Clinical Utility of Sleep Recordings During Presurgical Epilepsy Evaluation With Stereo-Electroencephalography: A Systematic Review

SUMMARY

Although the role of sleep in modulating epileptic activity is well established, many epileptologists overlook the significance of considering sleep during presurgical epilepsy evaluations in cases of drug-resistant epilepsy. Here, we conducted a comprehensive literature review from January 2000 to May 2023 using the PubMed electronic database and compiled evidence to highlight the need to revise the current clinical approach. All articles were assessed for eligibility by two independent reviewers. Our aim was to shed light on the clinical value of incorporating sleep monitoring into presurgical evaluations with stereo-electroencephalography. We present the latest developments on the important bidirectional interactions between sleep and various forms of epileptic activity observed in stereo-electroencephalography recordings. Specifically, epileptic activity is modulated by different sleep stages, peaking in non-rapid eye movement sleep, while being suppressed in rapid eye movement sleep. However, this modulation can vary across different brain regions, underlining the need to account for sleep to accurately pinpoint the epileptogenic zone during presurgical assessments. Finally, we offer practical solutions, such as automated sleep scoring algorithms using stereo-electroencephalography data alone, to seamlessly integrate sleep monitoring into routine clinical practice. It is hoped that this review will provide clinicians with a readily accessible roadmap to the latest evidence concerning the clinical utility of sleep monitoring in the context of stereo-electroencephalography and aid the development of therapeutic and diagnostic strategies to improve patient surgical outcomes.

Pulsatile corticoid therapy reduces interictal epileptic activity burden in children with genetic drug-resistant epilepsy

OBJECTIVE

Corticosteroids and adrenocorticotropic hormone (ACTH) are the therapy of choice to treat infantile spasms. However, systematic studies about their use in other types of childhood epilepsies remain rare and ACTH can have serious side effects. This study compares the interictal epileptic activity (IEA) burden (% of electroencephalography (EEG) time with IEDs) in children with genetic drug-resistant epilepsy before and after a standardized treatment with pulsatile corticoid therapy (PCT).

METHODS

Children with drug-resistant epilepsy underwent a standardized protocol for PCT with cycles of high-dose dexamethasone (20 mg/m2 body surface) intravenously. Patients were hospitalized for 3 days per PCT cycle and EEGs were obtained before initiation of treatment (baseline) and during the hospitalization around the time of every second cycle. EEG recordings during sleep and wakefulness were obtained. IEA burden was compared before and after PCT. Secondary outcome measures included the sleep spindle rate, the seizure frequency and subjective evaluation in a standardized interview.

RESULTS

In the cohort of 24 children (10 female, 6.2 ± 3.4 years), IEA burden was lower in the EEG after PCT compared to the baseline (baseline: 5.4% [0.7-97.3] vs. after PCT: 1.5% [0-96.9], p = 0.001, d = -0.41). Sleep physiology expressed by sleep spindles improved after PCT with enhanced fast spindle rates (0.8/min [0-2.2] vs. 1.5/min [0.2-3.4], p = 0.045, d = 0.36). Seizure frequency was decreased in 17 of the 24 patients (70.8%) with one patient achieving seizure freedom. The majority of patients improved in quality of life (79.2%), and sleep (81.3%). No serious adverse effects were documented.

SIGNIFICANCE

This study systematically assessed the effect of PCT in children with genetic / suspected genetic drug-resistant epilepsy. PCT was found to not only reduce the IEA burden but also increase sleep spindle rates, which are important for cognitive functioning.

PLAIN LANGUAGE SUMMARY

In this study, children with a form of epilepsy, which is resistant against antiseizure medication, received a systematic treatment with corticosteroids over multiple cycles in the hospital. It was found that not only the epileptic activity was reduced but also the sleep of the patients was improved after the treatment. These findings could provide the basis for extending the use of corticosteroids in children with epilepsy.

Effects of exercise on sleep in patients with epilepsy: A systematic review

Exercise interventions in epilepsy have been shown to improve seizure frequency, physical capacity, quality of life, mood, and cognitive functioning. However, the effectiveness of exercise in improving sleep in epilepsy is less clear. The purpose of this report is to identify the published literature regarding exercise interventions in people with epilepsy to determine 1) what proportion of published clinical trials assess sleep as an outcome, and 2) what benefits of exercise interventions on sleep have been observed. We searched the PubMed, PsycINFO, and SCOPUS electronic databases using the search terms "epilepsy AND [exercise OR physical activity]" and identified 23 articles reporting on 18 unique clinical trials. Nine studies were conducted in adults, five in children, and four in adults and children with active seizures, controlled seizures, or both. Exercise modalities included aerobic exercise, strength training, walking, and yoga, among others, and some also included educational and motivational components. Exercise effects on sleep were tested in four studies, two of which only included indirect measures of sleep- and rest-related fatigue, with mixed results. Of the two reports assessing sleep directly, one reported marginal non-significant improvements in subjective sleep quality and no improvements in objective sleep quality in children after twelve weeks of walking, and the other reported no benefits in subjective sleep quality after twelve weeks of combined aerobic, strength, and flexibility training in adults. Given the health benefits of sleep and detrimental effects of sleep deprivation in epilepsy, epilepsy researchers need to assess the effects of exercise interventions on sleep.

A platform for brain network sensing and stimulation with quantitative behavioral tracking: Application to limbic circuit epilepsy

Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures. These seizures often originate from limbic networks and people also experience chronic comorbidities related to memory, mood, and sleep (MMS). Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is a proven therapy, but the optimal stimulation parameters remain unclear. We developed a neurotechnology platform for tracking seizures and MMS to enable data streaming between an investigational brain sensing-stimulation implant, mobile devices, and a cloud environment. Artificial Intelligence algorithms provided accurate catalogs of seizures, interictal epileptiform spikes, and wake-sleep brain states. Remotely administered memory and mood assessments were used to densely sample cognitive and behavioral response during ANT-DBS. We evaluated the efficacy of low-frequency versus high-frequency ANT-DBS. They both reduced seizures, but low-frequency ANT-DBS showed greater reductions and better sleep and memory. These results highlight the potential of synchronized brain sensing and behavioral tracking for optimizing neuromodulation therapy.

Impaired post-sleep apnea autonomic arousals in patients with drug-resistant epilepsy

OBJECTIVE

Sudden and unexpected deaths in epilepsy (SUDEP) pathophysiology may involve an interaction between respiratory dysfunction and sleep/wake state regulation. We investigated whether patients with epilepsy exhibit impaired sleep apnea-related arousals.

METHODS

Patients with drug-resistant (N = 20) or drug-sensitive (N = 20) epilepsy and obstructive sleep apnea, as well as patients with sleep apnea but without epilepsy (controls, N = 20) were included. We explored (1) the respiratory arousal threshold based on nadir oxygen saturation, apnea-hypopnea index, and fraction of hypopnea among respiratory events; (2) the cardiac autonomic response to apnea/hypopnea quantified as percentages of changes from the baseline in RR intervals (RRI), high (HF) and low (LF) frequency powers, and LF/HF.

RESULTS

The respiratory arousal threshold did not differ between groups. At arousal onset, RRI decreased (-9.42%) and LF power (179%) and LF/HF ratio (190%) increased. This was followed by an increase in HF power (118%), p < 0.05. The RRI decrease was lower in drug-resistant (-7.40%) than in drug-sensitive patients (-9.94%) and controls (-10.91%), p < 0.05. LF and HF power increases were higher in drug-resistant (188%/126%) than in drug-sensitive patients (172%/126%) and controls (177%/115%), p < 0.05.

CONCLUSIONS

Cardiac reactivity following sleep apnea is impaired in drug-resistant epilepsy.

SIGNIFICANCE

This autonomic dysfunction might contribute to SUDEP pathophysiology.

Scalp and hippocampal sleep correlates of memory function in drug-resistant temporal lobe epilepsy

Seminal animal studies demonstrated the role of sleep oscillations such as cortical slow waves, thalamocortical spindles, and hippocampal ripples in memory consolidation. In humans, whether ripples are involved in sleep-related memory processes is less clear. Here, we explored the interactions between sleep oscillations (measured as traits) and general episodic memory abilities in 26 adults with drug-resistant temporal lobe epilepsy who performed scalp-intracranial electroencephalographic recordings and neuropsychological testing, including two analogous hippocampal-dependent verbal and nonverbal memory tasks. We explored the relationships between hemispheric scalp (spindles, slow waves) and hippocampal physiological and pathological oscillations (spindles, slow waves, ripples, and epileptic spikes) and material-specific memory function. To differentiate physiological from pathological ripples, we used multiple unbiased data-driven clustering approaches. At the individual level, we found material-specific cerebral lateralization effects (left-verbal memory, right-nonverbal memory) for all scalp spindles (rs > 0.51, ps < 0.01) and fast spindles (rs > 0.61, ps < 0.002). Hippocampal epileptic spikes and short pathological ripples, but not physiological oscillations, were negatively (rs > -0.59, ps < 0.01) associated with verbal learning and retention scores, with left lateralizing and antero-posterior effects. However, data-driven clustering failed to separate the ripple events into defined clusters. Correlation analyses with the resulting clusters revealed no meaningful or significant associations with the memory scores. Our results corroborate the role of scalp spindles in memory processes in patients with drug-resistant temporal lobe epilepsy. Yet, physiological and pathological ripples were not separable when using data-driven clustering, and thus our findings do not provide support for a role of sleep ripples as trait-like characteristics of general memory abilities in epilepsy.

Learn how to interpret and use intracranial EEG findings

Epilepsy surgery is the therapy of choice for many patients with drug-resistant focal epilepsy. Recognizing and describing ictal and interictal patterns with intracranial electroencephalography (EEG) recordings is important in order to most efficiently leverage advantages of this technique to accurately delineate the seizure-onset zone before undergoing surgery. In this seminar in epileptology, we address learning objective "1.4.11 Recognize and describe ictal and interictal patterns with intracranial recordings" of the International League against Epilepsy curriculum for epileptologists. We will review principal considerations of the implantation planning, summarize the literature for the most relevant ictal and interictal EEG patterns within and beyond the Berger frequency spectrum, review invasive stimulation for seizure and functional mapping, discuss caveats in the interpretation of intracranial EEG findings, provide an overview on special considerations in children and in subdural grids/strips, and review available quantitative/signal analysis approaches. To be as practically oriented as possible, we will provide a mini atlas of the most frequent EEG patterns, highlight pearls for its not infrequently challenging interpretation, and conclude with two illustrative case examples. This article shall serve as a useful learning resource for trainees in clinical neurophysiology/epileptology by providing a basic understanding on the concepts of invasive intracranial EEG.

Sleep, oscillations, and epilepsy

Sleep and wake are defined through physiological and behavioral criteria and can be typically separated into non-rapid eye movement (NREM) sleep stages N1, N2, and N3, rapid eye movement (REM) sleep, and wake. Sleep and wake states are not homogenous in time. Their properties vary during the night and day cycle. Given that brain activity changes as a function of NREM, REM, and wake during the night and day cycle, are seizures more likely to occur during NREM, REM, or wake at a specific time? More generally, what is the relationship between sleep-wake cycles and epilepsy? We will review specific examples from clinical data and results from experimental models, focusing on the diversity and heterogeneity of these relationships. We will use a top-down approach, starting with the general architecture of sleep, followed by oscillatory activities, and ending with ionic correlates selected for illustrative purposes, with respect to seizures and interictal spikes. The picture that emerges is that of complexity; sleep disruption and pathological epileptic activities emerge from reorganized circuits. That different circuit alterations can occur across patients and models may explain why sleep alterations and the timing of seizures during the sleep-wake cycle are patient-specific.

Subclinical epileptiform activity and sleep disturbances in Alzheimer's disease

INTRODUCTION

Subclinical epileptiform activity (SEA) and sleep disturbances are frequent in Alzheimer's disease (AD). Both have an important relation to cognition and potential therapeutic implications. We aimed to study a possible relationship between SEA and sleep disturbances in AD.

METHODS

In this cross-sectional study, we performed a 24-h ambulatory EEG and polysomnography in 48 AD patients without diagnosis of epilepsy and 34 control subjects.

RESULTS

SEA, mainly detected in frontotemporal brain regions during N2 with a median of three spikes/night [IQR1-17], was three times more prevalent in AD. AD patients had lower sleep efficacy, longer wake after sleep onset, more awakenings, more N1%, less REM sleep and a higher apnea-hypopnea index (AHI) and oxygen desaturation index (ODI). Sleep was not different between AD subgroup with SEA (AD-Epi+) and without SEA (AD-Epi-); however, compared to controls, REM% was decreased and AHI and ODI were increased in the AD-Epi+ subgroup.

DISCUSSION

Decreased REM sleep and more severe sleep-disordered breathing might be related to SEA in AD. These results could have diagnostic and therapeutic implications and warrant further study at the intersection between sleep and epileptiform activity in AD.

Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Rapid eye movement sleep affects interictal epileptic activity differently in mesiotemporal and neocortical areas

OBJECTIVE

Rapid eye movement (REM) sleep reduces the rate and extent of interictal epileptiform discharges (IEDs). Breakthrough epileptic activity during REM sleep is therefore thought to best localize the seizure onset zone (SOZ). We utilized polysomnography combined with direct cortical recordings to investigate the influences of anatomical locations and the time of night on the suppressive effect of REM sleep on IEDs.

METHODS

Forty consecutive patients with drug-resistant focal epilepsy underwent combined polysomnography and stereo-electroencephalography during presurgical evaluation. Ten-minute interictal epochs were selected 2 h prior to sleep onset (wakefulness), and from the first and second half of the night during non-REM (NREM) sleep and REM sleep. IEDs were detected automatically across all channels. Anatomic localization, time of night, and channel type (within or outside the SOZ) were tested as modulating factors.

RESULTS

Relative to wakefulness, there was a suppression of IEDs by REM sleep in neocortical regions (median = -27.6%), whereas mesiotemporal regions showed an increase in IEDs (19.1%, p = .01, d = .39). This effect was reversed when comparing the regional suppression of IEDs by REM sleep relative to NREM sleep (-35.1% in neocortical, -58.7% in mesiotemporal, p < .001, d = .39). Across all patients, no clinically relevant novel IED regions were observed in REM sleep versus NREM or wakefulness based on our predetermined thresholds (4 IEDs/min in REM, 0 IEDs/min in NREM and wakefulness). Finally, there was a reduction in IEDs in late (NREM: 1.08/min, REM: .61/min) compared to early sleep (NREM: 1.22/min, REM: .69/min) for both NREM (p < .001, d = .21) and REM (p = .04, d = .14).

SIGNIFICANCE

Our results demonstrate a spatiotemporal effect of IED suppression by REM sleep relative to wakefulness in neocortical but not mesiotemporal regions, and in late versus early sleep. This suggests the importance of considering sleep stage interactions and the potential influences of anatomical locations when using IEDs to define the epileptic focus.

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.

The Differing Effects of Sleep on Ictal and Interictal Network Dynamics in Drug-Resistant Epilepsy

OBJECTIVE

Sleep has important influences on focal interictal epileptiform discharges (IEDs), and the rates and spatial extent of IEDs are increased in non-rapid eye movement (NREM) sleep. In contrast, the influence of sleep on seizures is less clear, and its effects on seizure topography are poorly documented. We evaluated the influences of NREM sleep on ictal spatiotemporal dynamics and contrasted these with interictal network dynamics.

METHODS

We included patients with drug-resistant focal epilepsy who underwent continuous intracranial electroencephalography (iEEG) with depth electrodes. Patients were selected if they had 1 to 3 seizures from each vigilance state, wakefulness and NREM sleep, within a 48-hour window, and under the same antiseizure medication. A 10-minute epoch of the interictal iEEG was selected per state, and IEDs were detected automatically. A total of 25 patients (13 women; aged 32.5 ± 7.1 years) were included.

RESULTS

The seizure onset pattern, duration, spatiotemporal propagation, and latency of ictal high-frequency activity did not differ significantly between wakefulness and NREM sleep (all p > 0.05). In contrast, IED rates and spatial distribution were increased in NREM compared with wakefulness (p < 0.001, Cliff's d = 0.48 and 0.49). The spatial overlap between vigilance states was higher for seizures (57.1 ± 40.1%) than IEDs (41.7 ± 46.2%; p = 0.001, Cliff's d = 0.51).

INTERPRETATION

In contrast to its effects on IEDs, NREM sleep does not affect ictal spatiotemporal dynamics. This suggests that once the brain surpasses the seizure threshold, it will follow the underlying epileptic network irrespective of the vigilance state. These findings offer valuable insights into neural network dynamics in epilepsy and have important clinical implications for localizing seizure foci. ANN NEUROL 2023.

Focal epilepsy impacts rapid eye movement sleep microstructure

STUDY OBJECTIVES

Whereas there is plenty of evidence on the influence of epileptic activity on non-rapid eye movement (NREM) sleep macro- and micro-structure, data on the impact of epilepsy on rapid eye movement (REM) sleep remains sparse. Using high-density electroencephalography (HD-EEG), we assessed global and focal disturbances of sawtooth waves (STW) as cortically generated sleep oscillations of REM sleep in patients with focal epilepsy.

METHODS

Twenty-two patients with drug-resistant focal epilepsy (13 females; mean age, 32.6 ± 10.7 years; 12 temporal lobe epilepsy) and 12 healthy controls (3 females; 24.0 ± 3.2 years) underwent combined overnight HD-EEG and polysomnography. STW rate, duration, frequency, power, spatial extent, IED rates and sleep homeostatic properties were analyzed.

RESULTS

STW rate and duration were reduced in patients with focal epilepsy compared to healthy controls (rate: 0.64/min ± 0.46 vs. 1.12/min ± 0.41, p = .005, d = -0.98; duration: 3.60 s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01). Not surprisingly given the fronto-central maximum of STW, the reductions were driven by extratemporal lobe epilepsy patients (rate: 0.45/min ± 0.31 vs. 1.12/min ± 0.41, p = .0004, d = -1.35; duration: 3.49 s ± 0.92 vs. 4.57 ± 1.00, p = .017, d = -0.99) and were more pronounced in the first vs. the last sleep cycle (rate first cycle patients vs. controls: 0.60/min ± 0.49 vs. 1.10/min ± 0.55, p = .016, d = -0.90, rate last cycle patients vs. controls: 0.67/min ± 0.51 vs. 0.99/min ± 0.49, p = .11, d = -0.62; duration first cycle patients vs. controls: 3.60s ± 0.76 vs. 4.57 ± 1.00, p = .003, d = -1.01, duration last cycle patients vs. controls: 3.66s ± 0.84 vs. 4.51 ± 1.26, p = .039, d = -0.80). There was no regional decrease of STWs in the region with the epileptic focus vs. the contralateral side (all p > .05).

CONCLUSION

Patients with focal epilepsy and in particular extratemporal lobe epilepsy show a global reduction of STW activity in REM sleep. This may suggest that epilepsy impacts cortically generated sleep oscillations even in REM sleep when epileptic activity is low.

The effect of lacosamide monotherapy on sleep architecture in patients with epilepsy: a preliminary evidence

Lacosamide (LCM) is a third-generation antiseizure medication (ASM), and its effect on sleep architecture was supported by a few studies in patients with drug-resistant epilepsy in which LCM was used as an add-on treatment. To gather knowledge on ASMs effects on sleep, this study aimed at evaluating the effects of LCM monotherapy on sleep in patients with focal epilepsy. Ten patients diagnosed with epilepsy (mean age 58.00 ± 14.77, 60.0% female, mean monthly seizure frequency 1.20 ± 2.48) starting LCM as monotherapy were included. Sleep architecture was assessed through polysomnography at baseline and at the 6-month follow-up visit. A significant decrease was observed in seizure frequency (p = 0.004), being all patients seizure-free at follow-up. At baseline, eight patients had poor sleep efficiency (< 85%). Sleep efficiency increased at follow-up, with only three patients having an index < 85% (p = 0.022). From baseline to follow-up, a significant decrease was observed in sleep latency (p = 0.022) and wakefulness after sleep onset (p = 0.047). Moreover, a significant decrease was observed in the percentage of stage 1 (Md = 6.70 vs Md = 3.85, p = 0.005) and stage 3 (Md = 27.70 vs Md = 22.35, p = 0.01) of Non-REM sleep. This study suggests that LCM monotherapy may positively impact sleep architecture in patients with epilepsy. The sleep efficiency improvement and the decrease of sleep latency and wakefulness after sleep onset observed at follow-up highlight better sleep stability and continuity in patients treated with LCM. Notably, all patients were seizure-free at follow-up, and seizure freedom may also concur to sleep structure improvement.

Decrease in wearable-based nocturnal sleep efficiency precedes epileptic seizures

Introduction

While it is known that poor sleep is a seizure precipitant, this association remains poorly quantified. This study investigated whether seizures are preceded by significant changes in sleep efficiency as measured by a wearable equipped with an electrocardiogram, respiratory bands, and an accelerometer.

Methods

Nocturnal recordings from 47 people with epilepsy hospitalized at our epilepsy monitoring unit were analyzed (304 nights). Sleep metrics during nights followed by epileptic seizures (24 h post-awakening) were compared to those of nights which were not.

Results

Lower sleep efficiency (percentage of sleep during the night) was found in the nights preceding seizure days (p < 0.05). Each standard deviation decrease in sleep efficiency and increase in wake after sleep onset was respectively associated with a 1.25-fold (95 % CI: 1.05 to 1.42, p < 0.05) and 1.49-fold (95 % CI: 1.17 to 1.92, p < 0.01) increased odds of seizure occurrence the following day. Furthermore, nocturnal seizures were associated with significantly lower sleep efficiency and higher wake after sleep onset (p < 0.05), as well as increased odds of seizure occurrence following wake (OR: 5.86, 95 % CI: 2.99 to 11.77, p < 0.001).

Discussion

Findings indicate lower sleep efficiency during nights preceding seizures, suggesting that wearable sensors could be promising tools for sleep-based seizure-day forecasting in people with epilepsy.

Selective activation of the hypothalamic orexinergic but not melanin-concentrating hormone neurons following pilocarpine-induced seizures in rats

Introduction

Sleep disorders are common comorbidities in patients with temporal lobe epilepsy (TLE), but the underlying mechanisms remain poorly understood. Since the lateral hypothalamic (LH) and the perifornical orexinergic (ORX) and melanin-concentrating hormone (MCH) neurons are known to play opposing roles in the regulation of sleep and arousal, dysregulation of ORX and MCH neurons might contribute to the disturbance of sleep-wakefulness following epileptic seizures.

Methods

To test this hypothesis, rats were treated with lithium chloride and pilocarpine to induce status epilepticus (SE). Electroencephalogram (EEG) and electromyograph (EMG) were recorded for analysis of sleep-wake states before and 24 h after SE. Double-labeling immunohistochemistry of c-Fos and ORX or MCH was performed on brain sections from the epileptic and control rats. In addition, anterograde and retrograde tracers in combination with c-Fos immunohistochemistry were used to analyze the possible activation of the amygdala to ORX neural pathways following seizures.

Results

It was found that epileptic rats displayed prolonged wake phase and decreased non-rapid eye movement (NREM) and rapid eye movement (REM) phase compared to the control rats. Prominent neuronal activation was observed in the amygdala and the hypothalamus following seizures. Interestingly, in the LH and the perifornical nucleus, ORX but not MCH neurons were significantly activated (c-Fos+). Neural tracing showed that seizure-activated (c-Fos+) ORX neurons were closely contacted by axon terminals originating from neurons in the medial amygdala.

Discussion

These findings suggest that the spread of epileptic activity from amygdala to the hypothalamus causes selective activation of the wake-promoting ORX neurons but not sleep-promoting MCH neurons, which might contribute to the disturbance of sleep-wakefulness in TLE.

Sleep macrostructure and cyclic alternating pattern in patients who underwent surgery for hippocampal sclerosis: A prospective controlled polysomnographic study

INTRODUCTION

Temporal lobe epilepsy due to hippocampal sclerosis (TLE-HS) is one of the most common drug-resistant epilepsy. Surgery is currently accepted as an effective and safe therapeutic approach compared to antiseizure medications (ASMs). The study aims to evaluate the effect of surgical treatment of TLE-HS on sleep profile and architecture by subjective and objective evaluation of sleep in basal condition after one month and one year.

METHODS

Thirteen patients with TLE-HS were recruited to undergo overnight polysomnography and a subjective evaluation of nocturnal sleep utilizing the Pittsburgh Sleep Quality Index (PSQI) and daytime somnolence through the Epworth Sleepiness Scale (ESS) in basal condition (T0), one month (T1) and one year after surgery (T2), respectively. Thirteen healthy controls (HC) matched for age, sex and BMI were recruited. Scoring and analysis of sleep macrostructure and cyclic alternating pattern (CAP) parameters were performed.

RESULTS

The comparison between patients in basal condition (T0) and HC showed a significant lower sleep efficiency (p = 0.003) and REM percentage (p < 0.001). Regarding CAP, patients at T0 showed higher total CAP rate (p < 0.001), CAP rate in N2 (p < 0.001), higher A3 (%) (p = 0.001), higher mean duration of A1 (p = 0.002), A3 index (p < 0.001), cycle in sequences (p < 0.001), lower B duration (p < 0.001), cycle mean duration (p < 0.001) than HC. Surgery did not induce significant changes in nocturnal macrostructural polysomnographic variables in T1 and T2. Lower CAP rate (T1 vs T0 and T2 vs T0 p < 0.001), CAP rate in N3 (T1 vs T0 and T2 vs T0 p < 0.001), A3 (%) (T1 vs T0 and T2 vs T0 p < 0.001); lower phase A2 index (T1 vs T0 p < 0.001) and A3 index (T1 vs T0 p < 0.001), lower phase A1 index (T2 vs T0 p < 0.001) and cycle in sequences (T2 vs T0 p = 0.002) higher B mean duration (T2 vs T0 p = 0.002). No significant differences were found between T1 and T2 in CAP parameters.

CONCLUSION

We found a significant NREM sleep instability in patients with TLE-HS compared with HC. In addition, anterior temporal lobectomy (ATL) induced a significant improvement in sleep continuity as evaluated by cyclic alternating pattern already one month later and this effect persisted after one year. ALT seems to restore a more resilient sleeping brain.

Sleep in children with refractory epilepsy and epileptic encephalopathies: A systematic review of literature

Children with epilepsy have more sleep disorders compared to healthy children. The bidirectional interaction between epilepsy and sleep is not completely understood. However, disruption of sleep architecture during childhood may have consequences for cognitive development. As children with drug-refractory epilepsy often have intellectual disability, sleep disruption could be an important contributing factor in severity of their cognitive impairment. To better understand these interactions, sleep architecture in children with drug-refractory epilepsy and epileptic encephalopathies should be investigated. In this review, we conducted a systematic literature search on this topic. Articles that investigated sleep macro- and/or microstructure by means of electroencephalogram/polysomnography were included, as well as articles that used validated questionnaires. Sixteen articles were reviewed, eight of which used polysomnography. Only 2 articles examined sleep in children with epileptic encephalopathies. Consistent findings on measures of sleep architecture were a reduction in REM percentage and an increase in sleep fragmentation when comparing drug-refractory patients with non-refractory and healthy subjects. The findings on slow wave sleep were less clear. Studies with questionnaires unambiguously confirmed subjectively more sleep problems in children with drug-refractory epilepsy. This is the first review of literature in this patient population. More good quality sleep studies in children with drug-refractory epilepsy are warranted. The use of wearables in the home setting together with automatic sleep staging could provide more insights.

Sleep and epilepsy: A snapshot of knowledge and future research lines

Sleep and epilepsy have a reciprocal relationship, and have been recognized as bedfellows since antiquity. However, research on this topic has made a big step forward only in recent years. In this narrative review we summarize the most stimulating discoveries and insights reached by the "European school." In particular, different aspects concerning the sleep-epilepsy interactions are analysed: (a) the effects of sleep on epilepsy; (b) the effects of epilepsy on sleep structure; (c) the relationship between epilepsy, sleep and epileptogenesis; (d) the impact of epileptic activity during sleep on cognition; (e) the relationship between epilepsy and the circadian rhythm; (f) the history and features of sleep hypermotor epilepsy and its differential diagnosis; (g) the relationship between epilepsy and sleep disorders.

SleepSEEG: Automatic sleep scoring using intracranial EEG recordings only

OBJECTIVE

To perform automatic sleep scoring based only on intracranial EEG, without the need for scalp electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG), in order to study sleep, epilepsy, and their interaction.

APPROACH

Data from 33 adult patients was used for development and training of the automatic scoring algorithm using both oscillatory and non-oscillatory spectral features. The first step consisted in unsupervised clustering of channels based on feature variability. For each cluster the classification was done in two steps, a multiclass tree followed by binary classification trees to distinguish the more challenging stage N1. The test data consisted in 11 patients, in whom the classification was done independently for each channel and then combined to get a single stage per epoch.

MAIN RESULTS

An overall agreement of 78% was observed in the test set between the sleep scoring of the algorithm and two human experts scoring based on scalp EEG, EOG and EMG. Balanced sensitivity and specificity were obtained for the different sleep stages. The performance was excellent for stages W, N2, and N3, and good for stage R, but with high variability across patients. The performance for the challenging stage N1 was poor, but at a similar level as for published algorithms based on scalp EEG. High confidence epochs in different stages (other than N1) can be identified with median per patient specificity >80%.

SIGNIFICANCE

The automatic algorithm can perform sleep scoring of long term recordings of patients with intracranial electrodes undergoing presurgical evaluation in the absence of scalp EEG, EOG and EMG, which are normally required to define sleep stages but are difficult to use in the context of intracerebral studies. It also constitutes a valuable tool to generate hypotheses regarding local aspects of sleep, and will be significant for sleep evaluation in clinical epileptology and neuroscience research.

Spatio-temporal spike dynamics predict surgical outcome in adult focal epilepsy

OBJECTIVE

We hypothesized that spatio-temporal dynamics of interictal spikes reflect the extent and stability of epileptic sources and determine surgical outcome.

METHODS

We studied 30 consecutive patients (14 good outcome). Spikes were detected in prolonged stereo-electroencephalography recordings. We quantified the spatio-temporal dynamics of spikes using the variance of the spike rate, line length and skewness of the spike distribution, and related these features to outcome. We built a logistic regression model, and compared its performance to traditional markers.

RESULTS

Good outcome patients had more dominant and stable sources than poor outcome patients as expressed by a higher variance of spike rates, a lower variance of line length, and a lower variance of positive skewness (ps < 0.05). The outcome was correctly predicted in 80% of patients. This was better or non-inferior to predictions based on a focal lesion (p = 0.016), focal seizure-onset zone, or complete resection (ps > 0.05). In the five patients where traditional markers failed, spike distribution predicted the outcome correctly. The best results were achieved by 18-h periods or longer.

CONCLUSIONS

Analysis of spike dynamics shows that surgery outcome depends on strong, single and stable sources.

SIGNIFICANCE

Our quantitative method has the potential to be a reliable predictor of surgical outcome.

Relationship Between Epilepsy and Dreaming: Current Knowledge, Hypotheses, and Perspectives

The interactions between epilepsy and sleep are numerous and the impact of epilepsy on cognition is well documented. Epilepsy is therefore likely to influence dreaming as one sleep-related cognitive activity. The frequency of dream recall is indeed decreased in patients with epilepsy, especially in those with primary generalized seizures. The content of dreams is also disturbed in epilepsy patients, being more negative and with more familiar settings. While several confounding factors (anti-seizure medications, depression and anxiety disorders, cognitive impairment) may partly account for these changes, some observations suggest an effect of seizures themselves on dreams. Indeed, the incorporation of seizure symptoms in dream content has been described, concomitant or not with a focal epileptic discharge during sleep, suggesting that epilepsy might directly or indirectly interfere with dreaming. These observations, together with current knowledge on dream neurophysiology and the links between epilepsy and sleep, suggest that epilepsy may impact not only wake- but also sleep-related cognition.

Invasive Electrophysiology for Circuit Discovery and Study of Comorbid Psychiatric Disorders in Patients With Epilepsy: Challenges, Opportunities, and Novel Technologies

Intracranial electroencephalographic (iEEG) recordings from patients with epilepsy provide distinct opportunities and novel data for the study of co-occurring psychiatric disorders. Comorbid psychiatric disorders are very common in drug-resistant epilepsy and their added complexity warrants careful consideration. In this review, we first discuss psychiatric comorbidities and symptoms in patients with epilepsy. We describe how epilepsy can potentially impact patient presentation and how these factors can be addressed in the experimental designs of studies focused on the electrophysiologic correlates of mood. Second, we review emerging technologies to integrate long-term iEEG recording with dense behavioral tracking in naturalistic environments. Third, we explore questions on how best to address the intersection between epilepsy and psychiatric comorbidities. Advances in ambulatory iEEG and long-term behavioral monitoring technologies will be instrumental in studying the intersection of seizures, epilepsy, psychiatric comorbidities, and their underlying circuitry.

Sleep quality and daytime sleepiness in epilepsy: Systematic review and meta-analysis of 25 studies including 8,196 individuals

We sought to gain a better understanding of the relationship between epilepsy and sleep quality and daytime sleepiness by performing a literature search of PubMed for case-control studies that compared patients with epilepsy to controls and reported the Pittsburgh sleep quality index (PSQI) and/or the Epworth sleepiness scale (ESS). Study-specific mean differences in the PSQI and ESS between cases and controls were extracted from the publications and pooled using random-effects meta-analysis. Twenty-five studies (2964 cases, 5232 controls) were included. Fifteen studies reported the PSQI and 24 the ESS. Mean age was 40 years; 50.4% were women. When comparing cases to controls, the pooled mean differences in the PSQI and ESS were 1.27 (95% confidence interval (CI): 0.76, 1.78; P < 0.001; I²: 81.4%) and 0.38 (95% CI: -0.07, 0.84; P = 0.099; I²: 81.0%). Subgroup analyses revealed that mean differences in the ESS were significantly lower in studies with a higher proportion of patients with focal epilepsy (P = 0.004). In this large-scale meta-analysis patients with epilepsy had a higher PSQI, close to the pathological cut-off, compared to controls, but a similar and unremarkable ESS. Further studies are needed to investigate potential effect modifiers, such as specific antiepileptic drugs or seizure frequency.

Bidirectional relationships of sleep and epilepsy in adults with epilepsy

This targeted review addresses the best accepted and most intriguing recent observations on the complex relationships between sleep and epilepsy. Ten to 15% of all epilepsies are sleep-related. Included in these is sleep-related hypermotor epilepsy, renamed from nocturnal frontal lobe epilepsy by a 2016 consensus conference since 30% of cases are extra-frontal, seizures are related to sleep rather than clock time, and the predominant semiology is hypermotor. Stereo-EEG is providing crucial insights into network activation in sleep-related epilepsies and definition of the epileptogenic zone. Pathologic high-frequency oscillations, a promising biomarker for identifying the epileptogenic zone, are most frequent in NREM sleep, lowest in wakefulness and REM sleep, similar to interictal epileptiform discharges (IEDs). Most sleep-related seizures are followed by awakening or arousal and IEDs cause arousals and increase after arousals, likely contributing to sleep/wake complaints. Sleep/wake disorders are 2-3 times more common in adults with epilepsy than the general population; these comorbidities are associated with poorer quality of life and may impact seizure control. Treatment of sleep apnea reduces seizures in many cases. An emerging area of research is in circadian biology and epilepsy. Over 90% of people with epilepsy have seizures with circadian periodicity, in part related to sleep itself, and the majority of SUDEP cases occur in sleep. Recognizing these bidirectional relationships is important for patient and caregiver education and counseling and optimizing epilepsy outcomes.

Deep-Seated Interictal Epileptiform Activity: Another Reason to Lose Sleep

Sleep Disruption in Epilepsy: Ictal and Interictal Epileptic Activity Matter

Peter-Derex L, Klimes P, Latreille V, et al. Ann Neurol. 2020;88(5):907-920. doi:10.1002/ana.25884. PMID: 32833279.

Objective:

Disturbed sleep is common in epilepsy. The direct influence of nocturnal epileptic activity on sleep fragmentation remains poorly understood. Stereo-electroencephalography paired with polysomnography is the ideal tool to study this relationship. We investigated whether sleep-related epileptic activity is associated with sleep disruption.

Methods:

We visually marked sleep stages, arousals, seizures, and epileptic bursts in 36 patients with focal drug resistant epilepsy who underwent combined stereo-electroencephalography/polysomnography during presurgical evaluation. Epileptic spikes were detected automatically. Spike and burst indices (n/sec/channel) were computed across four 3-second time windows (baseline sleep, prearousal, arousal, and postarousal). Sleep stage and anatomic localization were tested as modulating factors. We assessed the intra-arousal dynamics of spikes and their relationship with the slow-wave component of nonrapid eye movement sleep (NR) arousals.

Results:

The vast majority of sleep-related seizures (82.4%; 76.5% asymptomatic) were followed by awakenings or arousals. The epileptic burst index increased significantly before arousals as compared to baseline and postarousal, irrespective of sleep stage or brain area. A similar prearousal increase was observed for the spike index in NR stage 2 and rapid eye movement sleep. In addition, the spike index increased during the arousal itself in neocortical channels and was strongly correlated with the slow-wave component of NR arousals (r = 0.99, P < .0001).

Interpretation:

Sleep fragmentation in focal drug-resistant epilepsy is associated with ictal and interictal epileptic activity. The increase in interictal epileptic activity before arousals suggests its participation in sleep disruption. An additional increase in the spike rate during arousals may result from a sleep–wake boundary instability, suggesting a bidirectional relationship.