Circuits and components of delta wave regulation

LPS-induced systemic inflammation disrupts brain activity in a region- and vigilance-state specific manner

Sepsis-associated encephalopathy (SAE) is a common complication of sepsis and the systemic inflammatory response syndrome that leads to lasting consequences in survivors. It manifests as early EEG changes that are region-, time- and state-specific, possibly reflecting distinct mechanisms of injury. Here, we investigated the effects of 5 mg/kg lipopolysaccharide (LPS) on hippocampal and cortical sleep-wake states, oscillatory and non-oscillatory neuronal activity, as well as on within- and between-state dynamics using state-space analysis. LPS induced rapid-onset severe temporal and spatial vigilance state fragmentation, which preceded all other spectral changes by ∼90 min. Thereafter, LPS led to specific destabilization and increased delta oscillatory activity in wakefulness, but not NREM sleep, although state transitions remained largely normal. Instead, reduced NREM delta power resulted from aperiodic spectrum changes. LPS specifically reduced higher frequency hippocampal gamma oscillations (60-80 Hz peak) in wakefulness, but not cortical high gamma or lower frequency gamma oscillations. These results suggest that disruption of sleep-wake patterns could serve as an early indicator of sepsis and associated encephalopathy, independent of spectral changes. Moreover, treatment aimed at stabilizing vigilance states in early stages of sepsis might prove to be a novel option preventing the development of further pathological neurophysiology, as well as limiting inflammation-related brain damage.

NKCC1 inhibition improves sleep quality and EEG information content in a Down syndrome mouse model

In several brain disorders, the hyperpolarizing/inhibitory effects of GABA signaling through Cl-permeable GABAA receptors are compromised, leading to an imbalance between neuronal excitation and inhibition. For example, the Ts65Dn mouse model of Down syndrome (DS) exhibits increased expression of the Cl- importer NKCC1, leading to depolarizing gamma aminobutyric acid (GABA) signaling in the mature hippocampus and cortex. Inhibiting NKCC1 with the Food and Drug Administration (FDA)-approved diuretic bumetanide rescues inhibitory GABAergic transmission, synaptic plasticity, and cognitive functions in adult Ts65Dn mice. Given that DS individuals and Ts65Dn mice show sleep disturbances, and considering the key role of GABAergic transmission in sleep, we investigated whether NKCC1 upregulation contributes to sleep abnormalities in adult Ts65Dn mice. Chronic oral administration of bumetanide ameliorated the spectral profile of sleep, sleep architecture, and electroencephalogram (EEG) entropy/complexity, accompanied by a lower hyperactivity in trisomic mice. These results offer a potential avenue for addressing common sleep disturbances in DS.

Abnormal brain-heart electrophysiology in mild and severe orthostatic hypotension

INTRODUCTION

This study investigated the changes in cardiocerebral electrophysiology in patients with mild orthostatic hypotension (MOH) and severe orthostatic hypotension (SOH) and their relationship with the severity of orthostatic hypotension, psychiatric symptoms, and cognitive dysfunction.

METHODS

This study included 72 nonorthostatic hypotension (NOH), 17 with MOH, and 11 with SOH. Seated resting-state heart rate variability (HRV) and quantitative electroencephalogram parameters were synchronized and recorded. HRV measures in the time and frequency domains were analyzed, along with the peak frequency and power of the brain waves.

RESULTS

Abnormal neuronal activity was found in FP1 in patients with MOH, whereas it was more widespread in FP1, FP2, and O2 in patients with SOH ( P  < 0.05). Cardiac and cerebral electrophysiological abnormalities were significantly associated with orthostatic hypotension severity, psychiatric symptoms, and cognitive dysfunction.

CONCLUSION

Abnormal EEG activity in patients are mainly manifested in the prefrontal and occipital lobes, especially in patients with SOH. These results may help patients to better understand the mechanisms underlying orthostatic hypotension severity and psychiatric and cognitive impairment in orthostatic hypotension.

Chronic Caffeine Consumption, Alone or Combined with Agomelatine or Quetiapine, Reduces the Maximum EEG Peak, As Linked to Cortical Neurodegeneration, Ovarian Estrogen Receptor Alpha, and Melatonin Receptor 2

RATIONALE

Evidence of the effects of chronic caffeine (CAFF)-containing beverages, alone or in combination with agomelatine (AGO) or quetiapine (QUET), on electroencephalography (EEG), which is relevant to cognition, epileptogenesis, and ovarian function, remains lacking. Estrogenic, adenosinergic, and melatonergic signaling is possibly linked to the dynamics of these substances.

OBJECTIVES

The brain and ovarian effects of CAFF were compared with those of AGO + CAFF and QUET + CAFF. The implications of estrogenic, adenosinergic, and melatonergic signaling and the brain-ovarian crosstalk were investigated.

METHODS

Adult female rats were administered AGO (10 mg/kg), QUET (10 mg/kg), CAFF, AGO + CAFF, or QUET + CAFF, once daily for 8 weeks. EEG, estrous cycle progression, and microstructure of the brain and ovaries were examined. Brain and ovarian 17β-estradiol (E2), antimullerian hormone (AMH), estrogen receptor alpha (E2Rα), adenosine receptor 2A (A2AR), and melatonin receptor 2 (MT2R) were assessed.

RESULTS

CAFF, alone or combined with AGO or QUET, reduced the maximum EEG peak, which was positively linked to ovarian E2Rα, negatively correlated to cortical neurodegeneration and ovarian MT2R, and associated with cystic ovaries. A large corpus luteum emerged with AGO + CAFF and QUET + CAFF, antagonizing the CAFF-mediated increased ovarian A2AR and reduced cortical E2Rα. AGO + CAFF provoked TTP delay and increased ovarian AMH, while QUET + CAFF slowed source EEG frequency to δ range and increased brain E2.

CONCLUSIONS

CAFF treatment triggered brain and ovarian derangements partially antagonized with concurrent AGO or QUET administration but with no overt affection of estrus cycle progression. Estrogenic, adenosinergic, and melatonergic signaling and brain-ovarian crosstalk may explain these effects.

Extracts of Prunella vulgaris Enhanced Pentobarbital-Induced Sleeping Behavior in Mice Potentially via Adenosine A2A Receptor Activity

The increasing prevalence of sleep dysregulation cases has prompted the search for effective and safe sleep-enhancing agents. Numerous medications used in the treatment of sleep disorders function by enhancing γ-aminobutyric acid neurotransmitter activity. Unfortunately, these substances may induce significant adverse effects in chronic users, such as dependence and motor behavior impairments. Consequently, there is a growing interest in exploring therapeutic sleep-enhancing agents derived from natural sources, with the anticipation of causing less severe side effects. Prunella vulgaris (PV), a perennial plant indigenous to South Korea, exhibits various pharmacological effects, likely attributed to its chemical composition. Rosmarinic acid, one of its components, has previously demonstrated sleep-potentiating properties, suggesting the potential for PV to exhibit similar pharmacological effects. This study aims to investigate the potential effects of repeated administration of PV extract on the sleep behavior, brainwave activity, sleep-wake cycle, and physiological behavior of mice. Findings indicate that PV extracts exhibit sleep-enhancing effects in mice, characterized by prolonged sleep duration and a reduced onset time of pentobarbital-induced sleep. However, PV extracts only reduced alpha wave powers, with minor alterations in wakefulness and rapid-eye-movement sleep duration. In contrast to diazepam, PV extracts lack adverse effects on locomotor activity, motor coordination, or anxiety in mice. Receptor-binding assay and caffeine treatment support the potential involvement of adenosine A2A receptors in the effects of PV, suggesting distinct mechanisms of action compared to diazepam, despite both exhibiting sleep-altering effects. Overall, our results suggest that PV holds promise as a potential source of sleep-aiding agents.

Heukharang (Lactuca sativa L.) extracts enhanced the sleep behavior of mice: potential involvement of adenosine A1 and A2A receptors

A significant proportion of the world's population suffers from insomnia, a disorder characterized by complications in initiating and maintaining sleep. Many medications used to treat insomnia target the γ-aminobutyric acid (GABA) neurotransmitter system. However, these substances, such as benzodiazepines, induce significant adverse consequences, including dependence and memory impairment, after prolonged use. Thus, current studies are aimed at developing therapeutic hypnotics derived from natural sources that may cause less severe side effects. Heukharang is a variety of lettuce from Korea that was discovered to contain sleep-promoting compounds. Therefore, we investigated the potential effects of sub-chronic administration of Heukharang extract (FSD-LS) on sleep behavior (pentobarbital-induced sleeping test), brain wave activity and sleep architecture (electroencephalography), and physiological behavior (open-field test and rota-rod) in mice, along with radioligand binding assays (GABAA, adenosine A1 and A2A receptors). We found that FSD-LS prolonged the total sleep duration and reduced the onset time of sleep, and enhanced delta wave power and non-rapid eye movement (NREM) sleep duration, all indicating persistent sleep-enhancing effects. FSD-LS lacked adverse effects on the spontaneous locomotor activity and motor coordination of mice, unlike diazepam. Pharmacological blocking using caffeine and bicuculline supported the possible involvement of adenosine receptors in the sleep-promoting effects of FSD-LS, with partial contribution from GABA receptor activity. Overall, our study recommends FSD-LS as a potential source for the development of sleep-aiding therapeutics.

Sleep-Deep-Learner is taught sleep-wake scoring by the end-user to complete each record in their style

Sleep-wake scoring is a time-consuming, tedious but essential component of clinical and preclinical sleep research. Sleep scoring is even more laborious and challenging in rodents due to the smaller EEG amplitude differences between states and the rapid state transitions which necessitate scoring in shorter epochs. Although many automated rodent sleep scoring methods exist, they do not perform as well when scoring new datasets, especially those which involve changes in the EEG/EMG profile. Thus, manual scoring by expert scorers remains the gold standard. Here we take a different approach to this problem by using a neural network to accelerate the scoring of expert scorers. Sleep-Deep-Learner creates a bespoke deep convolution neural network model for individual electroencephalographic or local-field-potential (LFP) records via transfer learning of GoogLeNet, by learning from a small subset of manual scores of each EEG/LFP record as provided by the end-user. Sleep-Deep-Learner then automates scoring of the remainder of the EEG/LFP record. A novel REM sleep scoring correction procedure further enhanced accuracy. Sleep-Deep-Learner reliably scores EEG and LFP data and retains sleep-wake architecture in wild-type mice, in sleep induced by the hypnotic zolpidem, in a mouse model of Alzheimer's disease and in a genetic knock-down study, when compared to manual scoring. Sleep-Deep-Learner reduced manual scoring time to 1/12. Since Sleep-Deep-Learner uses transfer learning on each independent recording, it is not biased by previously scored existing datasets. Thus, we find Sleep-Deep-Learner performs well when used on signals altered by a drug, disease model, or genetic modification.

EEG in Down Syndrome-A Review and Insights into Potential Neural Mechanisms

Introduction: Down syndrome (DS) stands out as one of the most prevalent genetic disorders, imposing a significant burden on both society and the healthcare system. Scientists are making efforts to understand the neural mechanisms behind the pathophysiology of this disorder. Among the valuable methods for studying these mechanisms is electroencephalography (EEG), a non-invasive technique that measures the brain's electrical activity, characterised by its excellent temporal resolution. This review aims to consolidate studies examining EEG usage in individuals with DS. The objective was to identify shared elements of disrupted EEG activity and, crucially, to elucidate the neural mechanisms underpinning these deviations. Searches were conducted on Pubmed/Medline, Research Gate, and Cochrane databases. Results: The literature search yielded 17 relevant articles. Despite the significant time span, small sample size, and overall heterogeneity of the included studies, three common features of aberrant EEG activity in people with DS were found. Potential mechanisms for this altered activity were delineated. Conclusions: The studies included in this review show altered EEG activity in people with DS compared to the control group. To bolster these current findings, future investigations with larger sample sizes are imperative.

Sleep-Deep-Net learns sleep wake scoring from the end-user and completes each record in their style

Sleep-wake scoring is a time-consuming, tedious but essential component of clinical and pre-clinical sleep research. Sleep scoring is even more laborious and challenging in rodents due to the smaller EEG amplitude differences between states and the rapid state transitions which necessitate scoring in shorter epochs. Although many automated rodent sleep scoring methods exist, they do not perform as well when scoring new data sets, especially those which involve changes in the EEG/EMG profile. Thus, manual scoring by expert scorers remains the gold-standard. Here we take a different approach to this problem by using a neural network to accelerate the scoring of expert scorers. Sleep-Deep-Net (SDN) creates a bespoke deep convolution neural network model for individual electroencephalographic or local-field-potential records via transfer learning of GoogleNet, by learning from a small subset of manual scores of each EEG/LFP record as provided by the end-user. SDN then automates scoring of the remainder of the EEG/LFP record. A novel REM scoring correction procedure further enhanced accuracy. SDN reliably scores EEG and LFP data and retains sleep-wake architecture in wild-type mice, in sleep induced by the hypnotic zolpidem, in a mouse model of Alzheimer's disease and in a genetic knock-down study, when compared to manual scoring. SDN reduced manual scoring time to 1/12. Since SDN uses transfer learning on each independent recording, it is not biased by previously scored existing data sets. Thus, we find SDN performs well when used on signals altered by a drug, disease model or genetic modification.

Entorhinal cortical delta oscillations drive memory consolidation

Long-term memories are formed by creating stable memory representations via memory consolidation, which mainly occurs during sleep following the encoding of labile memories in the hippocampus during waking. The entorhinal cortex (EC) has intricate connections with the hippocampus, but its role in memory consolidation is largely unknown. Using cell-type- and input-specific in vivo neural activity recordings, here we show that the temporoammonic pathway neurons in the EC, which directly innervate the output area of the hippocampus, exhibit potent oscillatory activities during anesthesia and sleep. Using in vivo individual and populational neuronal activity recordings, we demonstrate that a subpopulation of the temporoammonic pathway neurons, which we termed sleep cells, generate delta oscillations via hyperpolarization-activated cyclic-nucleotide-gated channels during sleep. The blockade of these oscillations significantly impaired the consolidation of hippocampus-dependent memory. Together, our findings uncover a key driver of delta oscillations and memory consolidation that are found in the EC.

P2X7 receptor-activated microglia in cortex is critical for sleep disorder under neuropathic pain

Neuropathic pain (NP) is associated with sleep disturbances, which may substantially influence the quality of life. Clinical and animal studies demonstrated that neurotransmitter is one of the main contributors to cause sleep disturbances induced by NP. Recently, it was reported that P2X7 receptors (P2X7R) are widely expressed in microglia, which serves crucial role in neuronal activity in the pain and sleep-awake cycle. In this study, we adopted the chronic constriction injury (CCI) model to establish the progress of chronic pain and investigated whether P2X7R of microglia in cortex played a critical role in sleep disturbance induced by NP. At electroencephalogram (EEG) level, sleep disturbance was observed in mice treated with CCI as they exhibited mechanical and thermal hypersensitivity, and inhibition of P2X7R ameliorated these changes. We showed a dramatic high level of P2X7R and Iba-1 co-expression in the cortical region, and the inhibition of P2X7R also adversely affected it. Furthermore, the power of LFPs in ventral posterior nucleus (VP) and primary somatosensory cortex (S1) which changed in the CCI group was adverse after the inhibition of P2X7R. Furthermore, inhibition of P2X7R also decreased the VP-S1 coherence which increased in CCI group. Nuclear magnetic resonance demonstrated inhibition of P2X7R decreased glutamate (Glu) levels in thalamic and cortical regions which were significantly increased in the CCI mice. Our findings provide evidence that NP has a critical effect on neuronal activity linked to sleep and may built up a new target for the development of sleep disturbances under chronic pain conditions.

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

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