy of childhood who fell asleep during EEG-fMRI recordings. Brain regions associated with slow-wave occurrence were identified using a voxel-wise regression that also modelled interictal epileptic discharges and sleep spindles. At the group level, a mixed-effects linear model was used. The results were qualitatively compared with those obtained from 2 adolescents with epilepsy and 17 healthy adults.

RESULTS

Slow waves were associated with hemodynamic-signal decreases in bilateral somatomotor areas. Such changes extended more posteriorly relative to those in adults. Moreover, the involvement of areas belonging to the default mode network changes as a function of age. No significant hemodynamic responses were observed in subcortical structures. However, we identified a significant correlation between age and thalamic hemodynamic changes.

CONCLUSIONS

Present findings indicate that the somatomotor cortex may have a key role in slow-wave expression throughout the lifespan. At the same time, they are consistent with a posterior-to-anterior shift in slow-wave distribution mirroring brain maturational changes. Finally, our results suggest that slow-wave changes may not reflect only neocortical modifications but also the maturation of subcortical structures, including the thalamus.

Propagating population activity patterns during spontaneous slow waves in the thalamus of rodents

Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings collected under anesthesia demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus under anesthesia.

Sex and Sleep Disruption as Contributing Factors in Alzheimer's Disease

Alzheimer's disease (AD) affects more women than men, with women throughout the menopausal transition potentially being the most under researched and at-risk group. Sleep disruptions, which are an established risk factor for AD, increase in prevalence with normal aging and are exacerbated in women during menopause. Sex differences showing more disrupted sleep patterns and increased AD pathology in women and female animal models have been established in literature, with much emphasis placed on loss of circulating gonadal hormones with age. Interestingly, increases in gonadotropins such as follicle stimulating hormone are emerging to be a major contributor to AD pathogenesis and may also play a role in sleep disruption, perhaps in combination with other lesser studied hormones. Several sleep influencing regions of the brain appear to be affected early in AD progression and some may exhibit sexual dimorphisms that may contribute to increased sleep disruptions in women with age. Additionally, some of the most common sleep disorders, as well as multiple health conditions that impair sleep quality, are more prevalent and more severe in women. These conditions are often comorbid with AD and have bi-directional relationships that contribute synergistically to cognitive decline and neuropathology. The association during aging of increased sleep disruption and sleep disorders, dramatic hormonal changes during and after menopause, and increased AD pathology may be interacting and contributing factors that lead to the increased number of women living with AD.

Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction

Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-amplitude artifacts. Common approaches to remove them are fraught with issues: channel interpolation, rejection of noisy intervals, and independent component analysis are time-consuming, rely on subjective user decisions, and result in signal loss. Artifact Subspace Reconstruction (ASR) is an increasingly popular approach to rapidly and automatically clean wake EEG data. Indeed, ASR adaptively removes large-amplitude artifacts regardless of their scalp topography or consistency throughout the recording. This makes ASR, at least in theory, a highly-promising tool to clean whole-night EEG. However, ASR crucially relies on calibration against a subset of relatively clean "baseline" data. This is problematic when the baseline changes substantially over time, as in whole-night EEG data. Here we tackled this issue and, for the first time, validated ASR for cleaning sleep EEG. We demonstrate that ASR applied out-of-the-box, with the parameters recommended for wake EEG, results in the dramatic removal of slow waves. We also provide an appropriate procedure to use ASR for automatic and rapid cleaning of whole-night sleep EEG data or any long EEG recording. Our procedure is freely available in Dusk2Dawn, an open-source plugin for EEGLAB.

Brain stimulation techniques as novel treatment options for insomnia: A systematic review

Despite the success of cognitive behavioural therapy for insomnia and recent advances in pharmacotherapy, many patients with insomnia do not sufficiently respond to available treatments. This systematic review aims to present the state of science regarding the use of brain stimulation approaches in treating insomnia. To this end, we searched MEDLINE, Embase and PsycINFO from inception to 24 March 2023. We evaluated studies that compared conditions of active stimulation with a control condition or group. Outcome measures included standardized insomnia questionnaires and/or polysomnography in adults with a clinical diagnosis of insomnia. Our search identified 17 controlled trials that met inclusion criteria, and assessed a total of 967 participants using repetitive transcranial magnetic stimulation, transcranial electric stimulation, transcutaneous auricular vagus nerve stimulation or forehead cooling. No trials using other techniques such as deep brain stimulation, vestibular stimulation or auditory stimulation met the inclusion criteria. While several studies report improvements of subjective and objective sleep parameters for different repetitive transcranial magnetic stimulation and transcranial electric stimulation protocols, important methodological limitations and risk of bias limit their interpretability. A forehead cooling study found no significant group differences in the primary endpoints, but better sleep initiation in the active condition. Two transcutaneous auricular vagus nerve stimulation trials found no superiority of active stimulation for most outcome measures. Although modulating sleep through brain stimulation appears feasible, gaps in the prevailing models of sleep physiology and insomnia pathophysiology remain to be filled. Optimized stimulation protocols and proof of superiority over reliable sham conditions are indispensable before brain stimulation becomes a viable treatment option for insomnia.

What is sleep exactly? Global and local modulations of sleep oscillations all around the clock

Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological. Although these dimensions often fluctuate in step, they can also dissociate. The current paradigm that views sleep as made of global NREM and REM states fail to account for these dissociations. This conundrum can be dissolved by stressing the existence and significance of the local regulation of sleep. We will review the evidence in animals and humans, healthy and pathological brains, showing different forms of local sleep and the consequences on behavior, cognition, and subjective experience. Altogether, we argue that the notion of local sleep provides a unified account for a host of phenomena: dreaming in REM and NREM sleep, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness. Yet, the physiological origins of local sleep or its putative functions remain unclear. Exploring further local sleep could provide a unique and novel perspective on how and why we sleep.

Wake slow waves in focal human epilepsy impact network activity and cognition

Slow waves of neuronal activity are a fundamental component of sleep that are proposed to have homeostatic and restorative functions. Despite this, their interaction with pathology is unclear and there is only indirect evidence of their presence during wakefulness. Using intracortical recordings from the temporal lobe of 25 patients with epilepsy, we demonstrate the existence of local wake slow waves (LoWS) with key features of sleep slow waves, including a down-state of neuronal firing. Consistent with a reduction in neuronal activity, LoWS were associated with slowed cognitive processing. However, we also found that LoWS showed signatures of a homeostatic relationship with interictal epileptiform discharges (IEDs): exhibiting progressive adaptation during the build-up of network excitability before an IED and reducing the impact of subsequent IEDs on network excitability. We therefore propose an epilepsy homeostasis hypothesis: that slow waves in epilepsy reduce aberrant activity at the price of transient cognitive impairment.

Medial temporal lobe functional network architecture supports sleep-related emotional memory processing in older adults

Memory consolidation occurs via reactivation of a hippocampal index during non-rapid eye movement slow-wave sleep (NREM SWS) which binds attributes of an experience existing within cortical modules. For memories containing emotional content, hippocampal-amygdala dynamics facilitate consolidation over a sleep bout. This study tested if modularity and centrality-graph theoretical measures that index the level of segregation/integration in a system and the relative import of its nodes-map onto central tenets of memory consolidation theory and sleep-related processing. Findings indicate that greater network integration is tied to overnight emotional memory retention via NREM SWS expression. Greater hippocampal and amygdala influence over network organization supports emotional memory retention, and hippocampal or amygdala control over information flow are differentially associated with distinct stages of memory processing. These centrality measures are also tied to the local expression and coupling of key sleep oscillations tied to sleep-dependent memory consolidation. These findings suggest that measures of intrinsic network connectivity may predict the capacity of brain functional networks to acquire, consolidate, and retrieve emotional memories.

Protocol of the Budapest sleep, experiences, and traits study: An accessible resource for understanding associations between daily experiences, individual differences, and objectively measured sleep

Sleep is both a neurophysiological state and a biologically necessary behavior that performs a variety of indispensable roles for human health, development, and cognitive functioning. Despite this, comparatively little is known about the relationships between daily experiences and sleep features. Importantly, these relationships are bidirectional in nature, may be differently associated with subjectively and objectively assessed sleep, and may also be modulated by individual differences To address this challenge, we created the Budapest Sleep, Experiences, and Traits Study (BSETS), a multidisciplinary observational sleep study utilizing novel remote EEG devices. BSETS was designed to establish a dataset for future use in investigating the relationships between sleep features and daily experiences. In this paper we describe the protocol of the currently ongoing BSETS, which examines a community-dwelling sample of over 250 healthy participants who are studied in a naturalistic setting using a large questionnaire assessing psychological, demographic, and anthropometric information, as well as evening/morning diaries of sleep and daily experiences, and mobile EEG recordings over a period of 7 days. This dataset will become an accessible resource to the wider scientific community and can be utilized to investigate the complex multidirectional relationships between objectively and subjectively measured sleep, daily experiences, and individual differences, bestowing it with significant value for sleep researchers as well as practitioners working in clinical settings with patients suffering from disordered sleep.

The claustrum and consciousness: An update

The seminal paper of Crick and Koch (2005) proposed that the claustrum, an enigmatic and thin grey matter structure that lies beside the insular cortex, may be involved in the processing of consciousness. As a result, this otherwise obscure structure has received ever-increasing interest in the search for neural correlates of consciousness. Here we review theories of consciousness and discuss the possible relationship between the claustrum and consciousness. We review relevant experimental evidence collected since the Crick and Koch (2005) paper and consider whether these findings support or contradict their hypothesis. We also explore how future experimental work can be designed to clarify how consciousness emerges from neural activity and to understand the role of the claustrum in consciousness.

How we sleep: From brain states to processes

All our lives, we alternate between wakefulness and sleep with direct consequences on our ability to interact with our environment, the dynamics and contents of our subjective experience, and our brain activity. Consequently, sleep has been extensively characterised in terms of behavioural, phenomenological, and physiological changes, the latter constituting the gold standard of sleep research. The common view is thus that sleep represents a collection of discrete states with distinct neurophysiological signatures. However, recent findings challenge such a monolithic view of sleep. Indeed, there can be sharp discrepancies in time and space in the activity displayed by different brain regions or networks, making it difficult to assign a global vigilance state to such a mosaic of contrasted dynamics. Viewing sleep as a multidimensional continuum rather than a succession of non-overlapping and mutually exclusive states could account for these local aspects of sleep. Moving away from the focus on sleep states, sleep can also be investigated through the brain processes that are present in sleep, if not necessarily specific to sleep. This focus on processes rather than states allows to see sleep for what it does rather than what it is, avoiding some of the limitations of the state perspective and providing a powerful heuristic to understand sleep. Indeed, what is sleep if not a process itself that makes up wake up every morning with a brain cleaner, leaner and less cluttered.

Sleep and epilepsy: A clinical and pathophysiological overview

The interaction between sleep and epilepsy is complex. A better understanding of the mechanisms linking sleep and epilepsy appears increasingly important as it may improve diagnosis and therapeutic strategies in patients with epilepsy. In this narrative review, we aim to (i) provide an overview of the physiological and pathophysiological processes linking sleep and epilepsy; (ii) present common sleep disorders in patients with epilepsy; (iii) discuss how sleep and sleep disorders should be considered in new therapeutic approaches to epilepsy such as neurostimulation; and (iv) present the overall nocturnal manifestations and differential diagnosis between epileptic seizures and parasomnia.

Beta traveling waves in monkey frontal and parietal areas encode recent reward history

Brain function depends on neural communication, but the mechanisms of this communication are not well understood. Recent studies suggest that one form of neural communication is through traveling waves (TWs)-patterns of neural oscillations that propagate within and between brain areas. We show that TWs are robust in microarray recordings in frontal and parietal cortex and encode recent reward history. Two adult male monkeys made saccades to obtain probabilistic rewards and were sensitive to the (statistically irrelevant) reward on the previous trial. TWs in frontal and parietal areas were stronger in trials that followed a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys' behavioral sensitivity to the prior reward. The findings suggest that neural communication mediated by TWs within the frontal and parietal lobes contribute to maintaining information about recent reward history and mediating the impact of this history on the monkeys' expectations.

Sleep disrupts complex spiking dynamics in the neocortex and hippocampus

Neuronal interactions give rise to complex dynamics in cortical networks, often described in terms of the diversity of activity patterns observed in a neural signal. Interestingly, the complexity of spontaneous electroencephalographic signals decreases during slow-wave sleep (SWS); however, the underlying neural mechanisms remain elusive. Here, we analyse in-vivo recordings from neocortical and hippocampal neuronal populations in rats and show that the complexity decrease is due to the emergence of synchronous neuronal DOWN states. Namely, we find that DOWN states during SWS force the population activity to be more recurrent, deterministic, and less random than during REM sleep or wakefulness, which, in turn, leads to less complex field recordings. Importantly, when we exclude DOWN states from the analysis, the recordings during wakefulness and sleep become indistinguishable: the spiking activity in all the states collapses to a common scaling. We complement these results by implementing a critical branching model of the cortex, which shows that inducing DOWN states to only a percentage of neurons is enough to generate a decrease in complexity that replicates SWS.

Superior sagittal sinus flow as a proxy for tracking global cerebral blood flow dynamics during wakefulness and sleep

Sleep, a state of reduced consciousness, affects brain oxygen metabolism and lowers cerebral metabolic rate of oxygen (CMRO2). Previously, we quantified CMRO2 during sleep via Fick's Principle, with a single-band MRI sequence measuring both hemoglobin O2 saturation (SvO2) and superior sagittal sinus (SSS) blood flow, which was upscaled to obtain total cerebral blood flow (tCBF). The procedure involves a brief initial calibration scan to determine the upscaling factor (fc), assumed state-invariant. Here, we used a dual-band sequence to simultaneously provide SvO2 in SSS and tCBF in the neck every 16 seconds, allowing quantification of fc dynamically. Ten healthy subjects were scanned by MRI with simultaneous EEG for 80 minutes, yielding 300 temporal image frames per subject. Four volunteers achieved slow-wave sleep (SWS), as evidenced by increased δ-wave activity (per American Academy of Sleep Medicine criteria). SWS was maintained for 13.5 ± 7.0 minutes, with CMRO2 28.6 ± 5.5% lower than pre-sleep wakefulness. Importantly, there was negligible bias between tCBF obtained by upscaling SSS-blood flow, and tCBF measured directly in the inflowing arteries of the neck (intra-class correlation 0.95 ± 0.04, averaged across all subjects), showing that the single-band approach is a valid substitute for quantifying tCBF, simplifying image data collection and analysis without sacrificing accuracy.

Coordinated human sleeping brainwaves map peripheral body glucose homeostasis

Insufficient sleep impairs glucose regulation, increasing the risk of diabetes. However, what it is about the human sleeping brain that regulates blood sugar remains unknown. In an examination of over 600 humans, we demonstrate that the coupling of non-rapid eye movement (NREM) sleep spindles and slow oscillations the night before is associated with improved next-day peripheral glucose control. We further show that this sleep-associated glucose pathway may influence glycemic status through altered insulin sensitivity, rather than through altered pancreatic beta cell function. Moreover, we replicate these associations in an independent dataset of over 1,900 adults. Of therapeutic significance, the coupling between slow oscillations and spindles was the most significant sleep predictor of next-day fasting glucose, even more so than traditional sleep markers, relevant to the possibility of an electroencephalogram (EEG) index of hyperglycemia. Taken together, these findings describe a sleeping-brain-body framework of optimal human glucose homeostasis, offering a potential prognostic sleep signature of glycemic control.