Influence of sleep and sleep deprivation on ictal and interictal epileptiform activity

Efficacy of Melatonin as a Sleep Inducer in EEG Procedures in the Pediatric Population: A Cross-Sectional Study

Introduction Melatonin has been used as an alternative to sleep deprivation for EEG sleep induction in the pediatric population. Our study aims to describe the efficacy of the currently used doses of melatonin for sleep induction among the pediatric age group. Methods A retrospective cross-sectional study included all patients who underwent an EEG after receiving melatonin over the period of one year. A total of 126 patients have been included in the study. Patients aged one year to three years received oral melatonin in doses between 2 mg and 6 mg. Patients in the age of three years and above received 10 mg of melatonin. Patients' success rate in achieving sleep and the exact time required for the patients to fall asleep were obtained using the readings of their EEG. The percentage of patients who have achieved sleep and the time required for those patients to sleep were calculated and correlated with the patient's gender, the presence of any associated neurobehavioral disorders, and their use of antiepileptic drugs (AED). Results Successful sleep was achieved in 84.9% (n:107) of the patients, with a mean time of 24 minutes to fall asleep (SD = 14.36). Patients with neurobehavioral disorders were 20% less likely to fall asleep when compared to other patients without neurobehavioral disorders (p: 0.003). However, there was not a statistically significant difference among different genders and among patients who received AED. Conclusion Melatonin is an effective sleep inducer for patients undergoing EEG procedures. It should be considered in the majority of patients. However, in patients with neurobehavioral disorders, a lower success rate is expected.

Differentiation of subclinical and clinical electrographic events in long-term electroencephalographic recordings

OBJECTIVE

With the advent of ultra-long-term recordings for monitoring of epilepsies, the interpretation of results of isolated electroencephalographic (EEG) recordings covering only selected brain regions attracts considerable interest. In this context, the question arises of whether detected ictal EEG patterns correspond to clinically manifest seizures or rather to purely electrographic events, that is, subclinical events.

METHODS

EEG patterns from 268 clinical seizures and 252 subclinical electrographic events from 50 patients undergoing video-EEG monitoring were analyzed. Features extracted included predominant frequency band, duration, association with rhythmic muscle artifacts, spatial extent, and propagation patterns. Classification using logistic regression was performed based on data from the whole dataset of 10-20 system EEG recordings and from a subset of two temporal electrode contacts.

RESULTS

Correct separation of clinically manifest and purely electrographic events based on 10-20 system EEG recordings was possible in up to 83.8% of events, depending on the combination of features included. Correct classification based on two-channel recordings was only slightly inferior, achieving 78.6% accuracy; 74.4% and 74.8%, respectively, of events could be correctly classified when using duration alone with either electrode set, although classification accuracies were lower for some subgroups of seizures, particularly focal aware seizures and epileptic arousals.

SIGNIFICANCE

A correct classification of subclinical versus clinical EEG events was possible in 74%-83% of events based on full EEG recordings, and in 74%-78% when considering only a subset of two electrodes, matching the channel number available from new implantable diagnostic devices. This is a promising outcome, suggesting that ultra-long-term low-channel EEG recordings may provide sufficient information for objective seizure diaries. Intraindividual optimization using high numbers of ictal events may further improve separation, provided that supervised learning with external validation is feasible.

Seizure forecasting: Bifurcations in the long and winding road

To date, the unpredictability of seizures remains a source of suffering for people with epilepsy, motivating decades of research into methods to forecast seizures. Originally, only few scientists and neurologists ventured into this niche endeavor, which, given the difficulty of the task, soon turned into a long and winding road. Over the past decade, however, our narrow field has seen a major acceleration, with trials of chronic electroencephalographic devices and the subsequent discovery of cyclical patterns in the occurrence of seizures. Now, a burgeoning science of seizure timing is emerging, which in turn informs best forecasting strategies for upcoming clinical trials. Although the finish line might be in view, many challenges remain to make seizure forecasting a reality. This review covers the most recent scientific, technical, and medical developments, discusses methodology in detail, and sets a number of goals for future studies.

Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

The Relationship Between Sleep, Epilepsy, and Development: a Review

PURPOSE OF REVIEW

To review the relationship between sleep, neurodevelopment, and epilepsy and potential underlying physiological mechanisms.

RECENT FINDINGS

Recent studies have advanced our understanding of the role of sleep in early brain development and epilepsy. Epileptogenesis has been proposed to occur when there is a failure of normal adaptive processes of synaptic and homeostatic plasticity. This sleep-dependent transformation may explain the cognitive impairment seen in epilepsy, especially when occurring early in life. The glymphatic system, a recently discovered waste clearance system of the central nervous system, has been described as a potential mechanism underlying the relationship between sleep and seizures and may account for the common association between sleep deprivation and increased seizure risk. Epilepsy and associated sleep disturbances can critically affect brain development and neurocognition. Here we highlight recent findings on this topic and emphasize the importance of screening for sleep concerns in people with epilepsy.

Obstructive sleep apnea and epilepsy: understanding the pathophysiology of the comorbidity

Obstructive sleep apnea (OSA) is a sleep disorder of significant health concern with a high prevalence in the general population. It has been found to exhibit a high incidence of comorbidity with epilepsy, the exact underlying pathophysiology of which still remains poorly understood. OSA is characterized by apnea/hypopnea spells and arousals, leading to intermittent hypoxemia and sleep deprivation. Both sleep deprivation and hypoxemia adversely affect the cortical excitability and favor epileptogenesis and worsening of pre-existing epilepsy, if any. In patients with OSA, deprivation of rapid eye movement sleep (REMS) phase (known for its strong antiepileptic influence) is relatively more than that non rapid eye movement sleep phase leading to postulation of REMS deprivation as a significant factor in the development of epilepsy as a comorbidity in patients with OSA. Furthermore, OSA and epilepsy both have shown to exercise a bidirectional influence on one another and are also likely to exacerbate each other through a positive feedback mechanism. This is especially based on the reports of improved control of epilepsy upon treatment of comorbid OSA. This brief paper attempts to present an underlying pathophysiological basis of the comorbidity of OSA and epilepsy based upon sleep deprivation and hypoxemia that are characteristic features observed in patients with OSA.

Perspectives on the basis of seizure-induced respiratory dysfunction

Epilepsy is an umbrella term used to define a wide variety of seizure disorders and sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in epilepsy. Although some SUDEP risk factors have been identified, it remains largely unpredictable, and underlying mechanisms remain poorly understood. Most seizures start in the cortex, but the high mortality rate associated with certain types of epilepsy indicates brainstem involvement. Therefore, to help understand SUDEP we discuss mechanisms by which seizure activity propagates to the brainstem. Specifically, we highlight clinical and pre-clinical evidence suggesting how seizure activation of: (i) descending inhibitory drive or (ii) spreading depolarization might contribute to brainstem dysfunction. Furthermore, since epilepsy is a highly heterogenous disorder, we also considered factors expected to favor or oppose mechanisms of seizure propagation. We also consider whether epilepsy-associated genetic variants directly impact brainstem function. Because respiratory failure is a leading cause of SUDEP, our discussion of brainstem dysfunction focuses on respiratory control.

On the relationships between epilepsy, sleep, and Alzheimer's disease: A narrative review

Epilepsy, sleep, and Alzheimer's disease (AD) are tightly and potentially causally interconnected. The aim of our review was to investigate current research directions on these relationships. Our hope is that they may indicate preventive measures and new treatment options for early neurodegeneration. We included articles that assessed all three topics and were published during the last ten years. We found that this literature corroborates connections on various pathophysiological levels, including sleep-stage-related epileptiform activity in AD, the negative consequences of different sleep disorders on epilepsy and cognition, common biochemical pathways as well as network dysfunctions. Here we provide a detailed overview of these topics and we discuss promising diagnostic and therapeutic consequences.

Electrophysiological Biomarkers of Epileptogenicity in Alzheimer's Disease

Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. Accurate identification of hyperexcitability and appropriate intervention to slow the compromise of cognitive functions of AD might open up a new approach to treatment. Based on the results of several studies, epileptiform discharges, especially those with specific features (including high frequency, robust morphology, right temporal location, and occurrence during awake or rapid eye movement states), frequent small sharp spikes (SSSs), temporal intermittent rhythmic delta activities (TIRDAs), and paroxysmal slow wave events (PSWEs) recorded in long-term scalp electroencephalogram (EEG) provide sufficient sensitivity and specificity in detecting cortical network hyperexcitability and epileptogenicity of AD. In addition, magnetoencephalogram (MEG), foramen ovale (FO) electrodes, and computational approaches help to find subclinical seizures that are invisible on scalp EEGs. We performed a comprehensive analysis of the aforementioned electrophysiological biomarkers of AD-related seizures.

Electrophysiological and neurochemical evaluation of the adverse effects of REM sleep deprivation and epileptic seizures on rat's brain

AIM

The current study aims to investigate the impact of paradoxical (REM) sleep deprivation and/or epileptic seizures on rat's cortical brain tissues.

MAIN METHODS

Animals were divided into four groups; control, epileptic, REM sleep deprived and epileptic subjected to REM sleep deprivation. Electrocorticogram (ECoG) signals were recorded and quantitatively analyzed for each group. Concentrations of amino acid neurotransmitters; proinflammatory cytokines; and oxidative stress parameters; and acetylcholinesterase activity were determined in the cortex of the animals in different groups.

KEY FINDINGS

Results showed significant variations in the spectral distribution of ECoG waves in the epilepsy model, 24- and 48-hours of REM sleep deprivation and their combined effects indicating a state of cortical hyperexcitability. Significant increases in NO and taurine and significant decrement in glutamine, GABA and glycine were determined. In REM sleep deprived rats significant elevation in glutamate, aspartate, glycine and taurine and a significant lowering in GABA were obtained. This was accompanied by significant reduction in AchE and IL-β. In the cortical tissue of epileptic rats deprived from REM sleep significant increases in lipid peroxidation, TNF-α, IL-1β, IL-6 and aspartate and a significant reduction in AchE were observed.

SIGNIFICANCE

The present data indicate that REM sleep deprivation induces an increase in lipid peroxidation and storming in proinflammatory cytokines in the cortex of rat model of epilepsy during SRS. These changes are associated with a decreased seizure threshold as inferred from the increase in alpha and Beta waves and a decrease in Delta waves of ECoG.

Neurochemical effects of sleep deprivation in the hippocampus of the pilocarpine-induced rat model of epilepsy

OBJECTIVES

The present study aims to investigate the pathological mechanisms mediating the effect of paradoxical sleep deprivation (PSD) for 48 hr on the spontaneous recurrent seizures (SRS) stage of the pilocarpine rat model of temporal lobe epilepsy.

MATERIALS AND METHODS

This was carried out through assessment of amino acid neurotransmitter levels, the main oxidative stress parameters, and the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) in the hippocampus. The experimental animals were divided into 4 groups: control, epileptic, PSD, and epileptic+PSD groups.

RESULTS

Data indicated that PSD in epileptic rats induced a significant decrease in GSH levels. TNF-α increased significantly in the PSD group and decreased significantly in both epileptic rats and epileptic rats deprived of paradoxical sleep. PSD induced a significant increase in glutamine, glutamate, and aspartate and a significant decrease in GABA. In epileptic rats and epileptic rats deprived of PS, a significant increase in aspartate and a significant decrease in GABA and taurine were recorded.

CONCLUSION

The present data suggest that exposure to PSD for 48 hr did not worsen the alterations produced in the present epileptic model. However, epileptic, PSD, epileptic + PSD groups showed a state of hyperexcitability and oxidative stress. PSD may increase the susceptibility of animals to the development of epilepsy.

Sleep Deprivation and Neurological Disorders

Sleep plays an important role in maintaining neuronal circuitry, signalling and helps maintain overall health and wellbeing. Sleep deprivation (SD) disturbs the circadian physiology and exerts a negative impact on brain and behavioural functions. SD impairs the cellular clearance of misfolded neurotoxin proteins like α-synuclein, amyloid-β, and tau which are involved in major neurodegenerative diseases like Alzheimer's disease and Parkinson's disease. In addition, SD is also shown to affect the glymphatic system, a glial-dependent metabolic waste clearance pathway, causing accumulation of misfolded faulty proteins in synaptic compartments resulting in cognitive decline. Also, SD affects the immunological and redox system resulting in neuroinflammation and oxidative stress. Hence, it is important to understand the molecular and biochemical alterations that are the causative factors leading to these pathophysiological effects on the neuronal system. This review is an attempt in this direction. It provides up-to-date information on the alterations in the key processes, pathways, and proteins that are negatively affected by SD and become reasons for neurological disorders over a prolonged period of time, if left unattended.

Association of epileptiform abnormalities and seizures in Alzheimer disease

OBJECTIVE

To examine the relationship between scalp EEG biomarkers of hyperexcitability in Alzheimer disease (AD) and to determine how these electric biomarkers relate to the clinical expression of seizures in AD.

METHODS

In this cross-sectional study, we performed 24-hour ambulatory scalp EEGs on 43 cognitively normal elderly healthy controls (HC), 41 participants with early-stage AD with no history or risk factors for epilepsy (AD-NoEp), and 15 participants with early-stage AD with late-onset epilepsy related to AD (AD-Ep). Two epileptologists blinded to diagnosis visually reviewed all EEGs and annotated all potential epileptiform abnormalities. A panel of 9 epileptologists blinded to diagnosis was then surveyed to generate a consensus interpretation of epileptiform abnormalities in each EEG.

RESULTS

Epileptiform abnormalities were seen in 53% of AD-Ep, 22% of AD-NoEp, and 4.7% of HC. Specific features of epileptiform discharges, including high frequency, robust morphology, right temporal location, and occurrence during wakefulness and REM, were associated with clinical seizures in AD. Multiple EEG biomarkers concordantly demonstrated a pattern of left temporal lobe hyperexcitability in early stages of AD, whereas clinical seizures in AD were often associated with bitemporal hyperexcitability. Frequent small sharp spikes were specifically associated with epileptiform EEGs and thus identified as a potential biomarker of hyperexcitability in AD.

CONCLUSION

Epileptiform abnormalities are common in AD but not all equivalent. Specific features of epileptiform discharges are associated with clinical seizures in AD. Given the difficulty recognizing clinical seizures in AD, these EEG features could provide guidance on which patients with AD are at high risk for clinical seizures.

Magnetoencephalography: Clinical and Research Practices

Magnetoencephalography (MEG) is a neurophysiological technique that detects the magnetic fields associated with brain activity. Synthetic aperture magnetometry (SAM), a MEG magnetic source imaging technique, can be used to construct both detailed maps of global brain activity as well as virtual electrode signals, which provide information that is similar to invasive electrode recordings. This innovative approach has demonstrated utility in both clinical and research settings. For individuals with epilepsy, MEG provides valuable, nonredundant information. MEG accurately localizes the irritative zone associated with interictal spikes, often detecting epileptiform activity other methods cannot, and may give localizing information when other methods fail. These capabilities potentially greatly increase the population eligible for epilepsy surgery and improve planning for those undergoing surgery. MEG methods can be readily adapted to research settings, allowing noninvasive assessment of whole brain neurophysiological activity, with a theoretical spatial range down to submillimeter voxels, and in both humans and nonhuman primates. The combination of clinical and research activities with MEG offers a unique opportunity to advance translational research from bench to bedside and back.

The Mutual Interaction Between Sleep and Epilepsy on the Neurobiological Basis and Therapy

BACKGROUND

Sleep and epilepsy are mutually related in a complex, bidirectional manner. However, our understanding of this relationship remains unclear.

RESULTS

The literatures of the neurobiological basis of the interactions between sleep and epilepsy indicate that non rapid eye movement sleep and idiopathic generalized epilepsy share the same thalamocortical networks. Most of neurotransmitters and neuromodulators such as adenosine, melatonin, prostaglandin D2, serotonin, and histamine are found to regulate the sleep-wake behavior and also considered to have antiepilepsy effects; antiepileptic drugs, in turn, also have effects on sleep. Furthermore, many drugs that regulate the sleep-wake cycle can also serve as potential antiseizure agents. The nonpharmacological management of epilepsy including ketogenic diet, epilepsy surgery, neurostimulation can also influence sleep.

CONCLUSION

In this paper, we address the issues involved in these phenomena and also discuss the various therapies used to modify them.