Epileptic interictal discharges are more frequent during NREM slow wave downstates

Intracortical mechanisms of single pulse electrical stimulation (SPES) evoked excitations and inhibitions in humans

Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.

Pathological and Physiological High-frequency Oscillations on Electroencephalography in Patients with Epilepsy

High-frequency oscillations (HFOs) encompass ripples (80 Hz-200 Hz) and fast ripples (200 Hz-600 Hz), serving as a promising biomarker for localizing the epileptogenic zone in epilepsy. Spontaneous fast ripples are always pathological, while ripples may be physiological or pathological. Distinguishing physiological from pathological ripples is important not only for designating epileptogenic brain regions, but also for investigations that study ripples in the context of memory encoding, consolidation, and recall in patients with epilepsy. Many studies have sought to identify distinguishing features between pathological and physiological ripples over the past two decades. Physiological and pathological ripples differ with respect to their spatial location, cellular mechanisms, morphology, and coupling with background electroencephalographic activity. Retrospective studies have demonstrated that differentiating between pathological and physiological ripples can improve surgical outcome prediction. In this review, we summarize the characteristics, differences, and applications of pathological and physiological HFOs and discuss strategies for their clinical translation.

Widespread slow oscillations support interictal epileptiform discharge networks in focal epilepsy

Interictal epileptiform discharges (IEDs) often co-occur across spatially-separated cortical regions, forming IED networks. However, the factors prompting IED propagation remain unelucidated. We hypothesized that slow oscillations (SOs) might facilitate IED propagation. Here, the amplitude and phase synchronization of SOs preceding propagating and non-propagating IEDs were compared in 22 patients with focal epilepsy undergoing intracranial electroencephalography (EEG) evaluation. Intracranial channels were categorized into the irritative zone (IZ) and normal zone (NOZ) regarding the presence of IEDs. During wakefulness, we found that pre-IED SOs within the IZ exhibited higher amplitudes for propagating IEDs than non-propagating IEDs (delta band: p = 0.001, theta band: p < 0.001). This increase in SOs was also concurrently observed in the NOZ (delta band: p = 0.04). Similarly, the inter-channel phase synchronization of SOs prior to propagating IEDs was higher than those preceding non-propagating IEDs in the IZ (delta band: p = 0.04). Through sliding window analysis, we observed that SOs preceding propagating IEDs progressively increased in amplitude and phase synchronization, while those preceding non-propagating IEDs remained relatively stable. Significant differences in amplitude occurred approximately 1150 ms before IEDs. During non-rapid eye movement (NREM) sleep, SOs on scalp recordings also showed higher amplitudes before intracranial propagating IEDs than before non-propagating IEDs (delta band: p = 0.006). Furthermore, the analysis of IED density around sleep SOs revealed that only high-amplitude sleep SOs demonstrated correlation with IED propagation. Overall, our study highlights that transient but widely distributed SOs are associated with IED propagation as well as generation in focal epilepsy during sleep and wakefulness, providing new insight into the EEG substrate supporting IED networks.

Identification of epileptic networks with graph convolutional network incorporating oscillatory activities and evoked synaptic responses

Stereoelectroencephalography (SEEG) offers unique neural data from in-depth brain structures with fine temporal resolutions to better investigate the origin of epileptic brain activities. Although oscillatory patterns from different frequency bands and functional connectivity computed from the SEEG datasets are employed to study the epileptic zones, direct electrical stimulation-evoked electrophysiological recordings of synaptic responses, namely cortical-cortical evoked potentials (CCEPs), from the same SEEG electrodes are not explored for the localization of epileptic zones. Here we proposed a two-stream model with unsupervised learning and graph convolutional network tailored to the SEEG and CCEP datasets in individual patients to perform localization of epileptic zones. We compared our localization results with the clinically marked electrode sites determined for surgical resections. Our model had good classification capability when compared to other state-of-the-art methods. Furthermore, based on our prediction results we performed group-level brain-area mapping analysis for temporal, frontal and parietal epilepsy patients and found that epileptic and non-epileptic brain networks were distinct in patients with different types of focal epilepsy. Our unsupervised data-driven model provides personalized localization analysis for the epileptic zones. The epileptic and non-epileptic brain areas disclosed by the prediction model provide novel insights into the network-level pathological characteristics of epilepsy.

Latencies to the first interictal epileptiform discharges recorded by the electroencephalography in different epileptic patients

PURPOSE

Interictal epileptiform discharges (IEDs) captured in electroencephalography (EEG) have a high diagnostic value for epileptic patients. Extending the recording time may increase the possibility of obtaining IEDs. The purpose of our research was to determine how long it took for various epileptic individuals to receive their first IEDs.

METHODS

We retrospectively analyzed patients who were diagnosed with epilepsy and had no anti-seizure medications (ASMs) between September 2018 and March 2019 in the neurology department of the First Affiliated Hospital of Xi'an Jiaotong University. Each individual underwent a 24-h long-term video electroencephalographic monitoring (VEM) procedure. Clinical information including age, gender, age of seizure onset, frequency of seizures, the interval between last seizure and VEM, and results of neuroimaging were gathered. We also calculated the times from the start of the VEM to the first definite IEDs.

RESULTS

A total of 241 patients were examined, including 191 with focal-onset epilepsy and 50 with generalized epilepsy. In individuals with focal-onset epilepsy, the median latency to the first IED was 63.0 min (IQR 19.0-299.0 min), as compared to 30.0 min (IQR 12.5-62.0 min) in patients with generalized epilepsy (p < 0.001). The latency to the first IED is significantly related to the age of seizure onset (HR = 0.988, p = 0.049), the interval between last seizure and VEM (HR = 0.998, p = 0.013). But it is not correlated with seizure frequency, gender and age.

CONCLUSIONS

IEDs were discovered during 24-h EEG monitoring in 222/241(92.1%) of the epilepsy patients that were included. Compared to focal-onset epilepsy, generalized epilepsy demonstrated a much shorter latency to IED. Patients with late-onset epilepsy or those without recent episodes may require longer EEG monitoring periods.

Chloride ion dysregulation in epileptogenic neuronal networks

GABA is the major inhibitory neurotransmitter in the mature CNS. When GABA_A receptors are activated the membrane potential is driven towards hyperpolarization due to chloride entry into the neuron. However, chloride ion dysregulation that alters the ionic gradient can result in depolarizing GABAergic post-synaptic potentials instead. In this review, we highlight that GABAergic inhibition prevents and restrains focal seizures but then reexamine this notion in the context of evidence that a static and/or a dynamic chloride ion dysregulation, that increases intracellular chloride ion concentrations, promotes epileptiform activity and seizures. To reconcile these findings, we hypothesize that epileptogenic pathologically interconnected neuron (PIN) microcircuits, representing a small minority of neurons, exhibit static chloride dysregulation and should exhibit depolarizing inhibitory post-synaptic potentials (IPSPs). We speculate that chloride ion dysregulation and PIN cluster activation may generate fast ripples and epileptiform spikes as well as initiate the hypersynchronous seizure onset pattern and microseizures. Also, we discuss the genetic, molecular, and cellular players important in chloride dysregulation which regulate epileptogenesis and initiate the low-voltage fast seizure onset pattern. We conclude that chloride dysregulation in neuronal networks appears to be critical for epileptogenesis and seizure genesis, but feed-back and feed-forward inhibitory GABAergic neurotransmission plays an important role in preventing and restraining seizures as well.

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.

Myelination synchronizes cortical oscillations by consolidating parvalbumin-mediated phasic inhibition

Parvalbumin-positive (PV⁺) γ-aminobutyric acid (GABA) interneurons are critically involved in producing rapid network oscillations and cortical microcircuit computations, but the significance of PV⁺ axon myelination to the temporal features of inhibition remains elusive. Here, using toxic and genetic mouse models of demyelination and dysmyelination, respectively, we find that loss of compact myelin reduces PV⁺ interneuron presynaptic terminals and increases failures, and the weak phasic inhibition of pyramidal neurons abolishes optogenetically driven gamma oscillations in vivo. Strikingly, during behaviors of quiet wakefulness selectively theta rhythms are amplified and accompanied by highly synchronized interictal epileptic discharges. In support of a causal role of impaired PV-mediated inhibition, optogenetic activation of myelin-deficient PV⁺ interneurons attenuated the power of slow theta rhythms and limited interictal spike occurrence. Thus, myelination of PV axons is required to consolidate fast inhibition of pyramidal neurons and enable behavioral state-dependent modulation of local circuit synchronization.

Untangling a Web: Basic Mechanisms of the Complex Interactions Between Sleep, Circadian Rhythms, and Epilepsy

Seizures have sleep–wake and circadian patterns in various epilepsies and, in turn, disrupt sleep and circadian rhythms. The resultant sleep deprivation (SD) is an exacerbating factor for seizures that sets up a vicious cycle that can potentially lead to disease progression and even to epilepsy-related mortality. A variety of cellular or network electrophysiological changes and changes in expression of clock-controlled genes or other transcription factors underlie sleep–wake and circadian distribution of seizures, as well as the disruptions seen in both. A broad understanding of these mechanisms may help in designing better treatments to prevent SD-induced seizure exacerbation, disrupt the vicious cycle of disease progression, and reduce epilepsy-related mortality.

Interictal epileptiform discharges shape large-scale intercortical communication

Dynamic interactions between remote but functionally specialized brain regions enable complex information processing. This intercortical communication is disrupted in the neural networks of patients with focal epilepsy, and epileptic activity can exert widespread effects within the brain. Using large-scale human intracranial electroencephalography recordings, we show that interictal epileptiform discharges (IEDs) are significantly coupled with spindles in discrete, individualized brain regions outside of the epileptic network. We found that a substantial proportion of these localized spindles travel across the cortical surface. Brain regions that participate in this IED-driven oscillatory coupling express spindles that have a broader spatial extent and higher tendency to propagate than spindles occurring in uncoupled regions. These altered spatiotemporal oscillatory properties identify areas that are shaped by epileptic activity independent of IED or seizure detection. Our findings suggest that IED-spindle coupling may be an important mechanism of interictal global network dysfunction that could be targeted to prevent disruption of normal neural activity.

Epilepsy and Its Interaction With Sleep and Circadian Rhythm

Growing evidence shows the bidirectional interactions between sleep, circadian rhythm, and epilepsy. Comprehending how these interact with each other may help to advance our understanding of the pathophysiology of epilepsy and develop new treatment strategies to improve seizure control by reducing the medication side effects and the risks associated with seizures. In this review, we present the overview of different temporal patterns of interictal epileptiform discharges and epileptic seizures over a period of 24 consecutive hours. Furthermore, we discuss the underlying mechanism of the core-clock gene in periodic seizure occurrences. Finally, we outline the role of circadian patterns of seizures on seizure forecasting models and its implication for chronotherapy in epilepsy.

Strong relationship between NREM sleep, epilepsy and plastic functions - A conceptual review on the neurophysiology background

The aim of this review is to summarize and discuss the strong bond between NREM sleep and epilepsy underlain by the shared link and effect on brain plasticity. Beyond the seizure occurrence rate, sleep relatedness may manifest in the enhancement of interictal epileptic discharges (spikes and pathological ripples). The number of the discharges as well as their propagation increase during NREM sleep, unmasking the epileptic network that is hidden during wakefulness. The interictal epileptic discharges associate with different sleep constituents (sleep slow waves, spindling and high frequency oscillations); known to play essential role in memory and learning. We highlight three major groups of epilepsies, in which sleep-related plastic functions suffer an epileptic derailment. In absence epilepsy mainly involving the thalamo-cortical system, sleep spindles transform to generalized spike-wave activity. In mesio-temporal epilepsy affecting the hippocampal declarative memory system, the sharp wave ripples derail to dysfunctional epileptic oscillations (spikes and pathological ripples). Idiopathic childhood epilepsies affecting the perisylvian network may progress to catastrophic status electricus during NREM sleep. In these major epilepsies, NREM sleep has a pivotal role in the development and course of the disorder. Epilepsy is born in-, and exhibits its pathological properties during NREM sleep. Interictal discharges are important causative agents in this process.

The first-hour-of-the-day sleep EEG reliably identifies interictal epileptiform discharges during long-term video-EEG monitoring

PURPOSE

To determine the usefulness of the first-hour sleep EEG recording in identifying interictal epileptiform discharges (IEDs) during long-term video-EEG monitoring.

METHOD

We retrospectively reviewed 255 consecutive patients who underwent continuous long-term video-EEG monitoring in the adult epilepsy monitoring unit (EMU) at the University of Chicago. The complete video-EEG recording was reviewed, and the occurrence of IEDs was determined for each patient. We compared the occurrence of IEDs observed during the first-hour sleep EEG recordings with the occurrence of IEDs observed during the complete video-EEG recordings.

RESULTS

Overall, IEDs were observed in 134 (53%) of 255 patients during the full long-term video-EEG recording with a mean duration of 4 days. IEDs were identified in the first-hour sleep EEG in 125 (49%) of 225 patients. Comparing to reviewing full records, the first hour sleep EEG identified IEDs in 125 (93%) of 134 patients. Of the IED subtypes, the first-hour sleep EEG identified 92 (94%) of 98 patients with temporal lobe IEDs, 11 (92%) of 12 patients with frontal lobe IEDs, 3 (100%) of 3 patients with parietal lobe IEDs, 1(50%) of the 2 patients with occipital lobe IEDs, 16 (94%) of 17 patients with generalized IEDs, and 2 (100%) 2 patients with multi-focal IEDs.

CONCLUSIONS

The first-hour sleep EEG reliably predicts the occurrence of IEDs during the long-term video-EEG recording, and therefore can be a time-efficient tool for identifying patients with IEDs during long-term video-EEG recording in the adult epilepsy monitoring unit.