Do interictal spikes sustain seizures and epileptogenesis?

Detecting fast-ripples on both micro- and macro-electrodes in epilepsy: A wavelet-based CNN detector

BACKGROUND

Fast-ripples (FR) are short (∼10 ms) high-frequency oscillations (HFO) between 200 and 600 Hz that are helpful in epilepsy to identify the epileptogenic zone. Our aim is to propose a new method to detect FR that had to be efficient for intracerebral EEG (iEEG) recorded from both usual clinical macro-contacts (millimeter scale) and microwires (micrometer scale).

NEW METHOD

Step 1 of the detection method is based on a convolutional neural network (CNN) trained using a large database of > 11,000 FR recorded from the iEEG of 38 patients with epilepsy from both macro-contacts and microwires. The FR and non-FR events were fed to the CNN as normalized time-frequency maps. Step 2 is based on feature-based control techniques in order to reject false positives. In step 3, the human is reinstated in the decision-making process for final validation using a graphical user interface.

RESULTS

WALFRID achieved high performance on the realistically simulated data with sensitivity up to 99.95 % and precision up to 96.51 %. The detector was able to adapt to both macro and micro-EEG recordings. The real data was used without any pre-processing step such as artefact rejection. The precision of the automatic detection was of 57.5. Step 3 helped eliminating remaining false positives in a few minutes per subject.

COMPARISON WITH EXISTING METHODS

WALFRID performed as well or better than 6 other existing methods.

CONCLUSION

Since WALFRID was created to mimic the work-up of the neurologist, clinicians can easily use, understand, interpret and, if necessary, correct the output.

Involvement of the contralateral hippocampus in ictal-like but not interictal epileptic activities in the kainate mouse model of temporal lobe epilepsy

OBJECTIVE

Animal and human studies have shown that the seizure-generating region is vastly dependent on distant neuronal hubs that can decrease duration and propagation of ongoing seizures. However, we still lack a comprehensive understanding of the impact of distant brain areas on specific interictal and ictal epileptic activities (e.g., isolated spikes, spike trains, seizures). Such knowledge is critically needed, because all kinds of epileptic activities are not equivalent in terms of clinical expression and impact on the progression of the disease.

METHODS

We used surface high-density electroencephalography and multisite intracortical recordings, combined with pharmacological silencing of specific brain regions in the well-known kainate mouse model of temporal lobe epilepsy. We tested the impact of selective regional silencing on the generation of epileptic activities within a continuum ranging from very transient to more sustained and long-lasting discharges reminiscent of seizures.

RESULTS

Silencing the contralateral hippocampus completely suppresses sustained ictal activities in the focus, as efficiently as silencing the focus itself, but whereas focus silencing abolishes all focus activities, contralateral silencing fails to control transient spikes. In parallel, we observed that sustained focus epileptiform discharges in the focus are preceded by contralateral firing and more strongly phase-locked to bihippocampal delta/theta oscillations than transient spiking activities, reinforcing the presumed dominant role of the contralateral hippocampus in promoting long-lasting, but not transient, epileptic activities.

SIGNIFICANCE

Altogether, our work provides suggestive evidence that the contralateral hippocampus is necessary for the interictal to ictal state transition and proposes that crosstalk between contralateral neuronal activity and ipsilateral delta/theta oscillation could be a candidate mechanism underlying the progression from short- to long-lasting epileptic activities.

Generalisability of epileptiform patterns across time and patients

The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection failures in achieving seizure freedom. The distinct patterns of epileptiform activity during interictal and ictal phases, varying across patients, often lead to suboptimal localisation using electroencephalography (EEG) features. We posed two key questions: whether neural signals reflecting epileptogenicity generalise from interictal to ictal time windows within each patient, and whether epileptiform patterns generalise across patients. Utilising an intracranial EEG dataset from 55 patients, we extracted a large battery of simple to complex features from stereo-EEG (SEEG) and electrocorticographic (ECoG) neural signals during interictal and ictal windows. Our features (n = 34) quantified many aspects of the signals including statistical moments, complexities, frequency-domain and cross-channel network attributes. Decision tree classifiers were then trained and tested on distinct time windows and patients to evaluate the generalisability of epileptogenic patterns across time and patients, respectively. Evidence strongly supported generalisability from interictal to ictal time windows across patients, particularly in signal power and high-frequency network-based features. Consistent patterns of epileptogenicity were observed across time windows within most patients, and signal features of epileptogenic regions generalised across patients, with higher generalisability in the ictal window. Signal complexity features were particularly contributory in cross-patient generalisation across patients. These findings offer insights into generalisable features of epileptic neural activity across time and patients, with implications for future automated approaches to supplement other EZ localisation methods.

Interictal spikes in Alzheimer's disease: Preclinical evidence for dominance of the dentate gyrus and cholinergic control by the medial septum

Interictal spikes (IIS) are a common type of abnormal electrical activity in Alzheimer's disease (AD) and preclinical models. The brain regions where IIS are largest are not known but are important because such data would suggest sites that contribute to IIS generation. Because hippocampus and cortex exhibit altered excitability in AD models, we asked which areas dominate the activity during IIS along the cortical-CA1-dentate gyrus (DG) dorso-ventral axis. Because medial septal (MS) cholinergic neurons are overactive when IIS typically occur, we also tested the novel hypothesis that silencing the MS cholinergic neurons selectively would reduce IIS. We used mice that simulate aspects of AD: Tg2576 mice, presenilin 2 (PS2) knockout mice and Ts65Dn mice. To selectively silence MS cholinergic neurons, Tg2576 mice were bred with choline-acetyltransferase (ChAT)-Cre mice and offspring were injected in the MS with AAV encoding inhibitory designer receptors exclusively activated by designer drugs (DREADDs). We recorded local field potentials along the cortical-CA1-DG axis using silicon probes during wakefulness, slow-wave sleep (SWS) and rapid eye movement (REM) sleep. We detected IIS in all transgenic or knockout mice but not age-matched controls. IIS were detectable throughout the cortical-CA1-DG axis and occurred primarily during REM sleep. In all 3 mouse lines, IIS amplitudes were significantly greater in the DG granule cell layer vs. CA1 pyramidal layer or overlying cortex. Current source density analysis showed robust and early current sources in the DG, and additional sources in CA1 and the cortex also. Selective chemogenetic silencing of MS cholinergic neurons significantly reduced IIS rate during REM sleep without affecting the overall duration, number of REM bouts, latency to REM sleep, or theta power during REM. Notably, two control interventions showed no effects. Consistent maximal amplitude and strong current sources of IIS in the DG suggest that the DG is remarkably active during IIS. In addition, selectively reducing MS cholinergic tone, at times when MS is hyperactive, could be a new strategy to reduce IIS in AD.

Distinctive biophysical features of human cell-types: insights from studies of neurosurgically resected brain tissue

Electrophysiological characterization of live human tissue from epilepsy patients has been performed for many decades. Although initially these studies sought to understand the biophysical and synaptic changes associated with human epilepsy, recently, it has become the mainstay for exploring the distinctive biophysical and synaptic features of human cell-types. Both epochs of these human cellular electrophysiological explorations have faced criticism. Early studies revealed that cortical pyramidal neurons obtained from individuals with epilepsy appeared to function "normally" in comparison to neurons from non-epilepsy controls or neurons from other species and thus there was little to gain from the study of human neurons from epilepsy patients. On the other hand, contemporary studies are often questioned for the "normalcy" of the recorded neurons since they are derived from epilepsy patients. In this review, we discuss our current understanding of the distinct biophysical features of human cortical neurons and glia obtained from tissue removed from patients with epilepsy and tumors. We then explore the concept of within cell-type diversity and its loss (i.e., "neural homogenization"). We introduce neural homogenization to help reconcile the epileptogenicity of seemingly "normal" human cortical cells and circuits. We propose that there should be continued efforts to study cortical tissue from epilepsy patients in the quest to understand what makes human cell-types "human".

Interictal Spikes in Alzheimer's Disease: Preclinical Evidence for Dominance of the Dentate Gyrus and Cholinergic Control by Medial Septum

HIGHLIGHTS

Interictal spikes (IIS) occur in 3 mouse lines with Alzheimer's disease featuresIIS in all 3 mouse lines were most frequent during rapid eye movement (REM) sleepThe dentate gyrus showed larger IIS and earlier current sources vs. CA1 or cortexChemogenetic silencing of medial septum (MS) cholinergic neurons reduced IIS during REMMS silencing did not change REM latency, duration, number of bouts or theta power.

Interictal spikes (IIS) are a common type of abnormal electrical activity in Alzheimer's disease (AD) and preclinical models. The brain regions where IIS are largest are not known but are important because such data would suggest sites that contribute to IIS generation. Because hippocampus and cortex exhibit altered excitability in AD models, we asked which areas dominate the activity during IIS along the cortical-CA1-dentate gyrus (DG) dorso-ventral axis. Because medial septal (MS) cholinergic neurons are overactive when IIS typically occur, we also tested the novel hypothesis that silencing the MS cholinergic neurons selectively would reduce IIS.We used mice that simulate aspects of AD: Tg2576 mice, presenilin 2 (PS2) knockout mice and Ts65Dn mice. To selectively silence MS cholinergic neurons, Tg2576 mice were bred with choline-acetyltransferase (ChAT)-Cre mice and offspring were injected in the MS with AAV encoding inhibitory designer receptors exclusively activated by designer drugs (DREADDs). We recorded local field potentials along the cortical-CA1-DG axis using silicon probes during wakefulness, slow-wave sleep (SWS) and rapid eye movement (REM) sleep.We detected IIS in all transgenic or knockout mice but not age-matched controls. IIS were detectable throughout the cortical-CA1-DG axis and occurred primarily during REM sleep. In all 3 mouse lines, IIS amplitudes were significantly greater in the DG granule cell layer vs. CA1 pyramidal layer or overlying cortex. Current source density analysis showed robust and early current sources in the DG, and additional sources in CA1 and the cortex also. Selective chemogenetic silencing of MS cholinergic neurons significantly reduced IIS rate during REM sleep without affecting the overall duration, number of REM bouts, latency to REM sleep, or theta power during REM. Notably, two control interventions showed no effects.Consistent maximal amplitude and strong current sources of IIS in the DG suggest that the DG is remarkably active during IIS. In addition, selectively reducing MS cholinergic tone, at times when MS is hyperactive, could be a new strategy to reduce IIS in AD.

Of the Mechanisms of Paroxysmal Depolarization Shifts: Generation and Maintenance of Bicuculline-Induced Paroxysmal Activity in Rat Hippocampal Cell Cultures

Abnormal depolarization of neuronal membranes called paroxysmal depolarization shift (PDS) represents a cellular correlate of interictal spikes. The mechanisms underlying the generation of PDSs or PDS clusters remain obscure. This study aimed to investigate the role of ionotropic glutamate receptors (iGluRs) in the generation of PDS and dependence of the PDS pattern on neuronal membrane potential. We have shown that significant depolarization or hyperpolarization (by more than ±50 mV) of a single neuron does not change the number of individual PDSs in the cluster, indicating the involvement of an external stimulus in PDS induction. Based on this data, we have suggested reliable protocols for stimulating single PDS or PDS clusters. Furthermore, we have found that AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptors are necessary for PDS generation since AMPAR antagonist NBQX completely suppresses bicuculline-induced paroxysmal activity. In turn, antagonists of NMDA (N-methyl-D-aspartate) and kainate receptors (D-AP5 and UBP310, respectively) caused a decrease in the amplitude of the first action potential in PDSs and in the amplitude of the oscillations of intracellular Ca²⁺ concentration occurring alongside the PDS cluster generation. The effects of the NMDAR (NMDA receptor) and KAR (kainate receptor) antagonists indicate that these receptors are involved only in the modulation of paroxysmal activity. We have also shown that agonists of some G_i-coupled receptors, such as A₁ adenosine (A₁Rs) or cannabinoid receptors (CBRs) (N₆-cyclohexyladenosine and WIN 55,212-2, respectively), completely suppressed PDS generation, while the A₁R agonist even prevented it. We hypothesized that the dynamics of extracellular glutamate concentration govern paroxysmal activity. Fine-tuning of neuronal activity via action on G_i-coupled receptors or iGluRs paves the way for the development of new approaches for epilepsy pharmacotherapy.

Epileptiform activity influences theta-burst induced LTP in the adult hippocampus: a role for synaptic lipid raft disruption in early metaplasticity?

Non-epileptic seizures are identified as a common epileptogenic trigger. Early metaplasticity following seizures may contribute to epileptogenesis by abnormally altering synaptic strength and homeostatic plasticity. We now studied how in vitro epileptiform activity (EA) triggers early changes in CA1 long-term potentiation (LTP) induced by theta-burst stimulation (TBS) in rat hippocampal slices and the involvement of lipid rafts in these early metaplasticity events. Two forms of EA were induced: (1) interictal-like EA evoked by Mg²⁺ withdrawal and K⁺ elevation to 6 mM in the superfusion medium or (2) ictal-like EA induced by bicuculline (10 μM). Both EA patterns induced and LTP-like effect on CA1 synaptic transmission prior to LTP induction. LTP induced 30 min post EA was impaired, an effect more pronounced after ictal-like EA. LTP recovered to control levels 60 min post interictal-like EA but was still impaired 60 min after ictal-like EA. The synaptic molecular events underlying this altered LTP were investigated 30 min post EA in synaptosomes isolated from these slices. EA enhanced AMPA GluA1 Ser831 phosphorylation but decreased Ser845 phosphorylation and the GluA1/GluA2 ratio. Flotillin-1 and caveolin-1 were markedly decreased concomitantly with a marked increase in gephyrin levels and a less prominent increase in PSD-95. Altogether, EA differentially influences hippocampal CA1 LTP thorough regulation of GluA1/GluA2 levels and AMPA GluA1 phosphorylation suggesting that altered LTP post-seizures is a relevant target for antiepileptogenic therapies. In addition, this metaplasticity is also associated with marked alterations in classic and synaptic lipid raft markers, suggesting these may also constitute promising targets in epileptogenesis prevention.

Acute effect of antiseizure drugs on background oscillations in Scn1aA1783V Dravet syndrome mouse model

Dravet syndrome (Dravet) is a rare and severe form of developmental epileptic encephalopathy. Antiseizure medications (ASMs) for Dravet patients include valproic acid (VA) or clobazam (CLB), with or without stiripentol (STP), while sodium channel blockers like carbamazepine (CBZ) or lamotrigine (LTG) are contraindicated. In addition to their effect on epileptic phenotypes, ASMs were shown to modify the properties of background neuronal activity. Nevertheless, little is known about these background properties alterations in Dravet. Here, utilizing Dravet mice (DS, Scn1aA1783V/WT), we tested the acute effect of several ASMs on background electrocorticography (ECoG) activity and frequency of interictal spikes. Compared to wild-type mice, background ECoG activity in DS mice had lower power and reduced phase coherence, which was not corrected by any of the tested ASMs. However, acute administration of Dravet-recommended drugs, VA, CLB, or a combination of CLB + STP, caused, in most mice, a reduction in the frequency of interictal spikes, alongside an increase in the relative contribution of the beta frequency band. Conversely, CBZ and LTG increased the frequency of interictal spikes, with no effect on background spectral properties. Moreover, we uncovered a correlation between the reduction in interictal spike frequency, the drug-induced effect on the power of background activity, and a spectral shift toward higher frequency bands. Together, these data provide a comprehensive analysis of the effect of selected ASMs on the properties of background neuronal oscillations, and highlight a possible correlation between their effect on epilepsy and background activity.

Evolution of interictal activity in models of mesial temporal lobe epilepsy

Interictal activity and seizures are the hallmarks of focal epileptic disorders (which include mesial temporal lobe epilepsy, MTLE) in humans and in animal models. Interictal activity, which is recorded with cortical and intracerebral EEG recordings, comprises spikes, sharp waves and high-frequency oscillations, and has been used in clinical practice to identify the epileptic zone. However, its relation with seizures remains debated. Moreover, it is unclear whether specific EEG changes in interictal activity occur during the time preceding the appearance of spontaneous seizures. This period, which is termed "latent", has been studied in rodent models of MTLE in which spontaneous seizures start to occur following an initial insult (most often a status epilepticus induced by convulsive drugs such as kainic acid or pilocarpine) and may mirror epileptogenesis, i.e., the process leading the brain to develop an enduring predisposition to seizure generation. Here, we will address this topic by reviewing experimental studies performed in MTLE models. Specifically, we will review data highlighting the dynamic changes in interictal spiking activity and high-frequency oscillations occurring during the latent period, and how optogenetic stimulation of specific cell populations can modulate them in the pilocarpine model. These findings indicate that interictal activity: (i) is heterogeneous in its EEG patterns and thus, presumably, in its underlying neuronal mechanisms; and (ii) can pinpoint to the epileptogenic processes occurring in focal epileptic disorders in animal models and, perhaps, in epileptic patients.

Diverse nature of interictal oscillations: EEG-based biomarkers in epilepsy

Interictal electroencephalogram (EEG) patterns, including high-frequency oscillations (HFOs), interictal spikes (ISs), and slow wave activities (SWAs), are defined as specific oscillations between seizure events. These interictal oscillations reflect specific dynamic changes in network excitability and play various roles in epilepsy. In this review, we briefly describe the electrographic characteristics of HFOs, ISs, and SWAs in the interictal state, and discuss the underlying cellular and network mechanisms. We also summarize representative evidence from experimental and clinical epilepsy to address their critical roles in ictogenesis and epileptogenesis, indicating their potential as electrophysiological biomarkers of epilepsy. Importantly, we put forwards some perspectives for further research in the field.

Subthreshold repetitive transcranial magnetic stimulation suppresses ketamine-induced poly population spikes in rat sensorimotor cortex

Cortical oscillations within or across brain regions play fundamental roles in sensory, motor, and memory functions. It can be altered by neuromodulations such as repetitive transcranial magnetic stimulation (rTMS) and pharmacological manipulations such as ketamine. However, the neurobiological basis of the effects of rTMS and ketamine, as well as their interactions, on cortical oscillations is not understood. In this study, we developed and applied a rodent model that enabled simultaneous rTMS treatment, pharmacological manipulations, and invasive electrophysiological recordings, which is difficult in humans. Specifically, a miniaturized C-shaped coil was designed and fabricated to deliver focal subthreshold rTMS above the primary somatosensory (S1) and motor (M1) cortex in rats. Multi-electrode arrays (MEA) were implanted to record local field potentials (LFPs) and single unit activities. A novel form of synchronized activities, poly population spikes (PPS), was discovered as the biomarker of ketamine in LFPs. Brief subthreshold rTMS effectively and reversibly suppressed PPS while increasing the firing rates of single unit activities. These results suggest that ketamine and rTMS have convergent but opposing effects on cortical oscillations and circuits. This highly robust phenomenon has important implications to understanding the neurobiological mechanisms of rTMS and ketamine as well as developing new therapeutic strategies involving both neuromodulation and pharmacological agents.

Group I metabotropic glutamate receptors contribute to the antiepileptic effect of electrical stimulation in hippocampal CA1 pyramidal neurons

Low-frequency deep brain stimulation (LFS) inhibits neuronal hyperexcitability during epilepsy. Accordingly, the use of LFS as a treatment method for patients with drug-resistant epilepsy has been proposed. However, the LFS antiepileptic mechanisms are not fully understood. Here, the role of metabotropic glutamate receptors group I (mGluR I) in LFS inhibitory action on epileptiform activity (EA) was investigated. EA was induced by increasing the K⁺ concentration in artificial cerebrospinal fluid (ACSF) up to 12 mM in hippocampal slices of male Wistar rats. LFS (1 Hz, 900 pulses) was delivered to the bundles of Schaffer collaterals at the beginning of EA. The excitability of CA1 pyramidal neurons was assayed by intracellular whole-cell recording. Applying LFS reduced the firing frequency during EA and substantially moved the membrane potential toward repolarization after a high-K⁺ ACSF washout. In addition, LFS attenuated the EA-generated neuronal hyperexcitability. A blockade of both mGluR 1 and mGluR 5 prevented the inhibitory action of LFS on EA-generated neuronal hyperexcitability. Activation of mGluR I mimicked the LFS effects and had similar inhibitory action on excitability of CA1 pyramidal neurons following EA. However, mGluR I agonist's antiepileptic action was not as strong as LFS. The observed LFS effects were significantly attenuated in the presence of a PKC inhibitor. Altogether, the LFS' inhibitory action on neuronal hyperexcitability following EA relies, in part, on the activity of mGluR I and a PKC-related signaling pathway.

AiED: Artificial intelligence for the detection of intracranial interictal epileptiform discharges

OBJECTIVE

Deep learning provides an appealing solution for the ongoing challenge of automatically classifying intracranial interictal epileptiform discharges (IEDs). We report results from an automated method consisting of a template-matching algorithm and convolutional neural network (CNN) for the detection of intracranial IEDs ("AiED").

METHODS

1000 intracranial electroencephalogram (EEG) epochs extracted randomly from 307 subjects with refractory epilepsy were annotated independently by two expert neurophysiologists. These annotated epochs were divided into 1062 two-second epochs with IEDs and 1428 two-second epochs without IEDs, which were transformed into spectrograms prior to training the neural network. The highest performing network was validated on an annotated external test set.

RESULTS

The final network had an F1-score of 0.95 (95% CI: 0.91-0.98) and an average Area Under the Receiver Operating Characteristic of 0.98 (95% CI: 0.96-1.00). For the external test set, it showed an overall F1-score of 0.71, correctly identifying 100% of all high-amplitude IED complexes, 96.23% of all high-amplitude isolated IEDs, and 66.15% of all IEDs of atypical morphology.

CONCLUSIONS

Template-matching combined with a CNN offers a fast, robust method for detecting intracranial IEDs.

SIGNIFICANCE

"AiED" is generalizable and achieves comparable performance to human reviewers; it may support clinical and research EEG analyses.

Leveraging electrophysiologic correlates of word encoding to map seizure onset zone in focal epilepsy: Task-dependent changes in epileptiform activity, spectral features, and functional connectivity

OBJECTIVE

Verbal memory dysfunction is common in focal, drug-resistant epilepsy (DRE). Unfortunately, surgical removal of seizure-generating brain tissue can be associated with further memory decline. Therefore, localization of both the circuits generating seizures and those underlying cognitive functions is critical in presurgical evaluations for patients who may be candidates for resective surgery. We used intracranial electroencephalographic (iEEG) recordings during a verbal memory task to investigate word encoding in focal epilepsy. We hypothesized that engagement in a memory task would exaggerate local iEEG feature differences between the seizure onset zone (SOZ) and neighboring tissue as compared to wakeful rest ("nontask").

METHODS

Ten participants undergoing presurgical iEEG evaluation for DRE performed a free recall verbal memory task. We evaluated three iEEG features in SOZ and non-SOZ electrodes during successful word encoding and compared them with nontask recordings: interictal epileptiform spike (IES) rates, power in band (PIB), and relative entropy (REN; a functional connectivity measure).

RESULTS

We found a complex pattern of PIB and REN changes in SOZ and non-SOZ electrodes during successful word encoding compared to nontask. Successful word encoding was associated with a reduction in local electrographic functional connectivity (increased REN), which was most exaggerated in temporal lobe SOZ. The IES rates were reduced during task, but only in the non-SOZ electrodes. Compared with nontask, REN features during task yielded marginal improvements in SOZ classification.

SIGNIFICANCE

Previous studies have supported REN as a biomarker for epileptic brain. We show that REN differences between SOZ and non-SOZ are enhanced during a verbal memory task. We also show that IESs are reduced during task in non-SOZ, but not in SOZ. These findings support the hypothesis that SOZ and non-SOZ respond differently to task and warrant further exploration into the use of cognitive tasks to identify functioning memory circuits and localize SOZ.

Musical components important for the Mozart K448 effect in epilepsy

There is growing evidence for the efficacy of music, specifically Mozart’s Sonata for Two Pianos in D Major (K448), at reducing ictal and interictal epileptiform activity. Nonetheless, little is known about the mechanism underlying this beneficial “Mozart K448 effect” for persons with epilepsy. Here, we measured the influence that K448 had on intracranial interictal epileptiform discharges (IEDs) in sixteen subjects undergoing intracranial monitoring for refractory focal epilepsy. We found reduced IEDs during the original version of K448 after at least 30-s of exposure. Nonsignificant IED rate reductions were witnessed in all brain regions apart from the bilateral frontal cortices, where we observed increased frontal theta power during transitions from prolonged musical segments. All other presented musical stimuli were associated with nonsignificant IED alterations. These results suggest that the “Mozart K448 effect” is dependent on the duration of exposure and may preferentially modulate activity in frontal emotional networks, providing insight into the mechanism underlying this response. Our findings encourage the continued evaluation of Mozart’s K448 as a noninvasive, non-pharmacological intervention for refractory epilepsy.

Slow oscillations open susceptible time windows for epileptic discharges

Objective

In patients with epilepsy, interictal epileptic discharges are a diagnostic hallmark of epilepsy and represent abnormal, so‐called “irritative” activity that disrupts normal cognitive functions. Despite their clinical relevance, their mechanisms of generation remain poorly understood. It is assumed that brain activity switches abruptly, unpredictably, and supposedly randomly to these epileptic transients. We aim to study the period preceding these epileptic discharges, to extract potential proepileptogenic mechanisms supporting their expression.

Methods

We used multisite intracortical recordings from patients who underwent intracranial monitoring for refractory epilepsy, the majority of whom had a mesial temporal lobe seizure onset zone. Our objective was to evaluate the existence of proepileptogenic windows before interictal epileptic discharges. We tested whether the amplitude and phase synchronization of slow oscillations (.5–4 Hz and 4–7 Hz) increase before epileptic discharges and whether the latter are phase‐locked to slow oscillations. Then, we tested whether the phase‐locking of neuronal activity (assessed by high‐gamma activity, 60–160 Hz) to slow oscillations increases before epileptic discharges to provide a potential mechanism linking slow oscillations to interictal activities.

Results

Changes in widespread slow oscillations anticipate upcoming epileptic discharges. The network extends beyond the irritative zone, but the increase in amplitude and phase synchronization is rather specific to the irritative zone. In contrast, epileptic discharges are phase‐locked to widespread slow oscillations and the degree of phase‐locking tends to be higher outside the irritative zone. Then, within the irritative zone only, we observe an increased coupling between slow oscillations and neuronal discharges before epileptic discharges.

Significance

Our results show that epileptic discharges occur during vulnerable time windows set up by a specific phase of slow oscillations. The specificity of these permissive windows is further reinforced by the increased coupling of neuronal activity to slow oscillations. These findings contribute to our understanding of epilepsy as a distributed oscillopathy and open avenues for future neuromodulation strategies aiming at disrupting proepileptic mechanisms.

Modulation in time of the interictal spiking pattern related to epileptic seizures

OBJECTIVE

To test the hypothesis that significant changes in the occurrence of interictal epileptiform electroencephalography (EEG) discharges (EDs) are associated with seizures: while some EDs are pro-convulsive, increasing at seizure-occurrence, others are protective, showing decrease related to seizures.

METHODS

We analyzed 102 consecutive, long-term video-EEG monitoring sessions, from 98 patients. Using a semi-automated spike-detection method, we quantified the occurrence of EDs, grouped according to their location and morphology (clusters) and we constructed graphical representation of data, showing changes in time of the spiking patterns (spike-histograms). We compared the spike-histograms with the time-points of the seizures (pre-, peri- and postictal changes).

RESULTS

Totally 179 ED-clusters were identified. Modulation of the spiking pattern, associated with seizures, was observed in 66 clusters (37%), from 47 patients (48%). Most of these changes (40 clusters; 61%) were related to increase in the spiking-pattern.

CONCLUSIONS

Changes in spiking-pattern were associated with more than one third of the EDs. Both increasing and decreasing patterns were observed.

SIGNIFICANCE

EDs are more often pro-convulsive, with increasing spiking patterns associated with seizures. However, in more than one third of the ED clusters modulated by seizures, the spiking pattern decreased, raising the possibility of an anticonvulsive function of these discharges.

Morphological Description of Frontal EEG Interictal and Ictal Discharges in an Adult Cohort of 175 Patients

Clinical and electroencephalogram (EEG) features in frontal lobe epilepsy (FLE) vary considerably among patients, making the diagnosis a challenge. The objective of this study was to describe interictal and ictal EEG activity, identifying variables that could help to differentiate and diagnose frontal lobe epilepsy cases. A prospective cross-sectional study from patients with frontal interictal epileptiform discharges (IED) referred to the Vall d’Hebron University Hospital (Barcelona, Spain) after a clinical event compatible with epileptic seizures was designed. The interictal and ictal activity were analyzed to provide a detailed EEG description of the cases, using different statistical analyses. The morphological seizure pattern at the ictal onset remained globally unchanged over time in seizures arising from the frontal lobe for each patient. Isolated sharp waves were the most frequent waveforms in the expression of IED. Frontal lobe seizures are frequently short and sometimes appear grouped in clusters within the same recording. Often the ictal expression of the electrical activity in frontal lobe seizure is subtle and challenging to interpret. A description of the main findings is summarized to identify seizures arising from the frontal lobe and avoid false negatives findings in EEG interpretations.

Measuring synchrony in bio-medical timeseries

Paroxysms are sudden, unpredictable, short-lived events that abound in physiological processes and pathological disorders, from cellular functions (e.g., hormone secretion and neuronal firing) to life-threatening attacks (e.g., cardiac arrhythmia, epileptic seizures, and diabetic ketoacidosis). With the increasing use of personal chronic monitoring (e.g., electrocardiography, electroencephalography, and glucose monitors), the discovery of cycles in health and disease, and the emerging possibility of forecasting paroxysms, the need for suitable methods to evaluate synchrony-or phase-clustering-between events and related underlying physiological fluctuations is pressing. Here, based on examples in epilepsy, where seizures occur preferentially in certain brain states, we characterize different methods that evaluate synchrony in a controlled timeseries simulation framework. First, we compare two methods for extracting the phase of event occurrence and deriving the phase-locking value, a measure of synchrony: (M1) fitting cycles of fixed period-length vs (M2) deriving continuous cycles from a biomarker. In our simulations, M2 provides stronger evidence for cycles. Second, by systematically testing the sensitivity of both methods to non-stationarity in the underlying cycle, we show that M2 is more robust. Third, we characterize errors in circular statistics applied to timeseries with different degrees of temporal clustering and tested with different strategies: Rayleigh test, Poisson simulations, and surrogate timeseries. Using epilepsy data from 21 human subjects, we show the superiority of testing against surrogate time-series to minimize false positives and false negatives, especially when used in combination with M1. In conclusion, we show that only time frequency analysis of continuous recordings of a related bio-marker reveals the full extent of cyclical behavior in events. Identifying and forecasting cycles in biomedical timeseries will benefit from recordings using emerging wearable and implantable devices, so long as conclusions are based on conservative statistical testing.

Under-sampling in epilepsy: Limitations of conventional EEG

The cyclical structure of epilepsy was recently (re)-discovered through years-long intracranial electroencephalography (EEG) obtained with implanted devices. In this review, we discuss how new revelations from chronic EEG relate to the practice and interpretation of conventional EEG. We argue for an electrographic definition of seizures and highlight the caveats of counting epileptiform discharges in EEG recordings of short duration. Limitations of conventional EEG have practical implications with regard to titrating anti-seizure medications and allowing patients to drive, and we propose that chronic monitoring of brain activity could greatly improve epilepsy care. An impending paradigm shift in epilepsy will involve using next-generation devices for chronic EEG to leverage known biomarkers of disease state.

Dynamic analysis of fMRI activation during epileptic spikes can help identify the seizure origin

OBJECTIVE

We use the dynamic electroencephalography-functional magnetic resonance imaging (EEG-fMRI) method to incorporate variability in the amplitude and field of the interictal epileptic discharges (IEDs) into the fMRI analysis. We ask whether IED variability analysis can (a) identify additional activated brain regions during the course of IEDs, not seen in standard analysis; and (b) demonstrate the origin and spread of epileptic activity. We explore whether these functional changes recapitulate the structural connections and propagation of epileptic activity during seizures.

METHODS

Seventeen patients with focal epilepsy and at least 30 IEDs of a single type during simultaneous EEG-fMRI were studied. IED variability and EEG source imaging (ESI) analysis extracted time-varying dynamic changes. General linear modeling (GLM) generated static functional maps. Dynamic maps were compared to static functional maps. The dynamic sequence from IED variability was compared to the ESI results. In a subset of patients, we investigated structural connections between active brain regions using diffusion-based fiber tractography.

RESULTS

IED variability distinguished the origin of epileptic activity from its propagation in 15 of 17 (88%) patients. This included two cases where no result was obtained from the standard GLM analysis. In both of these cases, IED variability revealed activation in line with the presumed epileptic focus. Two cases showed no result from either method. Both had very high spike rates associated with dysplasia in the postcentral gyrus. In all 15 cases with dynamic activation, the observed dynamics were concordant with ESI. Fiber tractography identified specific white matter pathways between brain regions that were active at IED onset and propagation.

SIGNIFICANCE

Dynamic techniques involving IED variability can provide additional power for EEG-fMRI analysis, compared to standard analysis, revealing additional biologically plausible information in cases with no result from the standard analysis and gives insight into the origin and spread of IEDs.

Early seizure spread and epilepsy surgery: A systematic review

OBJECTIVE

A fundamental question in epilepsy surgery is how to delineate the margins of cortex that must be resected to result in seizure freedom. Whether and which areas showing seizure activity early in ictus must be removed to avoid postoperative recurrence of seizures is an area of ongoing research. Seizure spread dynamics in the initial seconds of ictus are often correlated with postoperative outcome; there is neither a consensus definition of early spread nor a concise summary of the existing literature linking seizure spread to postsurgical seizure outcomes. The present study is intended to summarize the literature that links seizure spread to postoperative seizure outcome and to provide a framework for quantitative assessment of early seizure spread.

METHODS

A systematic review was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A Medline search identified clinical studies reporting data on seizure spread measured by intracranial electrodes, having at least 10 subjects and reporting at least 1-year postoperative outcome in the English literature from 1990 to 2019. Studies were evaluated regarding support for a primary hypothesis: Areas of early seizure spread represent cortex with seizure-generating potential.

RESULTS

The search yielded 4562 studies: 15 studies met inclusion criteria and 7 studies supported the primary hypothesis. The methods and metrics used to describe seizure spread were heterogenous. The timeframe of seizure spread associated with seizure outcome ranged from 1-14 seconds, with large, well-designed, retrospective studies pointing to 3-10 seconds as most likely to provide meaningful correlates of postoperative seizure freedom.

SIGNIFICANCE

The complex correlation between electrophysiologic seizure spread and the potential for seizure generation needs further elucidation. Prospective cohort studies or trials are needed to evaluate epilepsy surgery targeting cortex involved in the first 3-10 seconds of ictus.

Spatio-temporal dynamics of interictal activity in musicogenic epilepsy: Two case reports and a systematic review of the literature

OBJECTIVE

To explore neurophysiological features of musicogenic epilepsy (ME), discussing experimental findings in the framework of a systematic review on ME.

METHODS

Two patients with ME underwent high-density-electroencephalography (hd-EEG) while listening to ictogenic songs. In one case, musicogenic seizures were elicited. Independent component analysis (ICA) was applied to hd-EEG, and components hosting interictal and ictal elements were identified and localized. Finally, the temporal dynamics of spike-density was studied relative to seizures. All findings were compared against the results of a systematic review on ME, collecting 131 cases.

RESULTS

Interictal spikes appeared isolated in specific fronto-temporal independent components, whose cortical generators were located in the anterior temporal and inferior frontal lobe. In the patient undergoing seizure, ictal discharge relied in the same component, with the interictal spike-density decreasing before the seizure onset.

CONCLUSION

Our study shows how ICA can isolate neurophysiological features of ictal and interictal discharges in ME, highlighting a fronto-temporal localization and a suppression of spike-density preceding the seizure onset.

SIGNIFICANCE

While the localization of ME activity could indicate which aspect within the musical stimulus might trigger musicogenic seizures for each patient, the study of ME dynamics could contribute to the development of models for seizure-prediction and their validation.

The Significance of Interictal Spike Frequency in Temporal Lobe Epilepsy

Purpose. In this study, the frequency of interictal epileptiform discharges (IEDs) in patients with drug-resistant temporal lobe epilepsy (TLE) was measured to determine its correlation with epilepsy duration, seizure frequency, brain magnetic resonance imaging (MRI) findings, and recent occurrence of focal to bilateral tonic clonic seizures (FBTCS). Methods. Our study was performed on TLE patients, who admitted to epilepsy monitoring unit of Loghman-Hakim hospital, Tehran, from 2016 to 2018. The patients' IEDs frequency were measured from their scalp EEG recording during no-rapid eye movement (NREM) sleep. The IEDs frequency was classified into 3 groups of rare, occasional, and frequent. Results. A total of 142 patients, with the mean age of 33.95 ± 12.73 years, were included in the study. The patients' mean epilepsy duration was 17.27 ± 12.19 years and the mean seizure frequency was 10.56 ± 12.95 attacks per month. The mean IEDs frequency was 123.48 ± 513.01 per hour. Thirty-five (24.6%) patients had history of FBTCS in the past year. Our findings revealed no significant association between IEDs frequency with epilepsy duration (P = .22), the recent occurrence of FBTCS (P = .42), and the type of MRI abnormalities (P = .66). There was only a weak positive correlation between seizure frequency and interictal spike density (r = 0.2, P = .007). Conclusions. In patients with TLE, standard EEG recording may not be a reliable method to predict the probability of occurring future seizures.

Ongoing intracortical neural activity predicts upcoming interictal epileptiform discharges in human epilepsy

Interictal epileptiform discharges (IEDs) are a hallmark of focal epilepsies. Most previous studies have focused on whether IED events increase seizure likelihood or, on the contrary, act as a protective mechanism. Here, we study instead whether IED events themselves can be predicted based on measured ongoing neural activity. We examined local field potentials (LFPs) and multi-unit activity (MUA) recorded via intracortical 10 × 10 (4 × 4 mm) arrays implanted in two patients with pharmacologically resistant seizures. Seizures in one patient (P1) were characterized by low-voltage fast-activity (LVFA), and IEDs occurred as isolated (100 - 200 ms) spike-wave events. In the other patient (P2), seizures were characterized by complex spike-wave discharges (2 - 3 Hz) and IEDs consisted of bursts of ~ 2 - 3 spike-wave discharges each lasting ~ 300 - 500 ms. We used extreme gradient boosting (XGBoost) classifiers for IED prediction. Inputs to the classifiers consisted of LFP power spectra; In addition, counts of MUA (1-ms and 100-ms time bins) and envelope, as well as leading eigenvalues/eigenvectors of MUA correlation matrices were used as features. Features were computed from moving short-time windows (1 second) immediately preceding IED events (0.3 - 0.5 preictal gap). Classifiers allowed successful IED prediction in both patients, with better results in the case of IED occurring in the LVFA case (area under ROC curve: 0.86). In comparison, LFP features performed comparatively for P1 datasets, while MUA appeared not predictive in the case of P2. Our preliminary results suggest that features of ongoing activity, predictive of upcoming IED events, can be identified based on intracortical recordings, and warrant further investigation in larger datasets. We expect this type of prediction analyses to contribute to a better understanding of the mechanisms underlying the generation of IED events and their contribution to seizure onset.

Automatic detection of the epileptogenic zone: An application of the fingerprint of epilepsy

BACKGROUND

The successful delineation of the epileptogenic zone in epilepsy monitoring is crucial for achieving seizure freedom after epilepsy surgery.

NEW METHOD

We aim to improve epileptogenic zone localization by utilizing a computer-assisted tool for the automated grading of the seizure activity recorded in various locations for 20 patients undergoing stereo electroencephalography. Their epileptic seizures were processed to extract two potential biomarkers. The concentration of these biomarkers from within each patient's implantation were then graded to identify their epileptogenic zone and were compared to the clinical assessment.

RESULTS

Our technique was capable of ranking the clinically defined epileptogenic zone with high accuracy, above 95%, with a true to false positive ratio of 1:1.52, and was effective with both temporal and extra-temporal onset epilepsies.

COMPARISON WITH EXISTING METHOD

We compared our method to two other groups performing localization using similar biomarkers. Our classification metrics, sensitivity and precision together were comparable to both groups and our overall accuracy from a larger population was also higher then both.

CONCLUSIONS

Our method is highly accurate, automated and non-parametric providing clinicians another tool that can be used to help identify the epileptogenic zone in patients undergoing the stereo electroencephalography procedure for epilepsy monitoring.

The effect of antiepileptic drugs on epileptiform discharges in genetic generalized epilepsy: A systematic review

OBJECTIVE

The objective of this study was to evaluate the current evidence regarding the effect of antiepileptic drugs (AEDs) on epileptiform discharge (ED) burden in genetic generalized epilepsy (GGE).

METHODS

We conducted a comprehensive literature search of PubMed, Embase, PsycINFO, and the Web of Science Core Collection databases using the keywords 'genetic generalized epilepsy', 'antiepileptic drugs' and 'epileptiform discharge'. Primary human studies published in English that reported the effect of AEDs on EDs captured on electroencephalogram (EEG) recordings of at least 24 h in duration in patients with GGE were included.

RESULTS

Six studies published between 1984 and 2017, which reported the effect of AEDs on EDs, involving a total of 116 patients with GGE, were analyzed. Our systematic review found a tendency for AEDs to reduce ED density, frequency, cumulative duration, and burst duration in GGE. Furthermore, we found evidence that the AED-mediated reduction in ED burden was associated with improved seizure control and cognitive outcomes.

CONCLUSIONS

Antiepileptic drugs tend to reduce ED burden in GGE, but the significance of this association remains uncertain.

A Straw Can Break a Neural Network's Back and Lead to Seizures-But Only When Delivered at the Right Time

Loss of Neuronal Network Resilience Precedes Seizures and Determines the Ictogenic Nature of Interictal Synaptic Perturbations Chang WC, Kudlacek J, Hlinka J, et al. Nat Neurosci. 2018; 21(12):1742-1752. doi:10.1038/s41593-018-0278-y. PMID: 30482946. The mechanism of seizure emergence and the role of brief interictal epileptiform discharges (IEDs) in seizure generation are 2 of the most important unresolved issues in modern epilepsy research. We found that the transition to seizure is not a sudden phenomenon, but is instead a slow process that is characterized by the progressive loss of neuronal network resilience. From a dynamical perspective, the slow transition is governed by the principles of critical slowing, a robust natural phenomenon that is observable in systems characterized by transitions between dynamical regimes. In epilepsy, this process is modulated by synchronous synaptic input from IEDs. The IEDs are external perturbations that produce phasic changes in the slow transition process and exert opposing effects on the dynamics of a seizure-generating network, causing either antiseizure or proseizure effects. We found that the multifaceted nature of IEDs is defined by the dynamical state of the network at the moment of the discharge occurrence.

The Paroxysmal Depolarization Shift: Reconsidering Its Role in Epilepsy, Epileptogenesis and Beyond

Paroxysmal depolarization shifts (PDS) have been described by epileptologists for the first time several decades ago, but controversy still exists to date regarding their role in epilepsy. In addition to the initial view of a lack of such a role, seemingly opposing hypotheses on epileptogenic and anti-ictogenic effects of PDS have emerged. Hence, PDS may provide novel targets for epilepsy therapy. Evidence for the roles of PDS has often been obtained from investigations of the multi-unit correlate of PDS, an electrographic spike termed “interictal” because of its occurrence during seizure-free periods of epilepsy patients. Meanwhile, interictal spikes have been found to be associated with neuronal diseases other than epilepsy, e.g., Alzheimer’s disease, which may indicate a broader implication of PDS in neuropathologies. In this article, we give an introduction to PDS and review evidence that links PDS to pro- as well as anti-epileptic mechanisms, and to other types of neuronal dysfunction. The perturbation of neuronal membrane voltage and of intracellular Ca²⁺ that comes with PDS offers many conceivable pathomechanisms of neuronal dysfunction. Out of these, the operation of L-type voltage-gated calcium channels, which play a major role in coupling excitation to long-lasting neuronal changes, is addressed in detail.

Transient Cognitive Impairment in Epilepsy

Impairments of the dialog between excitation and inhibition (E/I) is commonly associated to neuropsychiatric disorders like autism, bipolar disorders and epilepsy. Moderate levels of hyperexcitability can lead to mild alterations of the EEG and are often associated with cognitive deficits even in the absence of overt seizures. Indeed, various testing paradigms have shown degraded performances in presence of acute or chronic non-ictal epileptiform activity. Evidences from both animal models and the clinics suggest that anomalous activity can cause cognitive deficits by transiently disrupting cortical processing, independently from the underlying etiology of the disease. Here, we will review our understanding of the influence of an abnormal EEG activity on brain computation in the context of the available clinical data and in genetic or pharmacological animal models.

Clinical and electrocorticographic response to antiepileptic drugs in patients treated with responsive stimulation

OBJECTIVE

The objective of this study was to explore whether chronic electrocorticographic (ECoG) data recorded by a responsive neurostimulation system could be used to assess clinical responses to antiepileptic drugs (AEDs).

METHODS

Antiepileptic drugs initiated and maintained for ≥3 months by patients participating in clinical trials of the RNS^® System were identified. Such "AED Starts" that produced an additional ≥50% reduction in patient-reported clinical seizure frequency were categorized as clinically beneficial, and the remaining as not beneficial. Electrocorticographic features recorded by the RNS^® Neurostimulator were analyzed during three periods: 3 months before the AED Start, first month after the AED Start, and the first 3 months after the AED Start.

RESULTS

The most commonly added medications were clobazam (n = 41), lacosamide (n = 96), levetiracetam (n = 31), and pregabalin (n = 25). Across all four medications, there were sufficient clinical data for 193 AED Starts to be included in the analyses, and 59 AED Starts were considered clinically beneficial. The proportion of AED Starts that qualified as clinically beneficial was higher for clobazam (53.7%) and levetiracetam (51.6%) than for lacosamide (18.8%) and pregabalin (12%). Across all AED Starts for which RNS ECoG detection settings were held constant, the clinically beneficial AED Starts were associated with a significantly greater reduction in the detection of epileptiform activity (p < 0.001) at 1 (n = 33) and 3 months (n = 30) compared with AED Starts that were not beneficial at 1 (n = 71) and 3 months (n = 60). Furthermore, there was a significant reduction in interictal spike rate and spectral power (1-125 Hz) associated with a clinically beneficial response to an AED Start at 1 (n = 32) and 3 months (n = 35) (p < 0.001). These reductions were not observed at either 1 (n = 59) or 3 months (n = 60) for AED Starts that were not clinically beneficial.

CONCLUSIONS

Significant quantitative changes in ECoG data recorded by the RNS System were observed in patients who experienced an additional clinical response to a new AED. While there was variability across patients in the changes observed, the results suggest that quantitative ECoG data may provide useful information when assessing whether a patient may have a favorable clinical response to an AED.

A forward-looking review of seizure prediction

PURPOSE OF REVIEW

Seizure prediction has made important advances over the last decade, with the recent demonstration that prospective seizure prediction is possible, though there remain significant obstacles to broader application. In this review, we will describe insights gained from long-term trials, with the aim of identifying research goals for the next decade.

RECENT FINDINGS

Unexpected results from these studies, including strong and highly individual relationships between spikes and seizures, diurnal patterns of seizure activity, and the coexistence of different seizure populations within individual patients exhibiting distinctive dynamics, have caused us to re-evaluate many prior assumptions in seizure prediction studies and suggest alternative strategies that could be employed in the search for algorithms providing greater clinical utility. Advances in analytical approaches, particularly deep-learning techniques, harbour great promise and in combination with less-invasive systems with sufficiently power-efficient computational capacity will bring broader clinical application within reach.

SUMMARY

We conclude the review with an exercise in wishful thinking, which asks what the ideal seizure prediction dataset would look like and how these data should be manipulated to maximize benefits for patients. The motivation for structuring the review in this way is to create a forward-looking, optimistic critique of the existing methodologies.

Spatiotemporal evolution of focal epileptiform activity from surface and laminar field recordings in cat neocortex

New devices that use targeted electrical stimulation to treat refractory localization-related epilepsy have shown great promise, although it is not well known which targets most effectively prevent the initiation and spread of seizures. To better understand how the brain transitions from healthy to seizing on a local scale, we induced focal epileptiform activity in the visual cortex of five anesthetized cats with local application of the GABA_A blocker picrotoxin while simultaneously recording local field potentials on a high-resolution electrocorticography array and laminar depth probes. Epileptiform activity appeared in the form of isolated events, revealing a consistent temporal pattern of ictogenesis across animals with interictal events consistently preceding the appearance of seizures. Based on the number of spikes per event, there was a natural separation between seizures and shorter interictal events. Two distinct spatial regions were seen: an epileptic focus that grew in size as activity progressed, and an inhibitory surround that exhibited a distinct relationship with the focus both on the surface and in the depth of the cortex. Epileptiform activity in the cortical laminae was seen concomitant with activity on the surface. Focus spikes appeared earlier on electrodes deeper in the cortex, suggesting that deep cortical layers may be integral to recruiting healthy tissue into the epileptic network and could be a promising target for interventional devices. Our study may inform more effective therapies to prevent seizure generation and spread in localization-related epilepsies. NEW & NOTEWORTHY We induced local epileptiform activity and recorded continuous, high-resolution local field potentials from the surface and depth of the visual cortex in anesthetized cats. Our results reveal a consistent pattern of ictogenesis, characterize the spatial spread of the epileptic focus and its relationship with the inhibitory surround, and show that focus activity within events appears earliest in deeper cortical layers. These findings have potential implications for the monitoring and treatment of refractory epilepsy.

Characteristics of Epileptiform Discharge Duration and Interdischarge Interval in Genetic Generalized Epilepsies

We sought to investigate (1) the characteristics of epileptiform discharge (ED) duration and interdischarge interval (IDI) and (2) the influence of vigilance state on the ED duration and IDI in genetic generalized epilepsy (GGE). In a cohort of patients diagnosed with GGE, 24-h ambulatory EEG recordings were performed prospectively. We then tabulated durations, IDI, and vigilance state in relation to all EDs captured on EEGs. We used K-means cluster analysis and finite mixture modeling to quantify and characterize the groups of ED duration and IDI. To investigate the influence of sleep, we calculated the mean, median, and SEM in each population from all subjects for sleep state and wakefulness separately, followed by the Kruskal–Wallis test to compare the groups. We analyzed 4,679 EDs and corresponding IDI from 23 abnormal 24-h ambulatory EEGs. Our analysis defined two populations of ED durations and IDI: short and long. In all populations, both ED durations and IDI were significantly longer in wakefulness. Our results highlight different characteristics of ED populations in GGE and the influence by the sleep–wake cycle.

Progression of convulsive and nonconvulsive seizures during epileptogenesis after pilocarpine-induced status epilepticus

Although convulsive seizures occurring during pilocarpine-induced epileptogenesis have received considerable attention, nonconvulsive seizures have not been closely examined, even though they may reflect the earliest signs of epileptogenesis and potentially guide research on antiepileptogenic interventions. The definition of nonconvulsive seizures based on brain electrical activity alone has been controversial. Here we define and quantify electrographic properties of convulsive and nonconvulsive seizures in the context of the acquired epileptogenesis that occurs after pilocarpine-induced status epilepticus (SE). Lithium-pilocarpine was used to induce the prolonged repetitive seizures characteristic of SE; when SE was terminated with paraldehyde, seizures returned during the 2-day period after pilocarpine treatment. A distinct latent period ranging from several days to >2 wk was then measured with continuous, long-term video-EEG. Nonconvulsive seizures dominated the onset of epileptogenesis and consistently preceded the first convulsive seizures but were still present later. Convulsive and nonconvulsive seizures had similar durations. Postictal depression (background suppression of the EEG) lasted for >100 s after both convulsive and nonconvulsive seizures. Principal component analysis was used to quantify the spectral evolution of electrical activity that characterized both types of spontaneous recurrent seizures. These studies demonstrate that spontaneous nonconvulsive seizures have electrographic properties similar to convulsive seizures and confirm that nonconvulsive seizures link the latent period and the onset of convulsive seizures during post-SE epileptogenesis in an animal model. Nonconvulsive seizures may also reflect the earliest signs of epileptogenesis in human acquired epilepsy, when intervention could be most effective. NEW & NOTEWORTHY Nonconvulsive seizures usually represent the first bona fide seizure following a latent period, dominate the early stages of epileptogenesis, and change in severity in a manner consistent with the progressive nature of epileptogenesis. This analysis demonstrates that nonconvulsive and convulsive seizures have different behavioral outcomes but similar electrographic signatures. Alternatively, epileptiform spike-wave discharges fail to recapitulate several key seizure features and represent a category of electrical activity separate from nonconvulsive seizures in this model.

Multi-day rhythms modulate seizure risk in epilepsy

Epilepsy is defined by the seemingly random occurrence of spontaneous seizures. The ability to anticipate seizures would enable preventative treatment strategies. A central but unresolved question concerns the relationship of seizure timing to fluctuating rates of interictal epileptiform discharges (here termed interictal epileptiform activity, IEA), a marker of brain irritability observed between seizures by electroencephalography (EEG). Here, in 37 subjects with an implanted brain stimulation device that detects IEA and seizures over years, we find that IEA oscillates with circadian and subject-specific multidien (multi-day) periods. Multidien periodicities, most commonly 20-30 days in duration, are robust and relatively stable for up to 10 years in men and women. We show that seizures occur preferentially during the rising phase of multidien IEA rhythms. Combining phase information from circadian and multidien IEA rhythms provides a novel biomarker for determining relative seizure risk with a large effect size in most subjects.

Pathophysiological mechanisms of migraine and epilepsy: Similarities and differences

Migraine and epilepsy are episodic disorders with distinct features, but they have some clinical and pathophysiological overlaps. We review here clinical overlaps between seizures and migraine attacks, activities of neuronal networks observed during seizures and migraine attacks, and molecular and cellular mechanisms of migraine identified in genetic forms, focusing on genetic variants identified in hemiplegic migraine and their functional effects. Epilepsy and migraine can be generated by dysfunctions of the same neuronal networks, but these dysfunctions can be disease-specific, even if pathogenic mutations target the same protein. Studies of rare monogenic forms have allowed the identification of some molecular/cellular dysfunctions that provide a window on pathological mechanisms: we have begun to disclose the tip of the iceberg.

Correlating Interictal Spikes with Sigma and Delta Dynamics during Non-Rapid-Eye-Movement-Sleep

Interictal spikes (IS) are one of the major hallmarks of epilepsy. Understanding the factors promoting or suppressing IS would increase our comprehension of epilepsy and possibly open new avenues for therapy. Sleep strongly influences epileptic activity, and the modulatory effects of the different sleep stages on IS have been studied for decades. However, several aspects are still disputed, in particular the role of sleep spindles and slow waves in the activation of IS during Non-REM sleep. Here, we correlate the rate of IS with quantitative measures derived from stereo-EEG during one Non-REM cycle in 10 patients suffering from drug-resistant epilepsy due to type 2 focal cortical dysplasia. We show that the IS rate (ISR) is positively correlated with sigma power (a surrogate for sleep-spindle density) but negatively correlated with delta power (surrogate for slow wave activity). In addition, we present two new indices for quantifying the spatial and temporal instability of sleep. We found that both instability indices are correlated with a high ISR. The main contribution of this study is to confirm the suppressive effect of stable deep sleep on IS. This result might influence future guidelines for therapy of patients suffering from epilepsy and sleep disorders.

Activity Clamp Provides Insights into Paradoxical Effects of the Anti-Seizure Drug Carbamazepine

A major challenge in experimental epilepsy research is to reconcile the effects of anti-epileptic drugs (AEDs) on individual neurons with their network-level actions. Highlighting this difficulty, it is unclear why carbamazepine (CBZ), a frontline AED with a known molecular mechanism, has been reported to increase epileptiform activity in several clinical and experimental studies. We confirmed in an in vitro mouse model (in both sexes) that the frequency of interictal bursts increased after CBZ perfusion. To address the underlying mechanisms, we developed a method, activity clamp, to distinguish the response of individual neurons from network-level actions of CBZ. We first recorded barrages of synaptic conductances from neurons during epileptiform activity and then replayed them in pharmacologically isolated neurons under control conditions and in the presence of CBZ. CBZ consistently decreased the reliability of the second action potential in each burst of activity. Conventional current-clamp recordings using excitatory ramp or square-step current injections failed to reveal this effect. Network modeling showed that a CBZ-induced decrease of neuron recruitment during epileptic bursts can lead to an increase in burst frequency at the network level by reducing the refractoriness of excitatory transmission. By combining activity clamp with computer simulations, the present study provides a potential explanation for the paradoxical effects of CBZ on epileptiform activity.

SIGNIFICANCE STATEMENT The effects of anti-epileptic drugs on individual neurons are difficult to separate from their network-level actions. Although carbamazepine (CBZ) has a known anti-epileptic mechanism, paradoxically, it has also been reported to increase epileptiform activity in clinical and experimental studies. To investigate this paradox during realistic neuronal epileptiform activity, we developed a method, activity clamp, to distinguish the effects of CBZ on individual neurons from network-level actions. We demonstrate that CBZ consistently decreases the reliability of the second action potential in each burst of epileptiform activity. Network modeling shows that this effect on individual neuronal responses could explain the paradoxical effect of CBZ at the network level.

Continuous Intraoperative Monitoring of Temporal Lobe Epilepsy Surgery

BACKGROUND/AIMS

The monitoring of interictal epileptiform discharge rates (IEDRs) all along anterior temporal lobe resections (ATLRs) has never been reported. Here the effect of ATLR on continuous IEDR monitoring is described.

METHODS

IEDRs computed automatically during entire interventions were recorded in 34 patients (38.2%, 13/34 depth; 61.8%, 21/34 scalp electrodes only). Monitorings were invalidated when burst suppression occurred or if initial IEDRs were <5.

RESULTS

Monitoring was successful for 69.2% (9/13) of the patients with depth recordings and for 4.8% (1/21) of the patients with scalp recordings. Burst suppressions precluded it in 30.8% (4/13) of the depth and in 57.1% (12/21) of the scalp recordings. Initial IEDRs were <5 for 38.1% (8/21) of the scalp recordings. Significant IEDR decreases were observed in 8/10 patients with successful monitoring. These decreases started with resection of the superior temporal gyrus. IEDRs decreased further with amygdalohippocampectomy in 3/5 patients. At the 12-month follow-up, all patients with IEDR decreases remained seizure free; both patients without did not.

CONCLUSION

IEDR monitoring was possible with depth, but not with scalp electrodes. IEDR decreases started with resection of the superior temporal gyrus. A larger patient cohort is necessary to confirm the high predictive values of IEDR monitoring that could become a tool for surgery customization.