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Altered sleep homeostasis correlates with cognitive impairment in patients with focal epilepsy.

ABSTRACT: In animal studies, both seizures and interictal spikes induce synaptic potentiation. Recent evidence suggests that electroencephalogram slow wave activity during sleep reflects synaptic potentiation during wake, and that its homeostatic decrease during the night is associated with synaptic renormalization and its beneficial effects. Here we asked whether epileptic activity induces plastic changes that can be revealed by high-density electroencephalography recordings during sleep in 15 patients with focal epilepsy and 15 control subjects. Compared to controls, patients with epilepsy displayed increased slow wave activity power during non-rapid eye movement sleep over widespread, bilateral scalp regions. This global increase in slow wave activity power was positively correlated with the frequency of secondarily generalized seizures in the 3-5 days preceding the recordings. Individual patients also showed local increases in sleep slow wave activity power at scalp locations matching their seizure focus. This local increase in slow wave activity power was positively correlated with the frequency of interictal spikes during the last hour of wakefulness preceding sleep. By contrast, frequent interictal spikes during non-rapid eye movement sleep predicted a reduced homeostatic decrease in the slope of sleep slow waves during the night, which in turn predicted reduced daytime learning. Patients also showed an increase in sleep spindle power, which was negatively correlated with intelligence quotient. Altogether, these findings suggest that both seizures and interictal spikes may induce long-lasting changes in the human brain that can be sensitively detected by electroencephalographic markers of sleep homeostasis. Furthermore, abnormalities in sleep markers are correlated with cognitive impairment, suggesting that not only seizures, but also interictal spikes can have negative consequences.

SUBMITTER: Boly M

PROVIDER: S-EPMC5837505 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Altered sleep homeostasis correlates with cognitive impairment in patients with focal epilepsy.

Boly Melanie M Jones Benjamin B Findlay Graham G Plumley Erin E Mensen Armand A Hermann Bruce B Tononi Guilio G Maganti Rama R

Brain : a journal of neurology 20170401 4

In animal studies, both seizures and interictal spikes induce synaptic potentiation. Recent evidence suggests that electroencephalogram slow wave activity during sleep reflects synaptic potentiation during wake, and that its homeostatic decrease during the night is associated with synaptic renormalization and its beneficial effects. Here we asked whether epileptic activity induces plastic changes that can be revealed by high-density electroencephalography recordings during sleep in 15 patients w ...[more]

PMID: 28334879

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Project description:Abstract Sleep can modulate epileptic activities, but our knowledge of sleep perturbation by epilepsy remains sparse. Interestingly, epilepsy and sleep both present with defining electrophysiological features in the form of specific graphoelements on EEG. This raises the possibility to identify, within ongoing EEG activity, how epilepsy impacts and disrupts sleep. Here, we asked whether the presence of a lateralized epileptic focus interferes with the expression of the dominant electrophysiological hallmarks of sleep: slow oscillations, slow waves and spindles. To this aim, we conducted a cross-sectional study and analysed sleep recordings with surface EEG from 69 patients with focal epilepsy (age range at EEG: 17–61 years, 29 females, 34 left focal epilepsy). Comparing patients with left and right focal epilepsy, we assessed inter-hemispheric asymmetry of sleep slow oscillations power (delta range, 0.5–4 Hz); sleep slow wave density; amplitude, duration and slope; and spindle density, amplitude, duration as well as locking to slow oscillations. We found significantly different asymmetries in slow oscillation power (P < 0.01); slow wave amplitude (P < 0.05) and slope (P < 0.01); and spindle density (P < 0.0001) and amplitude (P < 0.05). To confirm that these population-based differences reflect actual patient-by-patient differences, we then tested whether asymmetry of sleep features can classify laterality of the epileptic focus using a decision tree and a 5-fold cross-validation. We show that classification accuracy is above chance level (accuracy of 65%, standard deviation: 5%) and significantly outperforms a classification based on a randomization of epileptic lateralization (randomization data accuracy: 50%, standard deviation 7%, unpaired t-test, P < 0.0001). Importantly, we show that classification of epileptic lateralization by the canonical epileptic biomarker, i.e. interictal epileptiform discharges, improves slightly but significantly when combined with electrophysiological hallmarks of physiological sleep (from 75% to 77%, P < 0.0001, one-way ANOVA + Sidak’s multiple comparisons test). Together, we establish that epilepsy is associated with inter-hemispheric perturbation of sleep-related activities and provide an in-depth multi-dimensional profile of the main sleep electrophysiological signatures in a large cohort of patients with focal epilepsy. We provide converging evidence that the underlying epileptic process interacts with the expression of sleep markers, in addition to triggering well-known pathological activities, such as interictal epileptiform discharges. Sleep can modulate epilepsy, but we still lack a precise insight into how epilepsy affects sleep. Sheybani et al. show that sleep electrophysiological activities are asymmetrically expressed in patients with focal epilepsy, contributing to a better understanding of the interaction between epilepsy and normal brain network. Graphical Abstract Graphical abstract

Project description:ObjectiveCognitive comorbidities are common in epilepsy; however, symptomatic treatment is currently the only available effective therapy. Sleep, cognition, and epilepsy are closely associated. Therefore, many studies on epilepsy and cognition have focused on sleep structures, such as sleep spindles, which are considered windows to understanding the sleeping brain. This study aimed to investigate the relationship between sleep spindles and the severity of cognitive impairment in adult epilepsy.MethodsFifty-seven adults with epilepsy underwent overnight sleep electroencephalogram recordings and cognitive testing. Slow (9-12 Hz) and fast (12-15 Hz) spindle characteristics during N2 sleep were calculated using a convolutional neural network-based sleep staging system and automatic spindle detection algorithm. Repeated-measures analysis of variance was used to analyze differences in fast and slow spindle densities among subgroups of patients based on cognitive impairment severity.ResultsA significant between-group effect was observed for both slow and fast spindle densities. Multiple comparisons showed that slow and fast spindle densities of the severe cognitive impairment subgroup were lower than those of the noncognitive impairment subgroup (P < 0.05). Simple-effect analysis revealed differences in slow spindle density distributed among the EEG channels Fp1, Fp2, F3, C3, P4, O1, O2, F8, T4, T5, T6, Fz, and Cz (P < 0.05). Differences in fast spindle density were distributed among the channels Fp1, Fp2, F3, C3, O1, O2, F7, F8, T4, T5, T6, and Fz (P < 0.05).SignificanceSignificant differences in topographical distribution of fast and slow spindle densities were observed at the scalp level among patients with different cognitive statuses. Compared with patients with no cognitive impairment, those with severe cognitive impairment had lower slow and fast spindle densities over multiple scalp regions during N2 sleep. This study provides a reference for objective assessment of cognitive dysfunction in epilepsy patients.

Project description:OBJECTIVE:Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. METHODS:Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. RESULTS:We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p < 0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p < 0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p = 0.009; theta, p = 0.006, slow, p = 0.004) and parietal lobe (theta, p = 0.007, delta, p = 0.002, slow, p = 0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased. SIGNIFICANCE:Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ.

Project description:ObjectivesDisability in patients with epilepsy (PWEs) is multifactorial: beyond seizure frequency/severity, PWEs are prone to a range of neuropsychiatric, cognitive, and somatic comorbidities that significantly affect quality of life. Here, we explored how variations in seizure severity and the burden of self-reported somatic/neuropsychiatric symptoms correlate with disruptions to 24 h activity patterns (rest-activity rhythms [RARs]), determined through wrist accelerometry/actigraphy.MethodsMultiday wrist-actigraphy recordings were obtained from 59 adult patients with focal epilepsy (44% male, ages 18-72), who contemporaneously responded to validated psychometric instruments to measure anxiety, depression, sleepiness, and somatic symptoms. We conducted a similar in silico psychometric-actigraphic correlation in a publicly available data set of 1747 Hispanic subjects (35% male, ages 18-65) from the Study of Latinos (SOL) Sueño Ancillary Study. RARs were analyzed via a sigmoidally-transformed cosine model (quantifying amplitude, steepness, acrophase, and robustness) and nonparametric measures to estimate RAR stability, fragmentation, and sleep.ResultsCompared with matched SOL subjects, RARs from PWE subjects featured a significantly lower amplitude, a wider rest phase, and significantly more total daily sleep. Within PWEs, similar RAR distortions were associated with seizure intractability and/or anticonvulsant polytherapy, whereas high anxiety, depression, and somatic symptom scores were associated with lower RAR robustness and acrophase delay. We applied the SOL data set to train logistic regression models to dichotomously classify subjective anxiety, depression, and sleepiness symptoms using demographic and RAR parameters. When tested on PWEs, these models predicted prevalent anxiety and depression symptom burden (accuracy ~70%) but failed to predict subjective sleepiness.SignificanceTogether these results demonstrate that RAR features may encode prevalent depression and anxiety symptoms in patients with focal epilepsy, potentially offering wearable-derived endpoints to adjunct clinical care and drug/device trials. With larger PWE-specific actigraphic-psychometric data sets, we may identify RAR signatures that may more precisely correlate with varying seizure frequency, the burden of anticonvulsant therapy, and prevalent mood/anxiety symptoms.

Dataset Information

Altered sleep homeostasis correlates with cognitive impairment in patients with focal epilepsy.

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Altered sleep homeostasis correlates with cognitive impairment in patients with focal epilepsy.

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