Targeted memory reactivation of face-name learning depends on ample and undisturbed slow-wave sleep

Face memory, including the ability to recall a person’s name, is of major importance in social contexts. Like many other memory functions, it may rely on sleep. We investigated whether targeted memory reactivation during sleep could improve associative and perceptual aspects of face memory. Participants studied 80 face-name pairs, and then a subset of spoken names with associated background music was presented unobtrusively during a daytime nap. This manipulation preferentially improved name recall and face recognition for those reactivated face-name pairs, as modulated by two factors related to sleep quality; memory benefits were positively correlated with the duration of stage N3 sleep (slow-wave sleep) and negatively correlated with measures of sleep disruption. We conclude that (a) reactivation of specific face-name memories during sleep can strengthen these associations and the constituent memories, and that (b) the effectiveness of this reactivation depends on uninterrupted N3 sleep.

Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep

During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge and recruit large parts of the brain using a whole-brain model constructed from empirical connectivity data in which SOs are induced independently in each brain area by a local adaptation mechanism. Using an evolutionary optimization approach, good fits to human resting-state fMRI data and sleep EEG data are found at values of the adaptation strength close to a bifurcation where the model produces a balance between local and global SOs with realistic spatiotemporal statistics. Local oscillations are more frequent, last shorter, and have a lower amplitude. Global oscillations spread as waves of silence across the undirected brain graph, traveling from anterior to posterior regions. These traveling waves are caused by heterogeneities in the brain network in which the connection strengths between brain areas determine which areas transition to a down-state first, and thus initiate traveling waves across the cortex. Our results demonstrate the utility of whole-brain models for explaining the origin of large-scale cortical oscillations and how they are shaped by the connectome.

Neural glymphatic system: Clinical implications and potential importance of melatonin

The central nervous system was thought to lack a lymphatic drainage until the recent discovery of the neural glymphatic system. This highly specialized waste disposal network includes classical lymphatic vessels in the dura that absorb fluid and metabolic by-products and debris from the underlying cerebrospinal fluid (CSF) in the subarachnoid space. The subarachnoid space is continuous with the Virchow-Robin peri-arterial and peri-vascular spaces which surround the arteries and veins that penetrate into the neural tissue, respectively. The dural lymphatic vessels exit the cranial vault via an anterior and a posterior route and eventually drain into the deep cervical lymph nodes. Aided by the presence of aquaporin 4 on the perivascular endfeet of astrocytes, nutrients and other molecules enter the brain from peri-arterial spaces and form interstitial fluid (ISF) that baths neurons and glia before being released into peri-venous spaces. Melatonin, a pineal-derived secretory product which is in much higher concentration in the CSF than in the blood, is believed to follow this route and to clear waste products such as amyloid-β from the interstitial space. The clearance of amyloid-β reportedly occurs especially during slow wave sleep which happens concurrently with highest CSF levels of melatonin. Experimentally, exogenously-administered melatonin defers amyloid-β buildup in the brain of animals and causes its accumulation in the cervical lymph nodes. Clinically, with increased age CSF melatonin levels decrease markedly, co-incident with neurodegeneration and dementia. Collectively, these findings suggest a potential association between the loss of melatonin, decreased glymphatic drainage and neurocognitive decline in the elderly.

A Case of Carbamazepine-Induced Aggravation of Self-Limited Epilepsy with Centrotemporal Spikes Epilepsy and Valproate-Induced Hyperammonemic Encephalopathy in a Child with Heterozygous Gene Variant of Carbomoyl Phosphatase Synthetase Deficiency

Antiepileptics drugs are the mainstay of the management of epilepsy in children. Sodium valproate (VPA) and carbamazepine (CBZ) are widely used medications in childhood epilepsy. Hyperammonemia has been described as a known side effect of valproate therapy. It is known that VPA-associated HA is common among patients who hold genetic mutations of the carbomoyl phosphatase synthase 1 gene (CPS1). Aggravation of self-limited epilepsy with centrotemporal spikes (SLECTS) is a rare side effect of CBZ. Here, we present a child who had CBZ-induced aggravation of rolandic epilepsy and VPA-induced HA encephalopathy in the background of an unrecognised heterozygous gene variant of CPS1. An 8-year-old boy with SLECTS presented with a history of abnormal behaviours and drowsiness. He was apparently well until six years when he developed seizures in favour of rolandic epilepsy. His electroencephalogram (EEG) showed bilateral predominantly on the right-sided central-temporal spikes and waves. The diagnosis of SLECTS was made, and he was commenced on CBZ. Though he showed some improvement at the beginning, his seizure frequency increased when the dose of CBZ was increased. His repeat EEG showed electrical status in slow-wave sleep, and CBZ was stopped. Subsequently, he was started on VPA, and with that, he developed features of encephalopathy. He had elevated serum ammonia with normal liver functions. VPA was stopped with the suspicion of VPA-induced hyperammonemia. Tandem mass spectrometry did not show significant abnormality in the amino acid profile. Specific genetic analysis revealed a c.2756 C > T.p (Ser919Leu) heterozygote genetic mutation of the CSP 1 gene. This is a classic example where side effects of treatment determine the choice of antiepileptics drugs (AEDs) in childhood epilepsy. It is essential to keep in mind that SLECTS can be aggravated with certain AEDs, and VPA-induced HA in the absence of live failure could be due to underlying inherited metabolic disorders.

Low Frequency Oscillations drive EEG's complexity changes during wakefulness and sleep

Recently, the sleep-wake states have been analysed using novel complexity measures, complementing the classical analysis of EEGs by frequency bands. This new approach consistently shows a decrease in EEG's complexity during slow-wave sleep, yet it is unclear how cortical oscillations shape these complexity variations. In this work, we analyse how the frequency content of brain signals affects the complexity estimates in freely moving rats. We find that the low-frequency spectrum - including the Delta, Theta, and Sigma frequency bands - drives the complexity changes during the sleep-wake states. This happens because low-frequency oscillations emerge from neuronal population patterns, as we show by recovering the complexity variations during the sleep-wake cycle from micro, meso, and macroscopic recordings. Moreover, we find that the lower frequencies reveal synchronisation patterns across the neocortex, such as a sensory-motor decoupling that happens during REM sleep. Overall, our works shows that EEG's low frequencies are critical in shaping the sleep-wake states' complexity across cortical scales.

Self-Conscious Affect Is Modulated by Rapid Eye Movement Sleep but Not by Targeted Memory Reactivation–A Pilot Study

The neurophysiological properties of rapid eye movement sleep (REMS) are believed to tune down stressor-related emotional responses. While prior experimental findings are controversial, evidence suggests that affective habituation is hindered if REMS is fragmented. To elucidate the topic, we evoked self-conscious negative affect in the participants (N = 32) by exposing them to their own out-of-tune singing in the evening. Affective response to the stressor was measured with skin conductance response and subjectively reported embarrassment. To address possible inter-individual variance toward the stressor, we measured the shame-proneness of participants with an established questionnaire. The stressor was paired with a sound cue to pilot a targeted memory reactivation (TMR) protocol during the subsequent night's sleep. The sample was divided into three conditions: control (no TMR), TMR during slow-wave sleep, and TMR during REMS. We found that pre- to post-sleep change in affective response was not influenced by TMR. However, REMS percentage was associated negatively with overnight skin conductance response habituation, especially in those individuals whose REMS was fragmented. Moreover, shame-proneness interacted with REM fragmentation such that the higher the shame-proneness, the more the affective habituation was dependent on non-fragmented REMS. In summary, the potential of REMS in affective processing may depend on the quality of REMS as well as on individual vulnerability toward the stressor type.

Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication

Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. While the neurobehavioral symptoms of sleep inertia are well-described, less is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the cognitive impairments observed and the awakening process generally. We observed brain activity following abrupt awakening from slow wave sleep during the biological night. Using electroencephalography (EEG) and a network science approach, we evaluated power, clustering coefficient, and path length across frequency bands under both a control condition and a blue-enriched light intervention condition in a within-subject design. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to blue-enriched light immediately after awakening ameliorated these changes, but only for clustering. Our results suggest that long-range network communication within the brain is crucial to the waking process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanistic explanation for the effect of light in improving performance after waking.

Metabolomic Signature of Patients With Narcolepsy

Background and Objective:Narcolepsy type 1 (NT1) is an orphan brain disorder caused by the irreversible destruction of orexin neurons. Metabolic disturbances are common in patients with NT1 who have a body mass index (BMI) 10-20% higher than the general population, with one third being obese (BMI>30 kg/m2). Besides the destruction of orexin neurons in NT1, the metabolic alterations in obese and non-obese patients with narcolepsy type 1 remain unknown. The aim of the study was to identify possible differences in plasma metabolic profiles between patients with NT1 and controls as a function of their BMI status.Methods:We used a targeted liquid chromatography-mass spectrometry metabolomics approach to measure 141 circulating, low molecular weight metabolites in drug-free fasted plasma samples from 117 NT1 patients (including 41 obese subjects) compared with 116 BMI-matched controls (including 57 obese subjects).Results:Common metabolites driving the difference between NT1 and controls, irrespective of BMI, were identified, namely sarcosine, glutamate, nonaylcarnitine (C9), 5 long chain lysophosphatidylcholine acyls, one sphingolipid, 12 phosphatidylcholine diacyls and 11 phosphatidylcholine acyl-akyls, all showing increased concentrations in NT1. Metabolite concentrations significantly affected by NT1 (n = 42) and BMI category (n = 40) showed little overlap (n = 5). Quantitative enrichment analysis revealed common metabolic pathways that were implicated in the NT1/control differences, in both normal BMI and obese comparisons, namely glycine and serine, arachidonic acid, and tryptophan metabolisms. The metabolites driving these differences were glutamate, sarcosine and ornithine (glycine and serine metabolism), glutamate and PC aa C34:4 (arachidonic acid metabolism) and glutamate, serotonin and tryptophan (tryptophan metabolism). Linear metabolite-endophenotype regression analyses highlight that as part of the NT1 metabolic phenotype, most of the relationships between the sleep parameters (i.e. slow wave sleep duration, sleep latency and periodic leg movement) and metabolite concentrations seen in the controls were lost.Discussion:These results represented the most comprehensive metabolic profiling of patients with NT1 as a function of BMI and propose some metabolic diagnostic biomarkers for NT1, namely glutamate, sarcosine, serotonin, tryptophan, nonaylcarnitine and some phosphatidylcholines. The metabolic pathways identified offer, if confirmed, possible targets for treatment of obesity in NT1.Classification of Evidence:This study provides Class II evidence that a distinct metabolic profile can differentiate patients with Narcolepsy Type 1 from patients without the disorder.