A Subpopulation of Spikes Predicts Successful Epilepsy Surgery Outcome.

OBJECTIVE: Epileptic spikes are the traditional interictal electroencephalographic (EEG) biomarker for epilepsy. Given their low specificity for identifying the epileptogenic zone (EZ), they are given only moderate attention in presurgical evaluation. This study aims to demonstrate that it is possible to identify specific spike features in intracranial EEG that optimally define the EZ and predict surgical outcome. METHODS: We analyzed spike features on stereo-EEG segments from 83 operated patients from 2 epilepsy centers (37 Engel IA) in wakefulness, non-rapid eye movement sleep, and rapid eye movement sleep. After automated spike detection, we investigated 135 spike features based on rate, morphology, propagation, and energy to determine the best feature or feature combination to discriminate the EZ in seizure-free and non-seizure-free patients by applying 4-fold cross-validation. RESULTS: The rate of spikes with preceding gamma activity in wakefulness performed better for surgical outcome classification (4-fold area under receiver operating characteristics curve [AUC] = 0.755 ± 0.07) than the seizure onset zone, the current gold standard (AUC = 0.563 ± 0.05, p = 0.015) and the ripple rate, an emerging seizure-independent biomarker (AUC = 0.537 ± 0.07, p = 0.006). Channels with a spike-gamma rate exceeding 1.9/min had an 80% probability of being in the EZ. Combining features did not improve the results. INTERPRETATION: Resection of brain regions with high spike-gamma rates in wakefulness is associated with a high probability of achieving seizure freedom. This rate could be applied to determine the minimal number of spiking channels requiring resection. In addition to quantitative analysis, this feature is easily accessible to visual analysis, which could aid clinicians during presurgical evaluation. ANN NEUROL 2023;93:522-535.

Oscillatory and nonoscillatory sleep electroencephalographic biomarkers of the epileptic network.

OBJECTIVE: In addition to the oscillatory brain activity, the nonoscillatory (scale-free) components of the background electroencephalogram (EEG) may provide further information about the complexity of the underlying neuronal network. As epilepsy is considered a network disease, such scale-free metrics might help to delineate the epileptic network. Here, we performed an analysis of the sleep oscillatory (spindle, slow wave, and rhythmic spectral power) and nonoscillatory (H exponent) intracranial EEG using multiple interictal features to estimate whether and how they deviate from normalcy in 38 adults with drug-resistant epilepsy. METHODS: To quantify intracranial EEG abnormalities within and outside the seizure onset areas, patients' values were adjusted based on normative maps derived from the open-access Montreal Neurological Institute open iEEG Atlas. In a subset of 29 patients who underwent resective surgery, we estimated the predictive value of these features to identify the epileptogenic zone in those with a good postsurgical outcome. RESULTS: We found that distinct sleep oscillatory and nonoscillatory metrics behave differently across the epileptic network, with the strongest differences observed for (1) a reduction in spindle activity (spindle rates and rhythmic sigma power in the 10-16 Hz band), (2) a higher rhythmic gamma power (30-80 Hz), and (3) a higher H exponent (steeper 1/f slope). As expected, epileptic spikes were also highest in the seizure onset areas. Furthermore, in surgical patients, the H exponent achieved the highest performance (balanced accuracy of .76) for classifying resected versus nonresected channels in good outcome patients. SIGNIFICANCE: This work suggests that nonoscillatory components of the intracranial EEG signal could serve as promising interictal sleep candidates of epileptogenicity in patients with drug-resistant epilepsy. Our findings further advance the understanding of epilepsy as a disease, whereby absence or loss of sleep physiology may provide information complementary to pathological epileptic processes.

Sleep Disruption in Epilepsy: Ictal and Interictal Epileptic Activity Matter.

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, pre-arousal, arousal, and post-arousal). 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 non-rapid 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 pre-arousal 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 < 0.0001). 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. ANN NEUROL 2020;88:907-920.

The human K-complex: Insights from combined scalp-intracranial EEG recordings.

Sleep spindles and K-complexes (KCs) are a hallmark of N2 sleep. While the functional significance of spindles is comparatively well investigated, there is still ongoing debate about the role of the KC: it is unclear whether it is a cortical response to an arousing stimulus (either external or internal) or whether it has sleep-promoting properties. Invasive intracranial EEG recordings from individuals with drug-resistant epilepsy offer a unique opportunity to study in-situ human brain physiology. To better understand the function of the KC, we aimed to (i) investigate the intracranial correlates of spontaneous scalp KCs, and (ii) compare the intracranial activity of scalp KCs associated or not with arousals. Whole-night recordings from adults with drug-resistant focal epilepsy who underwent combined intracranial-scalp EEG for pre-surgical evaluation at the Montreal Neurological Institute between 2010 and 2018 were selected. KCs were visually marked in the scalp and categorized according to the presence of microarousals: (i) Pre-microarousal KCs; (ii) KCs during an ongoing microarousal; and (iii) KCs without microarousal. Power in different spectral bands was computed to compare physiological intracranial EEG activity at the time of scalp KCs relative to the background, as well as to compare microarousal subcategories. A total of 1198 scalp KCs selected from 40 subjects were analyzed, resulting in 32,504 intracranial KC segments across 992 channels. Forty-seven percent of KCs were without microarousal, 30% were pre-microarousal, and 23% occurred during microarousals. All scalp KCs were accompanied by widespread cortical increases in delta band power (0.3-4 â€‹Hz) relative to the background: the highest percentages were observed in the parietal (60-65%) and frontal cortices (52-58%). Compared to KCs without microarousal, pre-microarousal KCs were accompanied by increases (66%) in beta band power (16-30 â€‹Hz) in the motor cortex, which was present before the peak of the KC. In addition, spatial distribution of spectral power changes following each KC without microarousal revealed that certain brain regions were associated with increases in delta power (25-62%) or decreases in alpha/beta power (11-24%), suggesting a sleep-promoting pattern, whereas others were accompanied by increases of higher frequencies (12-27%), suggesting an arousal-related pattern. This study shows that KCs can be generated across widespread cortical areas. Interestingly, the motor cortex shows awake-like EEG activity before the onset of KCs followed by microarousals. Our findings also highlight region-specific sleep- or arousal-promoting responses following KCs, suggesting a dual role for the human KC.

Objectively measured sleep-wake patterns in patients with drug-resistant epilepsy - Interaction with quality of life and antiepileptic treatment.

RATIONALE: Patients with epilepsy experience frequent episodes of fragmented sleep which may contribute to chronic sleep loss. Enhancing sleep patterns might lead to improved quality of life in these patients. Currently, unlike some other antiepileptic drugs (AEDs), there are no data on the effects of clobazam, a novel AED on sleep. Therefore, we tested the hypothesis that patients with epilepsy will have longer, more consolidated sleep after treatment with clobazam. METHODS: In this prospective study, we included adults with drug-resistant epilepsy who were being considered for treatment with clobazam. Patients with known untreated moderate/severe sleep apnea or with major circadian rhythm disorders were excluded. We tested a set of the following subjective sleep measures: Pittsburgh Sleep Quality Inventory (PSQI), Epworth Sleepiness Scale (ESS), Karolinska Sleepiness Scale (KSS), Insomnia Severity Index (ISI), and Quality of Life in Epilepsy (QOLIE) prior to starting the treatment, as well as after achieving a stable clobazam dose. We also measured sleep pattern using wrist actigraphy - before starting therapy and after achieving stable dose. RESULTS: A total of 12 participants completed all parts of the study. After treatment, a lower number of awakenings and less wake after sleep onset (WASO) were seen, as well as a lower number of seizures. Average pretreatment bedtime was 23:45, and average wake time was 8:24. A higher seizure frequency significantly correlated with all subjective sleep measures, as well as with a higher amount actigraphy measured WASO and less total sleep time (TST) measured both by sleep log and by actigraphy. Those with higher baseline WASO by actigraphy also had more depressive symptoms, worse quality of life, longer duration of epilepsy, and a higher seizure frequency. CONCLUSION: Both objective and subjective sleep metrics correlate with depressive symptoms and quality of life. After treatment, there were fewer awakenings as well as fewer seizures.

Sleep in psychogenic nonepileptic seizures: Time to raise a red flag.

Poor sleep is a frequent complaint in patients with psychogenic nonepileptic seizures (PNES). However, few studies have examined sleep problems in this population. We aimed to compare sleep complaints in patients with PNES with those with epilepsy. Subjects diagnosed as having PNES by experts using video-electroencephalography (vEEG) were recruited through the Brigham and Women's Hospital epilepsy monitoring unit (EMU) between 3/25/2013 and 3/29/2018. Controls were patients with epilepsy recruited through the EMU and subspecialty clinics. All subjects were given the Beck Depression Inventory, 2nd Edition (BDI-II) and the Quality of Life in Epilepsy Inventory-10 (QOLIE-10). Subjective sleep problems were identified from item 16 (changes in sleep patterns) of the BDI-II. Independent sample t-test, chi-square test, and Spearman correlation were used. A total of 149 patients with PNES and 82 patients with epilepsy completed the BDI-II and QOLIE-10. Compared with control subjects with epilepsy, patients with PNES more frequently reported moderate-severe changes in sleep patterns, notably sleeping less than usual, waking up 1-2 h too early, and having trouble returning to sleep. These changes in sleep patterns were associated with worse quality of life. Our findings suggest that sleep is more commonly reported as a problem in PNES compared with epilepsy. Because sleep plays a major role in good health, understanding the specific sleep problem in PNES may provide insight for improving quality of life for this challenging disorder.

Nocturnal seizures are associated with more severe hypoxemia and increased risk of postictal generalized EEG suppression.

Patients with epilepsy have 20-fold risk of sudden death when compared to the general population. Uncontrolled seizures is the most consistent risk factor, and death often occurs at night or in relation to sleep. We examined seizure-related respiratory disturbances in sleep versus wakefulness, focusing on periictal oxygen saturation. Respiratory measures were examined in 48 recorded seizures (sleep, n = 23, wake, n = 25) from 20 adult patients with epilepsy. Seizures from sleep were associated with lower saturation, as compared to seizures from wakefulness, both during ictal (sleep median = 90.8, wake median = 95.5; p < 0.01) and postictal periods (sleep median = 94.3, wake median = 96.9; p = 0.05). Compared to wake-related seizures, seizures from sleep were also associated with a larger desaturation drop (sleep median = -4.2, wake median = -1.2; p = 0.01). Postictal generalized electroencephalography (EEG) suppression (PGES) occurred more frequently after seizures from sleep (39%), as compared to wake-related seizures (8%, p = 0.01). Our findings suggest that nocturnal seizures may entail a higher sudden unexpected death in epilepsy (SUDEP) severity burden, as they are associated with more severe and longer hypoxemia events, and more frequently followed by PGES, both factors implicated in sudden death.

Electroencephalographic prodromal markers of dementia across conscious states in Parkinson's disease.

In Parkinson's disease, electroencephalographic abnormalities during wakefulness and non-rapid eye movement sleep (spindles) were found to be predictive biomarkers of dementia. Because rapid eye movement sleep is regulated by the cholinergic system, which shows early degeneration in Parkinson's disease with cognitive impairment, anomalies during this sleep stage might mirror dementia development. In this prospective study, we examined baseline electroencephalographic absolute spectral power across three states of consciousness (non-rapid eye movement sleep, rapid eye movement sleep, and wakefulness) in 68 non-demented patients with Parkinson's disease and 44 healthy controls. All participants underwent baseline polysomnographic recordings and a comprehensive neuropsychological assessment. Power spectral analyses were performed on standard frequency bands. Dominant occipital frequency during wakefulness and ratios of slow-to-fast frequencies during rapid eye movement sleep and wakefulness were also computed. At follow-up (an average 4.5 years after baseline), 18 patients with Parkinson's disease had developed dementia and 50 patients remained dementia-free. In rapid eye movement sleep, patients with Parkinson's disease who later developed dementia showed, at baseline, higher absolute power in delta and theta bands and a higher slowing ratio, especially in temporal, parietal, and occipital regions, compared to patients who remained dementia-free and controls. In non-rapid eye movement sleep, lower baseline sigma power in parietal cortical regions also predicted development of dementia. During wakefulness, patients with Parkinson's disease who later developed dementia showed lower dominant occipital frequency as well as higher delta and slowing ratio compared to patients who remained dementia-free and controls. At baseline, higher slowing ratios in temporo-occipital regions during rapid eye movement sleep were associated with poor performance on visuospatial tests in patients with Parkinson's disease. Using receiver operating characteristic curves, we found that best predictors of dementia in Parkinson's disease were rapid eye movement sleep slowing ratios in posterior regions, wakefulness slowing ratios in temporal areas, and lower dominant occipital frequency. These results suggest that electroencephalographic slowing during sleep is a new promising predictive biomarker for Parkinson's disease dementia, perhaps as a marker of cholinergic denervation.

Patterns of cortical thinning in idiopathic rapid eye movement sleep behavior disorder.

Idiopathic rapid eye movement sleep behavior disorder is a parasomnia that is a risk factor for dementia with Lewy bodies and Parkinson's disease. Brain function impairments have been identified in this disorder, mainly in the frontal and posterior cortical regions. However, the anatomical support for these dysfunctions remains poorly understood. We investigated gray matter thickness, gray matter volume, and white matter integrity in patients with idiopathic rapid eye movement sleep behavior disorder. Twenty-four patients with polysomnography-confirmed idiopathic rapid eye movement sleep behavior disorder and 42 healthy individuals underwent a 3-tesla structural and diffusion magnetic resonance imaging examination using corticometry, voxel-based morphometry, and diffusion tensor imaging. In the patients with idiopathic rapid eye movement sleep behavior disorder, decreased cortical thickness was observed in the frontal cortex, the lingual gyrus, and the fusiform gyrus. Gray matter volume was reduced in the superior frontal sulcus only. Patients showed no increased gray matter thickness or volume. Diffusion tensor imaging analyses revealed no significant white matter differences between groups. Using corticometry in patients with idiopathic rapid eye movement sleep behavior disorder, several new cortical regions with gray matter alterations were identified, similar to those reported in dementia with Lewy bodies and Parkinson's disease. These findings provide some anatomical support for previously identified brain function impairments in this disorder.

Sleep spindles and rapid eye movement sleep as predictors of next morning cognitive performance in healthy middle-aged and older participants.

Spindles and slow waves are hallmarks of non-rapid eye movement sleep. Both these oscillations are markers of neuronal plasticity, and play a role in memory and cognition. Normal ageing is associated with spindle and slow wave decline and cognitive changes. The present study aimed to assess whether spindle and slow wave characteristics during a baseline night predict cognitive performance in healthy older adults the next morning. Specifically, we examined performance on tasks measuring selective and sustained visual attention, declarative verbal memory, working memory and verbal fluency. Fifty-eight healthy middle-aged and older adults (aged 50-91 years) without sleep disorders underwent baseline polysomnographic sleep recording followed by neuropsychological assessment the next morning. Spindles and slow waves were detected automatically on artefact-free non-rapid eye movement sleep electroencephalogram. All-night stage N2 spindle density (no./min) and mean frequency (Hz) and all-night non-rapid eye movement sleep slow wave density (no./min) and mean slope (µV/s) were analysed. Pearson's correlations were performed between spindles, slow waves, polysomnography and cognitive performance. Higher spindle density predicted better performance on verbal learning, visual attention and verbal fluency, whereas spindle frequency and slow wave density or slope predicted fewer cognitive performance variables. In addition, rapid eye movement sleep duration was associated with better verbal learning potential. These results suggest that spindle density is a marker of cognitive functioning in older adults and may reflect neuroanatomic integrity. Rapid eye movement sleep may be a marker of age-related changes in acetylcholine transmission, which plays a role in new information encoding.

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.

Rapid eye movement sleep behavior disorder and subtypes of Parkinson's disease.

Numerous studies have explored the potential relationship between rapid eye movement sleep behavior disorder (RBD) and manifestations of PD. Our aim was to perform an expanded extensive assessment of motor and nonmotor manifestations in PD to identify whether RBD was associated with differences in the nature and severity of these manifestations. PD patients underwent polysomnography (PSG) to diagnose the presence of RBD. Participants then underwent an extensive evaluation by a movement disorders specialist blinded to PSG results. Measures of disease severity, quantitative motor indices, motor subtypes, therapy complications, and autonomic, psychiatric, visual, and olfactory dysfunction were assessed and compared using regression analysis, adjusting for disease duration, age, and sex. Of 98 included patients, 54 had RBD and 44 did not. PD patients with RBD were older (P = 0.034) and were more likely to be male (P < 0.001). On regression analysis, the most consistent links between RBD and PD were a higher systolic blood pressure (BP) change while standing (-23.9 ± 13.9 versus -3.5 ± 10.9; P < 0.001), a higher orthostatic symptom score (0.89 ± 0.82 versus 0.44 ± 0.66; P = 0.003), and a higher frequency of freezing (43% versus 14%; P = 0.011). A systolic BP drop >10 could identify PD patients with RBD with 81% sensitivity and 86% specificity. In addition, there was a probable relationship between RBD and nontremor predominant subtype of PD (P = 0.04), increased frequency of falls (P = 0.009), and depression (P = 0.009). Our results support previous findings that RBD is a multifaceted phenomenon in PD. Patients with PD who have RBD tend to have specific motor and nonmotor manifestations, especially orthostatic hypotension.

Does epileptic activity impair sleep-related memory consolidation in epilepsy? A critical and systematic review.

STUDY OBJECTIVES: People with epilepsy often complain about disturbed sleep and cognitive impairment. Beyond seizures, the occurrence of interictal epileptic activity during sleep is also increasingly recognized to negatively impact cognitive functioning, including memory processes. The aim of this study was to critically review the effect of interictal epileptic activity on sleep-related memory consolidation. METHODS: PubMed and PsychINFO databases were systematically searched to identify experimental studies that investigated sleep-related memory consolidation and the relationships between sleep-related epileptic activity and memory in adults and children with epilepsy. This review also highlights hypotheses regarding the potential pathophysiological mechanisms. RESULTS: A total of 261 studies were identified; 27 of these met selection criteria. Only 13 studies prospectively assessed the effect of sleep on memory in epilepsy. Most studies reported no alteration of sleep-related memory consolidation in patients, with either similar retention levels following a period containing sleep (n = 5) or improved memory performance postsleep (n = 4). Two studies in children with epilepsy found impaired sleep-related memory consolidation. Ten studies, of which 6 were in childhood epilepsy syndromes, reported a debilitating effect of sleep-related epileptic activity on memory functioning. CONCLUSIONS: Conclusions from existing studies were hampered by small sample sizes, heterogeneous patient groups, and variations in memory assessment techniques. Overall, results to date preclude any definitive conclusions on the alteration of sleep-related memory consolidation in epilepsy. We discuss methodological considerations specific to people with epilepsy and provide suggestions on how to best investigate the relationship between epileptic activity, sleep, and memory consolidation in future studies. CITATION: Latreille V, Schiller K, Peter-Derex L, Frauscher B. Does epilepticimpair sleep-related memory consolidation in epilepsy? A critical and systematic review. J Clin Sleep Med. 2022;18(10):2481-2495.

Validity of the Mattis Dementia Rating Scale to detect mild cognitive impairment in Parkinson's disease and REM sleep behavior disorder.

BACKGROUND/AIMS: Mild cognitive impairment (MCI) is frequent in Parkinson's disease (PD) and idiopathic REM sleep behavior disorder (iRBD). However, only a few studies have evaluated the validity of brief cognitive measures to detect MCI in PD or iRBD using standard diagnostic criteria for MCI. Our aim was to evaluate the validity of the Mini-Mental State Examination (MMSE) and the Mattis Dementia Rating Scale (DRS-2) to detect MCI in PD and iRBD. METHODS: Forty PD patients and 34 iRBD patients were studied. Receiver operating characteristic curves were created for both tests to assess their effectiveness in identifying MCI in PD and iRBD. RESULTS: In PD, a normality cutoff of 138 on the DRS-2 yielded the best balance between sensitivity (72%) and specificity (86%) with a correct classification of 80%. In iRBD, the optimal normality cutoff was 141 on the DRS-2, with a sensitivity of 90%, a specificity of 71% and a correct classification of 82%. No cutoff for the MMSE was found to have acceptable sensitivity or specificity. CONCLUSION: The DRS-2 has satisfactory validity to detect MCI in PD or iRBD. The MMSE proved to be invalid as a screening test for MCI in both populations.

The Montreal Cognitive Assessment: a screening tool for mild cognitive impairment in REM sleep behavior disorder.

Mild cognitive impairment (MCI) is a frequent feature in idiopathic REM sleep behavior disorder (RBD), a sleep disturbance that can be a preclinical stage of Parkinson's disease or Lewy body dementia. We evaluated the sensitivity and specificity of two brief screening tools, the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), in detecting MCI in idiopathic RBD. Thirty-eight idiopathic RBD patients underwent a comprehensive neuropsychological assessment, including the MoCA and the MMSE. Receiver operating characteristic curves were created for the MoCA and the MMSE to assess their ability to identify MCI in idiopathic RBD patients, with neuropsychological assessment as the gold standard. For the MoCA, a normality cutoff of 26 yielded the best balance between sensitivity (76%) and specificity (85%) with a correct classification of 79%. For the MMSE, the optimal normality cutoff was 30, with a sensitivity of 84% and a specificity of 54% and a correct classification of 74%. The MoCA is superior to the MMSE in detecting MCI in idiopathic RBD patients, showing good sensitivity and very good specificity.

Sleep Disorders.

Sleep disorders are frequent and can have serious consequences on patients' health and quality of life. While some sleep disorders are more challenging to treat, most can be easily managed with adequate interventions. We review the main diagnostic features of 6 major sleep disorders (insomnia, circadian rhythm disorders, sleep-disordered breathing, hypersomnia/narcolepsy, parasomnias, and restless legs syndrome/periodic limb movement disorder) to aid medical practitioners in screening and treating sleep disorders as part of clinical practice.

Neuropsychological correlates of obstructive sleep apnea severity in patients with epilepsy.

Obstructive sleep apnea affects up to 30% of patients with epilepsy. As obstructive sleep apnea represents a clinical risk factor for cognitive deficits, its occurrence in epilepsy patients may exacerbate cognitive deficits associated with this condition. However, the cognitive burden of obstructive sleep apnea in epilepsy remains poorly understood. We conducted a retrospective record review of adults with epilepsy who underwent a polysomnography and a neuropsychological assessment at Brigham and Women's Hospital. We examined the relationship between obstructive sleep apnea severity and cognitive functioning, particularly attention/executive functions, memory, and processing speed in untreated obstructive sleep apnea patients with epilepsy. Twenty patients with epilepsy and mild-to-severe obstructive sleep apnea were included in the analyses. We found significant positive correlations between the oxygen saturation levels during rapid-eye-movement sleep and attention/executive tests (p<0.05), as well as time spent with saturation levels ≤90% and executive functioning (p=0.008). Similarly, worse verbal memory performances were associated with lower oxygen levels (p=0.003). In addition, more severe respiratory events during rapid-eye-movement sleep were associated with worse performances on attention tests (p=0.03). Our findings indicate that more severe obstructive sleep apnea-related hypoxemia during sleep is associated with poorer cognitive performances on tests that assess attention/executive functions and verbal memory in patients with epilepsy. Overall, these results are consistent with the sleep apnea literature, and suggest that patients with epilepsy are also vulnerable to the effects of obstructive sleep apnea. Future prospective studies will help in determining whether treatment of obstructive sleep apnea may help improve cognitive functioning in patients with epilepsy.

Sleep disturbances in patients with psychogenic non-epileptic seizures: Is it all subjective? A prospective pilot study of sleep-wake patterns.

PURPOSE: Patients with psychogenic non-epileptic seizures (PNES) frequently complain of poor sleep, yet there are few and inconsistent data supporting objective sleep disturbances in this population. In this prospective observational study, we aimed to compare objective and subjective sleep-wake patterns in patients with PNES with those with epilepsy. METHODS: Subjects were recruited through the Brigham and Women's Epilepsy Monitoring Unit (EMU) over a 6-month period, and were diagnosed as having PNES or epilepsy by experts using video-electroencephalography (v-EEG). Sleep-wake patterns were objectively examined using EEG and actigraphy during EMU admission. Subjects also completed several validated questionnaires on sleep. RESULTS: Twenty-seven subjects, including 17 with PNES and 10 with epilepsy were enrolled in the study. Compared to controls with epilepsy, PNES subjects showed greater sleep onset latency (48.7 ± 47.5 min vs 14.0 ± 13.4 min; p = 0.02). Otherwise, sleep architecture was similar between the groups. However, subjectively, PNES subjects reported worse sleep quality (10.8 ± 5.1 vs 5.8 ± 2.9; p = 0.01) and were more likely to meet clinical criteria for insomnia relative to epilepsy subjects (50% vs 10%, p = 0.05). Moreover, a higher proportion of PNES subjects reported taking medications for sleep (44% vs 0%, p = 0.01). CONCLUSION: Overall, we found more evidence for a subjective basis rather than a pathophysiological nature for the reported sleep disturbances in PNES subjects. In addition to educating PNES patients on the importance of maintaining good sleep habits, clinicians should address sleep complaints and screen for insomnia, as effective treatments are available and may improve overall health.

Age-related cortical signatures of human sleep electroencephalography.

Accumulating evidence demonstrates a direct relationship between impaired neural integrity and disrupted sleep physiology in normal and pathological aging. However, previous work has focus almost exclusively on nonrapid eye movement sleep electroencephalography as a proxy of cortical integrity with aging. Whether this relationship holds true for rapid eye movement sleep electroencephalography is unknown. Our results show that age-related reduction in low-frequency delta activity during both rapid eye movement and nonrapid eye movement sleep was statistically mediated by the thinning of the medial frontal and anterior cingulate cortices. These findings (1) support the potential role of the medial frontal and cingulate cortices, major hubs of the human brain, in synchronizing neuronal assemblies during sleep, and (2) suggest that, with age, a reduction in cortical integrity within this frontal network mediates the loss of delta power during sleep. Further work will determine whether cortical thinning and delta loss may interact and contribute to cognitive decline with aging.

Novel non-pharmacological insomnia treatment - a pilot study.

OBJECTIVE: The objective of this prospective pilot study was to examine the effects of a novel non-pharmacological device (BioBoosti) on insomnia symptoms in adults. METHODS: Subjects with chronic insomnia were instructed to hold the device in each hand for 8 mins for 6 cycles on a nightly basis for 2 weeks. Outcomes tested included standardized subjective sleep measures assessing sleep quality, insomnia symptoms, and daytime sleepiness. Sleep was objectively quantified using electroencephalogram (EEG) before and after 2 weeks of treatment with BioBoosti, and wrist actigraphy throughout the study. RESULTS: Twenty adults (mean age: 45.6±17.1 y/o; range 18-74 y/o) were enrolled in the study. No significant side effects were noted by any of the subjects. After 2 weeks of BioBoosti use, subjects reported improved sleep quality (Pittsburgh Sleep Quality Index: 12.6±3.3 versus 8.5±3.7, p=0.001) and reduced insomnia symptoms (Insomnia Severity Index: 18.2±5.2 versus 12.8±7.0, p<0.001). Sleepiness, as assessed by a visual analog scale, was significantly reduced after treatment (5.7±2.8 versus 4.0±3.3, p=0.03). CONCLUSION: BioBoosti use yielded an improvement in insomnia symptoms. Larger placebo-controlled studies are needed to fully assess efficacy.