Temporal distribution of seizures in epilepsy

Rat strain differences in seizure frequency and hilar neuron loss after systemic treatment with pilocarpine

At least 3 months after systemic treatment with pilocarpine to induce status epilepticus, Long-Evans and Sprague-Dawley rats were video-EEG monitored for seizures continuously for 1 month. Rats were then perfused, hippocampi were processed for Nissl staining, and hilar neurons were quantified. Seizure frequency in Long-Evans rats was 1/10th of that in Sprague-Dawley rats, and more variable. Hilar neuron loss was also less severe in Long-Evans rats. However, there was no correlation between hilar neuron loss and seizure frequency in either strain. The low and variable seizure frequency suggests limited usefulness of pilocarpine-treated Long-Evans rats for some epilepsy experiments.

Ictal activity is sustained by the estrogen receptor β during the estrous cycle

Catamenial epilepsy, defined as a periodicity of seizure exacerbation during the menstrual cycle, affects up to 70 % of epileptic women. Seizures in these patients are often non-responsive to medication; however, our understanding of the relation between menstrual cycle and seizure generation (i.e. ictogenesis) remains limited. We employed here field potential recordings in the in vitro 4-aminopyridine model of epileptiform synchronization in female mice (P60-P130) and found that: (i) the estrous phase favors ictal activity in the entorhinal cortex; (ii) these ictal discharges display an onset pattern characterised by the presence of chirps that are thought to mirror synchronous interneuron firing; and (iii) blocking estrogen receptor β-mediated signaling reduces ictal discharge duration. Our findings indicate that the duration of 4AP-induced ictal discharges, in vitro, increases during the estrous phase, which corresponds to the human peri-ovulatory period. We propose that these effects are caused by the presumptive enhancement of interneuron excitability due to increased estrogen receptor β-mediated signaling.

Epileptic seizure clustering and accumulation at transition from activity to rest in GAERS rats

Knowing when seizures occur may help patients and can also provide insight into epileptogenesis mechanisms. We recorded seizures over periods of several days in the Genetic Absence Epileptic Rat from Strasbourg (GAERS) model of absence epilepsy, while we monitored behavioral activity with a combined head accelerometer (ACCEL), neck electromyogram (EMG), and electrooculogram (EOG). The three markers consistently discriminated between states of behavioral activity and rest. Both GAERS and control Wistar rats spent more time in rest (55-66%) than in activity (34-45%), yet GAERS showed prolonged continuous episodes of activity (23 vs. 18 min) and rest (34 vs. 30 min). On average, seizures lasted 13 s and were separated by 3.2 min. Isolated seizures were associated with a decrease in the power of the activity markers from steep for ACCEL to moderate for EMG and weak for EOG, with ACCEL and EMG power changes starting before seizure onset. Seizures tended to occur in bursts, with the probability of seizing significantly increasing around a seizure in a window of ±4 min. Furthermore, the seizure rate was strongly increased for several minutes when transitioning from activity to rest. These results point to mechanisms that control behavioral states as determining factors of seizure occurrence.

Biological rhythms and epilepsy treatment

Approximately one-third of patients with epilepsy are drug-refractory, necessitating novel treatment approaches. Chronopharmacology, which adjusts pharmacological treatment to physiological variations in seizure susceptibility and drug responsiveness, offers a promising strategy to enhance efficacy and tolerance. This narrative review provides an overview of the biological foundations for rhythms in seizure activity, clinical implications of seizure patterns through case reports, and the potential of chronopharmacological strategies to improve treatment. Biological rhythms, including circadian and infradian rhythms, play an important role in epilepsy. Understanding seizure patterns may help individualize treatment decisions and optimize therapeutic outcomes. Altering drug concentrations based on seizure risk periods, adjusting administration times, and exploring hormone therapy are potential strategies. Large-scale randomized controlled trials are needed to evaluate the efficacy and safety of differential and intermittent treatment approaches. By tailoring treatment to individual seizure patterns and pharmacological properties, chronopharmacology offers a personalized approach to improve outcomes in patients with epilepsy.

Chronic recording of the vagus nerve to analyze modulations by the light-dark cycle

OBJECTIVE

The vagus nerve is considered to play a key role in the circadian rhythm. Chronic continuous analysis of the vagus nerve activity could contribute to a better understanding of the role of the vagus nerve in light-dark modulations. This paper presents a continuous analysis of spontaneous vagus nerve activity performed in four rats.

APPROACH

We analyzed the vagus electroneurogram (VENG) and electroencephalogram (EEG) over a recording period of 28 days. Spike activity and heart rate estimation were derived from the VENG, and slow-wave activity was derived from the EEG. The presence of repetitive patterns was investigated with periodograms, cosinor fitting, autocorrelation, and statistical tests. The light-dark variations derived from the VENG spikes were compared with EEG slow waves, an established metric in circadian studies.

RESULTS

Our results demonstrate that light-dark variations can be detected in long-term vagus nerve activity monitoring. A recording period of about seven days is required to characterize accurately the VENG light-dark variations.

SIGNIFICANCE

As a major outcome of this study, vagus nerve recordings hold the promise to help understand circadian regulation.

Tracking cortical excitability dynamics with transcranial magnetic stimulation in focal epilepsy

INTRODUCTION

The lack of reliable biomarkers constrain epilepsy management. We assessed the potential of repeated transcranial magnetic stimulation with electromyography (TMS-EMG) to track dynamical changes in cortical excitability on a within-subject basis.

METHODS

We recruited people with refractory focal epilepsy who underwent video-EEG monitoring and drug tapering as part of the presurgical evaluation. We performed daily TMS-EMG measurements with additional postictal assessments 1-6 h following seizures to assess resting motor threshold (rMT), and motor evoked potentials (MEPs) with single- and paired-pulse protocols. Anti-seizure medication (ASM) regimens were recorded for the day before each measurement and expressed in proportion to the dosage before tapering. Additional measurements were performed in healthy controls to evaluate day-to-day rMT variability.

RESULTS

We performed 77 (58 baseline, 19 postictal) measurements in 16 people with focal epilepsy and 35 in seven healthy controls. Controls showed minimal day-to-day rMT variation. Withdrawal of ASMs was associated with a lower rMT without affecting MEPs of single- and paired-pulse TMS-EMG paradigms. Postictal measurements following focal to bilateral tonic-clonic seizures demonstrated unaltered rMT and increased short interval intracortical inhibition, while measurements following focal seizures with impaired awareness showed decreased rMT's and reduced short and long interval intracortical inhibition.

CONCLUSION

Serial within-subject rMT measurements yielded reproducible, stable results in healthy controls. ASM tapering and seizures had distinct effects on TMS-EMG excitability indices in people with epilepsy. Drug tapering decreased rMT, indicating increased overall corticospinal excitability, whereas seizures affected intracortical inhibition with contrasting effects between seizure types.

Treatments for seizures in catamenial (menstrual-related) epilepsy

BACKGROUND

This is an updated version of a Cochrane Review previously published in 2019. Catamenial epilepsy describes worsening seizures in relation to the menstrual cycle and may affect around 40% of women with epilepsy. Vulnerable days of the menstrual cycle for seizures are perimenstrually (C1 pattern), at ovulation (C2 pattern), and during the luteal phase (C3 pattern). A reduction in progesterone levels premenstrually and reduced secretion during the luteal phase is implicated in catamenial C1 and C3 patterns. A reduction in progesterone has been demonstrated to reduce sensitivity to the inhibitory neurotransmitter in preclinical studies, hence increasing risk of seizures. A pre-ovulatory surge in oestrogen has been implicated in the C2 pattern of seizure exacerbation, although the exact mechanism by which this surge increases risk is uncertain. Current treatment practices include the use of pulsed hormonal (e.g. progesterone) and non-hormonal treatments (e.g. clobazam or acetazolamide) in women with regular menses, and complete cessation of menstruation using synthetic hormones (e.g. medroxyprogesterone (Depo-Provera) or gonadotropin-releasing hormone (GnRH) analogues (triptorelin and goserelin)) in women with irregular menses. Catamenial epilepsy and seizure exacerbation is common in women with epilepsy. Women may not receive appropriate treatment for their seizures because of uncertainty regarding which treatment works best and when in the menstrual cycle treatment should be taken, as well as the possible impact on fertility, the menstrual cycle, bone health, and cardiovascular health. This review aims to address these issues to inform clinical practice and future research.

OBJECTIVES

To evaluate the efficacy and tolerability of hormonal and non-hormonal treatments for seizures exacerbated by the menstrual cycle in women with regular or irregular menses. We synthesised the evidence from randomised and quasi-randomised controlled trials of hormonal and non-hormonal treatments in women with catamenial epilepsy of any pattern.

SEARCH METHODS

We searched the following databases on 20 July 2021 for the latest update: Cochrane Register of Studies (CRS Web) and MEDLINE Ovid (1946 to 19 July 2021). CRS Web includes randomised controlled trials (RCTs) or quasi-RCTs from PubMed, Embase, ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform, the Cochrane Central Register of Controlled Trials (CENTRAL), and the specialised registers of Cochrane Review Groups including Cochrane Epilepsy. We used no language restrictions. We checked the reference lists of retrieved studies for additional reports of relevant studies.

SELECTION CRITERIA

We included RCTs and quasi-RCTs of blinded or open-label design that randomised participants individually (i.e. cluster-randomised trials were excluded). We included cross-over trials if each treatment period was at least 12 weeks in length and the trial had a suitable wash-out period. We included the following types of interventions: women with any pattern of catamenial epilepsy who received a hormonal or non-hormonal drug intervention in addition to an existing antiepileptic drug regimen for a minimum treatment duration of 12 weeks.

DATA COLLECTION AND ANALYSIS

We extracted data on study design factors and participant demographics for the included studies. The primary outcomes of interest were: proportion seizure-free, proportion of responders (at least 50% decrease in seizure frequency from baseline), and change in seizure frequency. Secondary outcomes included: number of withdrawals, number of women experiencing adverse events of interest (seizure exacerbation, cardiac events, thromboembolic events, osteoporosis and bone health, mood disorders, sedation, menstrual cycle disorders, and fertility issues), and quality of life outcomes.

MAIN RESULTS

Following title, abstract, and full-text screening, we included eight full-text articles reporting on four double-blind, placebo-controlled RCTs. We included two cross-over RCTs of pulsed norethisterone, and two parallel RCTs of pulsed progesterone recruiting a total of 192 women aged between 13 and 45 years with catamenial epilepsy. We found no RCTs for non-hormonal treatments of catamenial epilepsy or for women with irregular menses. Meta-analysis was not possible for the primary outcomes, therefore we undertook a narrative synthesis. For the two RCTs evaluating norethisterone versus placebo (24 participants), there were no reported treatment differences for change in seizure frequency. Outcomes for the proportion seizure-free and 50% responders were not reported. For the two RCTs evaluating progesterone versus placebo (168 participants), the studies reported conflicting results for the primary outcomes. One progesterone RCT reported no significant difference between progesterone 600 mg/day taken on day 14 to 28 and placebo with respect to 50% responders, seizure freedom rates, and change in seizure frequency for any seizure type. The other progesterone RCT reported a decrease in seizure frequency from baseline in the progesterone group that was significantly higher than the decrease in seizure frequency from baseline in the placebo group. The results of secondary efficacy outcomes showed no significant difference between groups in the pooled progesterone RCTs in terms of treatment withdrawal for any reason (pooled risk ratio (RR) 1.56, 95% confidence interval (CI) 0.81 to 3.00, P = 0.18, I² = 0%) or treatment withdrawals due to adverse events (pooled RR 2.91, 95% CI 0.53 to 16.17, P = 0.22, I² = 0%). No treatment withdrawals were reported from the norethisterone RCTs. The RCTs reported limited information on adverse events, although one progesterone RCT reported no significant difference in the number of women experiencing adverse events (diarrhoea, dyspepsia, nausea, vomiting, fatigue, nasopharyngitis, dizziness, headache, and depression). No studies reported on quality of life. We judged the evidence for outcomes related to the included progesterone RCTs to be of low to moderate certainty due to risk of bias, and for outcomes related to the included norethisterone RCTs to be of very low certainty due to serious imprecision and risk of bias.

AUTHORS' CONCLUSIONS

This review provides very low-certainty evidence of no treatment difference between norethisterone and placebo, and moderate- to low-certainty evidence of no treatment difference between progesterone and placebo for catamenial epilepsy. However, as all the included studies were underpowered, important clinical effects cannot be ruled out. Our review highlights an overall deficiency in the literature base on the effectiveness of a wide range of other hormonal and non-hormonal interventions currently being used in practice, particularly for those women who do not have regular menses. Further clinical trials are needed in this area.

Long-term seizure dynamics are determined by the nature of seizures and the mutual interactions between them

The seemingly random and unpredictable nature of seizures is a major debilitating factor for people with epilepsy. An increasing body of evidence demonstrates that the epileptic brain exhibits long-term fluctuations in seizure susceptibility, and seizure emergence seems to be a consequence of processes operating over multiple temporal scales. A deeper insight into the mechanisms responsible for long-term seizure fluctuations may provide important information for understanding the complex nature of seizure genesis. In this study, we explored the long-term dynamics of seizures in the tetanus toxin model of temporal lobe epilepsy. The results demonstrate the existence of long-term fluctuations in seizure probability, where seizures form clusters in time and are then followed by seizure-free periods. Within each cluster, seizure distribution is non-Poissonian, as demonstrated by the progressively increasing inter-seizure interval (ISI), which marks the approaching cluster termination. The lengthening of ISIs is paralleled by: increasing behavioral seizure severity, the occurrence of convulsive seizures, recruitment of extra-hippocampal structures and the spread of electrographic epileptiform activity outside of the limbic system. The results suggest that repeated non-convulsive seizures obey the 'seizures-beget-seizures' principle, leading to the occurrence of convulsive seizures, which decrease the probability of a subsequent seizure and, thus, increase the following ISI. The cumulative effect of repeated convulsive seizures leads to cluster termination, followed by a long inter-cluster period. We propose that seizures themselves are an endogenous factor that contributes to long-term fluctuations in seizure susceptibility and their mutual interaction determines the future evolution of disease activity.

The interactions between reproductive hormones and epilepsy

There are complex interactions between hormones, epilepsy, and antiepileptic drugs (AEDs). While there is ample evidence that hormones influence epilepsy, it is also apparent that epileptic activity influences hormones in both women and men. In addition, AEDs may disturb endocrine function. The clinical importance of these interactions is primarily related to the effects on reproductive hormones, which is the focus of this article. Reproductive endocrine dysfunction is common among women and men with epilepsy. Menstrual disorders, polycystic ovaries, and infertility have been described among women with epilepsy, while reduced potency and sperm abnormalities have been found in men. Sexual problems and endocrine changes have been frequently described in both sexes. Epilepsy and AEDs can target a number of substrates to impact hormone levels. These include the limbic system, hypothalamus, pituitary, peripheral endocrine glands, liver, and adipose tissue. AEDs may also alter the synthesis of steroids and binding proteins, as well as hormone metabolism, and produce direct gonadal effects.

Circadian and multiday seizure periodicities, and seizure clusters in canine epilepsy

Advances in ambulatory intracranial EEG devices have enabled objective analyses of circadian and multiday seizure periodicities, and seizure clusters in humans. This study characterizes circadian and multiday seizure periodicities, and seizure clusters in dogs with naturally occurring focal epilepsy, and considers the implications of an animal model for the study of seizure risk patterns, seizure forecasting and personalized treatment protocols. In this retrospective cohort study, 16 dogs were continuously monitored with ambulatory intracranial EEG devices designed for humans. Detailed medication records were kept for all dogs. Seizure periodicity was evaluated with circular statistics methods. Circular non-uniformity was assessed for circadian, 7-day and approximately monthly periods. The Rayleigh test was used to assess statistical significance, with correction for multiple comparisons. Seizure clusters were evaluated with Fano factor (index of dispersion) measurements, and compared to a Poisson distribution. Relationships between interseizure interval (ISI) and seizure duration were evaluated. Six dogs met the inclusion criteria of having at least 30 seizures and were monitored for an average of 65 weeks. Three dogs had seizures with circadian seizure periodicity, one dog had a 7-day periodicity, and two dogs had approximately monthly periodicity. Four dogs had seizure clusters and significantly elevated Fano factor values. There were subject-specific differences in the dynamics of ISI and seizure durations, both within and between lead and clustered seizure categories. Our findings show that seizure timing in dogs with naturally occurring epilepsy is not random, and that circadian and multiday seizure periodicities, and seizure clusters are common. Circadian, 7-day, and monthly seizure periodicities occur independent of antiseizure medication dosing, and these patterns likely reflect endogenous rhythms of seizure risk.

A Clinical Approach to Catamenial Epilepsy: A Review

IMPORTANCE

Catamenial epilepsy (CE) is exacerbated by hormonal fluctuations during the menstrual cycle. Approximately 1.7 million women have epilepsy in the United States. CE affects more than 40% of women with epilepsy. There is a paucity of literature addressing this condition from a clinical standpoint, and the literature that does exist is limited to the neurological community. This article reviews the diagnosis and management of CE for the non-neurologist. Women with CE have early touch points in their care with numerous health care providers before ever consulting with a specialist, including OB/GYNs, pediatricians, emergency department physicians, and family medicine providers. In addition, women affected by CE have seizures that are more recalcitrant to traditional epilepsy treatment regimens. To optimize management in patients affected by CE, menstrual physiology must be understood, individualized hormonal contraception treatment considered, and adjustments and interactions with antiepileptic drugs addressed.

OBSERVATIONS

CE is a unique subset of seizure disorders affected by menstrual fluctuations of progesterone and estrogen. The diagnosis of CE has been refined and clarified. There is an ever-increasing understanding of the importance and variety of options of hormonal contraception available to help manage CE. Furthermore, antiepileptic drugs and contraception can interact, so attention must be directed to optimizing both regimens to prevent uncontrolled seizures and pregnancy.

CONCLUSION AND RELEVANCE

CE can be diagnosed with charting of menstrual cycles and seizure activity. Hormonal treatments that induce amenorrhea have been shown to reduce CE. Optimizing antiepileptic drug dosing and contraceptive methods also can minimize unplanned pregnancies in women affected by CE.

Treatments for seizures in catamenial (menstrual-related) epilepsy

BACKGROUND

Catamenial epilepsy describes a worsening of seizures in relation to the menstrual cycle and may affect around 40% of women with epilepsy. Vulnerable days of the menstrual cycle for seizures are perimenstrually (C1 pattern), at ovulation (C2 pattern), and during the luteal phase (C3 pattern). A reduction in progesterone levels premenstrually and reduced secretion during the luteal phase is implicated in catamenial C1 and C3 patterns. A reduction in progesterone has been demonstrated to reduce sensitivity to the inhibitory neurotransmitter in preclinical studies, hence increasing risk of seizures. A pre-ovulatory surge in oestrogen has been implicated in the C2 pattern of seizure exacerbation, although the exact mechanism by which this surge increases risk is uncertain. Current treatment practices include the use of pulsed hormonal (e.g. progesterone) and non-hormonal treatments (e.g. clobazam or acetazolamide) in women with regular menses, and complete cessation of menstruation using synthetic hormones (e.g. medroxyprogesterone (Depo-Provera) or gonadotropin-releasing hormone (GnRH) analogues (triptorelin and goserelin)) in women with irregular menses.Catamenial epilepsy and seizure exacerbation is common in women with epilepsy, and may have a significant negative impact on quality of life. Women may not be receiving appropriate treatment for their seizures because of uncertainty regarding which treatment works best and when in the menstrual cycle treatment should be taken, as well as the possible impact on fertility, the menstrual cycle, bone health, and cardiovascular health. This review aimed to address these issues in order to inform clinical practice and future research.

OBJECTIVES

To evaluate the efficacy and tolerability of hormonal and non-hormonal treatments for seizures exacerbated by the menstrual cycle in women with regular or irregular menses. We synthesised the evidence from randomised controlled trials of hormonal and non-hormonal treatments in women with catamenial epilepsy of any pattern.

SEARCH METHODS

We searched the following databases to 10 January 2019: Cochrane Register of Studies (CRS Web; includes the Cochrane Epilepsy Group Specialized Register and the Cochrane Central Register of Controlled Trials (CENTRAL)), MEDLINE (Ovid: 1946 to 9 January 2019), ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP). We used no language restrictions. We checked the reference lists of retrieved studies for additional reports of relevant studies.

SELECTION CRITERIA

We included randomised and quasi-randomised controlled trials (RCTs) of blinded or opeṉlabel design that randomised participants individually (i.e. cluster-randomised trials were excluded). We included cross-over trials if each treatment period was at least 12 weeks in length and the trial had a suitable wash-out period. Types of interventions included: women with any pattern of catamenial epilepsy who received a hormonal or non-hormonal drug intervention in addition to an existing antiepileptic drug regimen for a minimum treatment duration of 12 weeks.

DATA COLLECTION AND ANALYSIS

We extracted data on study design factors and participant demographics for the included studies. The primary outcomes of interest were: proportion seizure-free, proportion of responders (at least 50% decrease in seizure frequency from baseline), and mean change in seizure frequency. Secondary outcomes included: number of withdrawals, number of women experiencing adverse events of interest (seizure exacerbation, cardiac events, thromboembolic events, osteoporosis and bone health, mood disorders, sedation, menstrual cycle disorders, and fertility issues), and quality of life outcomes.

MAIN RESULTS

We identified 62 records from the databases and search strategies. Following title, abstract, and full-text screening, we included eight full-text articles reporting on four double-blind, placebo-controlled RCTs. We included two cross-over RCTs of pulsed norethisterone and two parallel RCTs of pulsed progesterone recruiting a total of 192 women aged between 13 and 45 years with catamenial epilepsy. We found no RCTs for non-hormonal treatments of catamenial epilepsy or for women with irregular menses.Meta-analysis was not possible for the primary outcomes, therefore we undertook a narrative synthesis. For the two RCTs evaluating norethisterone versus placebo (24 participants), there were no reported treatment differences for mean change in seizure frequency. Outcomes for the proportion seizure-free and 50% responders were not reported. For the RCTs evaluating progesterone versus placebo (168 participants), the studies reported conflicting results on the primary outcomes. One progesterone RCT reported no significant difference between progesterone 600 mg/day taken on day 14 to 28 and placebo with respect to 50% responders, seizure freedom rates, and change in seizure frequency for any seizure type. The other progesterone RCT reported that the decrease in seizure frequency from baseline in the progesterone group was significantly higher than the decrease in seizure frequency from baseline in the placebo group.Results of secondary efficacy outcomes showed no significant difference in terms of treatment withdrawal for any reason in the pooled progesterone RCTs when compared to placebo (pooled risk ratio (RR) 1.56, 95% confidence interval (CI) 0.81 to 3.00, P = 0.18, I² = 0%) or for treatment withdrawals due to adverse events (pooled RR 2.91, 95% CI 0.53 to 16.17, P = 0.22, I² = 0%). No treatment withdrawals from the norethisterone RCTs were reported. The RCTs reported limited information on adverse events, although one progesterone RCT reported no significant difference in the number of women experiencing adverse events (diarrhoea, dyspepsia, nausea, vomiting, fatigue, nasopharyngitis, dizziness, headache, and depression). No studies reported on quality of life.We judged the evidence from the included progesterone RCTs to be of low to moderate certainty due to risk of bias and from the included norethisterone RCTs to be of very low certainty due to serious imprecision and risk of bias.

AUTHORS' CONCLUSIONS

This review provides very low-certainty evidence of no treatment difference between norethisterone and placebo, and moderate- to low-certainty evidence of no treatment difference between progesterone and placebo for catamenial epilepsy. However, as all the included studies were underpowered, important clinical effects cannot be ruled out.Our review highlighted an overall deficiency in the literature base on the effectiveness of a wide range of other hormonal and non-hormonal interventions currently being used in practice, particularly for those patients who do not have regular menses. Further clinical trials are needed in this area.

Methods for the Detection of Seizure Bursts in Epilepsy

Background: Seizure clusters and “bursts” are of clinical importance. Clusters are reported to be a marker of antiepileptic drug resistance. Additionally, seizure clustering has been found to be associated with increased morbidity and mortality. However, there are no statistical methods described in the literature to delineate bursting phenomenon in epileptic seizures.

Methods: We present three automatic burst detection methods referred to as precision constrained grouping (PCG), burst duration constrained grouping (BCG), and interseizure interval constrained grouping (ICG). Concordance correlation coefficients were used to confirm the pairwise agreement between common bursts isolated using these three automatic burst detection procedures. Additionally, three graphical methods were employed to demonstrate seizure bursts: modified scatter plots, staircase plots, and dropline plots. Burst detection procedures are demonstrated on data from continuous intracranial ambulatory EEG monitoring in a patient diagnosed with drug-refractory focal epilepsy.

Results: We analyzed 1,569 seizures, from our assigned index patient, captured on ambulatory intracranial EEG monitoring. A total of 31, 32, and 32 seizure bursts were detected by the three quantitative methods (BCG, ICG, and PCG), respectively. The concordance correlation coefficient was ≥0.99 signifying considerably stronger than chance burst detector agreements with one another.

Conclusions: Bursting is a quantifiable temporal phenomenon in epilepsy and seizure bursts can be reliably detected using our methodology.

Neurosteroid regulation of GABAA receptors: A role in catamenial epilepsy

The female reproductive hormones progesterone and estrogen regulate network excitability. Fluctuations in the circulating levels of these hormones during the menstrual cycle cause frequent seizures during certain phases of the cycle in women with epilepsy. This seizure exacerbation, called catamenial epilepsy, is a dominant form of drug-refractory epilepsy in women of reproductive age. Progesterone, through its neurosteroid derivative allopregnanolone, increases γ-aminobutyric acid type-A receptor (GABAR)-mediated inhibition in the brain and keeps seizures under control. Catamenial seizures are believed to be a neurosteroid withdrawal symptom, and it was hypothesized that exogenous administration of progesterone to maintain its levels high during luteal phase will treat catamenial seizures. However, in a multicenter, double-blind, phase III clinical trial, progesterone treatment did not suppress catamenial seizures. The expression of GABARs with reduced neurosteroid sensitivity in epileptic animals may explain the failure of the progesterone clinical trial. The expression of neurosteroid-sensitive δ subunit-containing GABARs is reduced, and the expression of α4γ2 subunit-containing GABARs is upregulated, which alters the inhibition of dentate granule cells in epilepsy. These changes reduce the endogenous neurosteroid control of seizures and contribute to catamenial seizures.

Semiology, clustering, periodicity and natural history of seizures in an experimental occipital cortical epilepsy model

Focal neocortical epilepsy is a common form of epilepsy and there is a need to develop animal models that allow the evaluation of novel therapeutic strategies to treat this type of epilepsy. Tetanus toxin (TeNT) injection into the rat visual cortex induces focal neocortical epilepsy without preceding status epilepticus. The latency to first seizure ranged from 3 to 7 days. Seizure duration was bimodal, with both short (approximately 30 s) and long-lasting (>100 s) seizures occurring in the same animals. Seizures were accompanied by non-motor features such as behavioural arrest, or motor seizures with or without evolution to generalized tonic-clonic seizures. Seizures were more common during the sleep phase of a light-dark cycle. Seizure occurrence was not random, and tended to cluster with significantly higher probability of recurrence within 24 h of a previous seizure. Across animals, the number of seizures in the first week could be used to predict the number of seizures in the following 3 weeks. The TeNT model of occipital cortical epilepsy is a model of acquired focal neocortical epilepsy that is well-suited for preclinical evaluation of novel anti-epileptic strategies. We provide here a detailed analysis of the epilepsy phenotypes, seizure activity, electrographic features and the semiology. In addition, we provide a predictive framework that can be used to reduce variation and consequently animal use in preclinical studies of potential treatments.

Prevalence and predictors of seizure clusters: A prospective observational study of adult patients with epilepsy

OBJECTIVE

The purpose of this prospective observational study was to describe the prevalence and adverse outcomes associated with seizure clusters (defined as ≥2 seizures in a 6-hour period) in a large sample of adult patients with a range of epilepsy severities and to identify clinical characteristics predictive of clustering.

METHODS

Patients maintained a seizure diary and were contacted monthly to verify compliance and data accuracy. Logistic regression models were utilized to test associations between individual patient demographic/clinical characteristics and seizure clustering. Fisher's exact test was utilized to test associations between rescue medication use and adverse seizure-related outcomes.

RESULTS

A total of 300 patients were followed prospectively for one year; 247 patients qualified for final analysis. Six-hour seizure clusters occurred in 45.8% of patients with active epilepsy at enrollment, including 62.7% of those with prior day-clusters and 30.0% of those without prior day-clusters. The odds of clustering were markedly greater among patients who reported a higher seizure frequency (>4 seizures per year vs. 1-4 seizures per year) (adjusted odds ratio (OR): 8.9; 95% confidence interval (CI): 3.2-24.6; p < 0.0001) and among patients with prior day-clusters (adjusted OR: 11.0; 95% CI: 1.2-104.2; p = 0.036). Rescue medication use was associated with significantly fewer injuries and emergency department visits, but rescue medication was underutilized.

CONCLUSIONS

Seizure clusters are common, occurring in nearly half of adult patients with active epilepsy followed prospectively over one year, and are more frequent in those with higher seizure frequencies and prior day-clusters. Although underutilized, rescue medication was associated with fewer injuries and emergency department visit.

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.

Epilepsy as a dynamic disease: A Bayesian model for differentiating seizure risk from natural variability

Objective

A fundamental challenge in treating epilepsy is that changes in observed seizure frequencies do not necessarily reflect changes in underlying seizure risk. Rather, changes in seizure frequency may occur due to probabilistic variation around an underlying seizure risk state caused by normal fluctuations from natural history, leading to seizure unpredictability and potentially suboptimal medication adjustments in epilepsy management. However, no rigorous statistical approach exists to systematically distinguish expected changes in seizure frequency due to natural variability from changes in underlying seizure risk.

Methods

Using data from SeizureTracker.com, a patient‐reported seizure diary tool containing over 1.2 million recorded seizures across 8 years, a novel epilepsy seizure risk assessment tool (EpiSAT) employing a Bayesian mixed‐effects hidden Markov model for zero‐inflated count data was developed to estimate changes in underlying seizure risk using patient‐reported seizure diary and clinical measurement data. Accuracy for correctly assessing underlying seizure risk was evaluated through a simulation comparison. Implications for the natural history of tuberous sclerosis complex (TSC) were assessed using data from SeizureTracker.com.

Results

EpiSAT led to significant improvement in seizure risk assessment compared to traditional approaches relying solely on observed seizure frequencies. Applied to TSC, four underlying seizure risk states were identified. The expected duration of each state was <12 months, providing a data‐driven estimate of the amount of time a person with TSC would be expected to remain at the same seizure risk level according to the natural course of epilepsy.

Significance

We propose a novel Bayesian statistical approach for evaluating seizure risk on an individual patient level using patient‐reported seizure diaries, which allows for the incorporation of external clinical variables to assess impact on seizure risk. This tool may improve the ability to distinguish true changes in seizure risk from natural variations in seizure frequency in clinical practice. Incorporation of systematic statistical approaches into antiepileptic drug (AED) management may help improve understanding of seizure unpredictability as well as timing of treatment interventions for people with epilepsy.

Identifying seizure clusters in patients with psychogenic nonepileptic seizures

The present study explored how seizure clusters may be defined for those with psychogenic nonepileptic seizures (PNES), a topic for which there is a paucity of literature. The sample was drawn from a multisite randomized clinical trial for PNES; seizure data are from participants' seizure diaries. Three possible cluster definitions were examined: 1) common clinical definition, where ≥3 seizures in a day is considered a cluster, along with two novel statistical definitions, where ≥3 seizures in a day are considered a cluster if the observed number of seizures statistically exceeds what would be expected relative to a patient's: 1) average seizure rate prior to the trial, 2) observed seizure rate for the previous seven days. Prevalence of clusters was 62-68% depending on cluster definition used, and occurrence rate of clusters was 6-19% depending on cluster definition. Based on these data, clusters seem to be common in patients with PNES, and more research is needed to identify if clusters are related to triggers and outcomes.

Prevalence and risk factors of seizure clusters in adult patients with epilepsy

PURPOSE

In the current study, we explored the prevalence of physician-confirmed seizure clusters. We also investigated potential clinical factors associated with the occurrence of seizure clusters overall and by epilepsy type.

METHODS

We reviewed medical records of 4116 adult (≥16years old) outpatients with epilepsy at our centers for documentation of seizure clusters. Variables including patient demographics, epilepsy details, medical and psychiatric history, AED history, and epilepsy risk factors were then tested against history of seizure clusters. Patients were then divided into focal epilepsy, idiopathic generalized epilepsy (IGE), or symptomatic generalized epilepsy (SGE), and the same analysis was run.

RESULTS

Overall, seizure clusters were independently associated with earlier age of seizure onset, symptomatic generalized epilepsy (SGE), central nervous system (CNS) infection, cortical dysplasia, status epilepticus, absence of 1-year seizure freedom, and having failed 2 or more AEDs (P<0.0026). Patients with SGE (27.1%) were more likely to develop seizure clusters than patients with focal epilepsy (16.3%) and IGE (7.4%; all P<0.001). Analysis by epilepsy type showed that absence of 1-year seizure freedom since starting treatment at one of our centers was associated with seizure clustering in patients across all 3 epilepsy types. In patients with SGE, clusters were associated with perinatal/congenital brain injury. In patients with focal epilepsy, clusters were associated with younger age of seizure onset, complex partial seizures, cortical dysplasia, status epilepticus, CNS infection, and having failed 2 or more AEDs. In patients with IGE, clusters were associated with presence of an aura. Only 43.5% of patients with seizure clusters were prescribed rescue medications.

CONCLUSION

Patients with intractable epilepsy are at a higher risk of developing seizure clusters. Factors such as having SGE, CNS infection, cortical dysplasia, status epilepticus or an early seizure onset, can also independently increase one's chance of having seizure clusters.

Bursts of seizures in long-term recordings of human focal epilepsy

OBJECTIVE

We report on temporally clustered seizures detected from continuous long-term ambulatory human electroencephalographic data. The objective was to investigate short-term seizure clustering, which we have termed bursting, and consider implications for patient care, seizure prediction, and evaluating therapies.

METHODS

Chronic ambulatory intracranial electroencephalography (EEG) data collected for the purpose of seizure prediction were annotated to identify seizure events. A detection algorithm was used to identify bursts of events. Burst events were compared to nonburst events to evaluate event dispersion, duration and dynamics.

RESULTS

Bursts of seizures were present in 6 of 15 subjects, and detections were consistent over long-term monitoring (>2 years). Subjects with bursts of seizures had highly overdispersed seizure rates, compared to other subjects. There was a complicated relationship between bursts and clinical seizures, although bursts were associated with multimodal distributions of seizure duration, and poorer predictive outcomes. For three subjects, bursts demonstrated distinctive preictal dynamics compared to clinical seizures.

SIGNIFICANCE

We have previously hypothesized that there are distinct physiologic pathways underlying short- and long-duration seizures. Herein we show that burst seizures fall almost exclusively within the short population of seizure durations; however, a short duration event was not sufficient to induce or imply bursting. We can therefore conclude that in addition to distinct mechanisms underlying seizure duration, there are separate factors regulating bursts of seizures. We show that bursts were a robust phenomenon in our patient cohort, which were consistent with overdispersed seizure rates, suggesting long-memory dynamics.

Perimenstrual Catamenial Epilepsy

Epilepsy affects 50 million people worldwide, including women afflicted with catamenial epilepsy. Catamenial epilepsy is a form of epilepsy in which seizures are clustered around specific points in the menstrual cycle, most frequently during the perimenstrual or periovulatory phase. Although there are a number of standard and newer antiepileptic drugs for epilepsy, no specific drugs exist to treat catamenial seizures, which affect at least one in three women with epilepsy. Moreover, the molecular pathophysiology of catamenial seizures remains unclear. This article describes the pathophysiology, hormonal basis, diagnosis and treatment of perimenstrual catamenial epilepsy. Natural progesterone and synthetic neurosteroid replacement appears to be a suitable therapeutic approach for catamenial epilepsy.

Perspectives on seizure clusters: Gaps in lexicon, awareness, and treatment

Seizure clusters in epilepsy can result in serious outcomes such as missed work or school, postictal psychosis, emergency room visits, or hospitalizations, and yet they are often not included in discussions between health-care professionals (HCPs) and their patients. The purpose of this paper was to describe and compare consumer (patient and caregivers) and professional understanding of seizure clusters and to describe how consumers and HCPs communicate regarding seizure clusters. We reviewed social media discussion sites to explore consumers' understanding of seizure clusters. We analyzed professional (medical) literature to explore the HCPs' understanding of seizure clusters. Major themes were revealed in one or both groups, including: communication about diagnosis; frequency, duration, and time frame; seizure type and pattern; severity; and self-management. When comparing discussions of professionals and consumers, both consumers and clinicians discussed the definition of seizure clusters. Discussions of HCPs were understandably clinically focused, and consumer discussions reflected the experience of seizure clusters; however, both groups struggled with a common lexicon. Seizure cluster events remain a problem associated with serious outcomes. Herein, we outline the lack of a common understanding and recommend the development of a common lexicon to improve communication regarding seizure clusters.

Interictal spikes and epileptic seizures: their relationship and underlying rhythmicity

We report on a quantitative analysis of electrocorticography data from a study that acquired continuous ambulatory recordings in humans over extended periods of time. The objectives were to examine patterns of seizures and spontaneous interictal spikes, their relationship to each other, and the nature of periodic variation. The recorded data were originally acquired for the purpose of seizure prediction, and were subsequently analysed in further detail. A detection algorithm identified potential seizure activity and a template matched filter was used to locate spikes. Seizure events were confirmed manually and classified as either clinically correlated, electroencephalographically identical but not clinically correlated, or subclinical. We found that spike rate was significantly altered prior to seizure in 9 out of 15 subjects. Increased pre-ictal spike rate was linked to improved predictability; however, spike rate was also shown to decrease before seizure (in 6 out of the 9 subjects). The probability distribution of spikes and seizures were notably similar, i.e. at times of high seizure likelihood the probability of epileptic spiking also increased. Both spikes and seizures showed clear evidence of circadian regulation and, for some subjects, there were also longer term patterns visible over weeks to months. Patterns of spike and seizure occurrence were highly subject-specific. The pre-ictal decrease in spike rate is not consistent with spikes promoting seizures. However, the fact that spikes and seizures demonstrate similar probability distributions suggests they are not wholly independent processes. It is possible spikes actively inhibit seizures, or that a decreased spike rate is a secondary symptom of the brain approaching seizure. If spike rate is modulated by common regulatory factors as seizures then spikes may be useful biomarkers of cortical excitability.

Human focal seizures are characterized by populations of fixed duration and interval

OBJECTIVE

We report on a quantitative analysis of data from a study that acquired continuous long-term ambulatory human electroencephalography (EEG) data over extended periods. The objectives were to examine the seizure duration and interseizure interval (ISI), their relationship to each other, and the effect of these features on the clinical manifestation of events.

METHODS

Chronic ambulatory intracranial EEG data acquired for the purpose of seizure prediction were analyzed and annotated. A detection algorithm identified potential seizure activity, which was manually confirmed. Events were classified as clinically corroborated, electroencephalographically identical but not clinically corroborated, or subclinical. K-means cluster analysis supplemented by finite mixture modeling was used to locate groupings of seizure duration and ISI.

RESULTS

Quantitative analyses confirmed well-resolved groups of seizure duration and ISIs, which were either mono-modal or multimodal, and highly subject specific. Subjects with a single population of seizures were linked to improved seizure prediction outcomes. There was a complex relationship between clinically manifest seizures, seizure duration, and interval.

SIGNIFICANCE

These data represent the first opportunity to reliably investigate the statistics of seizure occurrence in a realistic, long-term setting. The presence of distinct duration groups implies that the evolution of seizures follows a predetermined course. Patterns of seizure activity showed considerable variation between individuals, but were highly predictable within individuals. This finding indicates seizure dynamics are characterized by subject-specific time scales; therefore, temporal distributions of seizures should also be interpreted on an individual level. Identification of duration and interval subgroups may provide a new avenue for improving seizure prediction.

Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating

Seizure activity in EEG recordings can persist for hours with seizure dynamics changing rapidly over time and space. To characterise the spatiotemporal evolution of seizure activity, large data sets often need to be analysed. Dynamic causal modelling (DCM) can be used to estimate the synaptic drivers of cortical dynamics during a seizure; however, the requisite (Bayesian) inversion procedure is computationally expensive. In this note, we describe a straightforward procedure, within the DCM framework, that provides efficient inversion of seizure activity measured with non-invasive and invasive physiological recordings; namely, EEG/ECoG. We describe the theoretical background behind a Bayesian belief updating scheme for DCM. The scheme is tested on simulated and empirical seizure activity (recorded both invasively and non-invasively) and compared with standard Bayesian inversion. We show that the Bayesian belief updating scheme provides similar estimates of time-varying synaptic parameters, compared to standard schemes, indicating no significant qualitative change in accuracy. The difference in variance explained was small (less than 5%). The updating method was substantially more efficient, taking approximately 5–10 min compared to approximately 1–2 h. Moreover, the setup of the model under the updating scheme allows for a clear specification of how neuronal variables fluctuate over separable timescales. This method now allows us to investigate the effect of fast (neuronal) activity on slow fluctuations in (synaptic) parameters, paving a way forward to understand how seizure activity is generated.

•

We describe a DCM procedure that provides efficient inversion of seizure activity.

•

Similar accuracy but substantially more efficient compared to standard DCM methods.

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Physiological fluctuations over different timescales can be specified.

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This scheme should contribute to understanding seizure activity using DCM.

Use of an online epilepsy diary to characterize repetitive seizures

SIGNIFICANCE

Little is known about patterns of seizures that occur multiple times a day, sometimes called clusters or serial seizures.

OBJECTIVE

The online diary, My Epilepsy Diary (MED), provided self-reported data from community-based patients to describe the characteristics of clusters.

METHODS

We used MED data to define a population of 5098 community outpatients, including 1177 who specified time of multiple seizures in a 24-hour period. Outcomes included cluster prevalence and frequency, distribution of interseizure time intervals, as well as the types of triggers commonly reported.

RESULTS

One-fourth of days with any seizures included clusters for these patients. Most days with clusters included 2 seizures, with >5 events occurring in only 10% of days. One-third of seizures occurred within 3h of the initial event and two-thirds within 6h. When more than 2 seizures occurred, the time to the next seizure decreased from an average of over 2h (to the 3rd event) to a quarter-hour (from the 4th to the 5th event).

CONCLUSION

My Epilepsy Diary data have provided the first overview of cluster seizures in a large community-based population. Treatments with less than 3-hour duration of action would be bioavailable at the time of only one-third of subsequent seizures. Although limited by the self-reported and observational nature of the diary data, some general patterns emerge and can help to focus questions for future studies.

Catamenial epilepsy: Update on prevalence, pathophysiology and treatment from the findings of the NIH Progesterone Treatment Trial

PURPOSE

To extend our knowledge and practical application of the concept of catamenial epilepsy.

METHODS

The review focuses on the impact of the NIH Progesterone Trial on our understanding of the pathophysiology and treatment of catamenial epilepsy.

RESULTS

Catamenial epilepsy refers to the cyclic exacerbation of seizures in relation to the menstrual cycle. An interaction between seizures and the menstrual cycle is suggested by variations in seizure frequency according to the day, phase and ovulatory status of the menstrual cycle. There are three commonly recognized patterns: perimenstrual (C1: Day -3 to +3), peri-ovulatory (C2: Day 10 to 3) and entire luteal phase in anovulatory cycles (C3: Day 10 to 3). Pathophysiological determinants include 1) the neuroactive properties of reproductive steroids, 2) the variation of neuroactive steroid levels across the menstrual cycle and 3) the differential susceptibility of epileptic substrates to neuroactive steroid effects. Perimenstrual seizure exacerbation may result from the premenstrual withdrawal of progesterone which is accompanied by withdrawal of allopregnanolone, a potent positive allosteric modulator of the GABAA receptor, and changes in the subunit composition of the GABAA receptor to the α4 subtype which is insensitive to benzodiazepine and GABA. Bioidentical progesterone supplement is no better than placebo in the treatment of women with focal onset epilepsy overall but shows superior efficacy in women whose seizures show robust perimenstrual exacerbation.

CONCLUSION

There is sound evidence for the existence of catamenial epilepsy and class 3 evidence for adjunctive progesterone treatment of the perimenstrually exacerbated subtype.

The dynamics of the epileptic brain reveal long-memory processes

The pattern of epileptic seizures is often considered unpredictable and the interval between events without correlation. A number of studies have examined the possibility that seizure activity respects a power-law relationship, both in terms of event magnitude and inter-event intervals. Such relationships are found in a variety of natural and man-made systems, such as earthquakes or Internet traffic, and describe the relationship between the magnitude of an event and the number of events. We postulated that human inter-seizure intervals would follow a power-law relationship, and furthermore that evidence for the existence of a long-memory process could be established in this relationship. We performed a post hoc analysis, studying eight patients who had long-term (up to 2 years) ambulatory intracranial EEG data recorded as part of the assessment of a novel seizure prediction device. We demonstrated that a power-law relationship could be established in these patients (β = - 1.5). In five out of the six subjects whose data were sufficiently stationary for analysis, we found evidence of long memory between epileptic events. This memory spans time scales from 30 min to 40 days. The estimated Hurst exponents range from 0.51 to 0.77 ± 0.01. This finding may provide evidence of phase-transitions underlying the dynamics of epilepsy.

Women and epilepsy: review and practical recommendations

Individuals with epilepsy experience a number of sex-specific problems. In women, pregnancy and delivery are obvious issues, fertility problems are more often encountered and they also seem to have a higher frequency of sexual problems. A large number of women with epilepsy experience seizure exacerbation in relation to the menstrual cycle and have higher frequencies of menstrual disturbances and polycystic ovaries. Cosmetic problems affecting skin, hair or weight may also be drug induced. The use of antiepileptic drugs may influence the effect of contraceptives leading to unplanned pregnancies and contraceptives may affect the serum levels of antiepileptic drugs. The care of pregnant women with epilepsy requires attention to a number of guidelines and close cooperation between neurologist and gynecologist is recommended. Although the majority of the women with epilepsy experience normal pregnancies and deliveries, their children have a higher risk of birth defects. At menopause, their seizure pattern may change and some antiepileptic drugs may increase the risk of osteoporosis. The optimal treatment of women with epilepsy should take into account these gender-specific issues in the different stages of life.

Neurosteroids and epileptogenesis

Epileptogenesis is defined as the latent period at the end of which spontaneous recurrent seizures occur. This concept has been recently re-evaluated to include exacerbation of clinically-manifested epilepsy. Thus, in patients affected by pharmacoresistant seizures, the progression toward a worse condition may be viewed as the result of a durable epileptogenic process. However, the mechanism potentially responsible for this progression remains unclear. Neuroinflammation has been consistently detected both in the latent period and in the chronic phase of epilepsy, especially when brain damage is present. This phenomenon is accompanied by glial cell reaction, leading to gliosis. We have previously described rats presenting an increased expression of the cytochrome P450 cholesterol side-chain cleavage (P450scc) enzyme, during the latent period, in glial cells of the hippocampus. The P450scc enzyme is critically involved in the synthesis of neurosteroids and its up-regulation is associated with a delayed appearance of spontaneous recurrent seizures in rats that experienced status epilepticus induced by pilocarpine. Moreover, by decreasing the synthesis of neurosteroids able to promote inhibition, such as allopregnanolone, through the administration of the 5α-reductase blocker finasteride, it is possible to terminate the latent period in pilocarpine-treated rats. Finasteride was also found to promote seizures in the chronic period of epileptic rats, suggesting that neurosteroids are continuously produced to counteract seizures. In humans, exacerbation of epilepsy has been also described in patients occasionally exposed to finasteride. Overall, these findings suggest a major role of neurosteroids in the progression of epilepsy and a possible antiepileptogenic role of allopregnanolone and cognate molecules.

Proposing a two-level stochastic model for epileptic seizure genesis

By assuming the brain as a multi-stable system, different scenarios have been introduced for transition from normal to epileptic state. But, the path through which this transition occurs is under debate. In this paper a stochastic model for seizure genesis is presented that is consistent with all scenarios: a two-level spontaneous seizure generation model is proposed in which, in its first level the behavior of physiological parameters is modeled with a stochastic process. The focus is on some physiological parameters that are essential in simulating different activities of ElectroEncephaloGram (EEG), i.e., excitatory and inhibitory synaptic gains of neuronal populations. There are many depth-EEG models in which excitatory and inhibitory synaptic gains are the adjustable parameters. Using one of these models at the second level, our proposed seizure generator is complete. The suggested stochastic model of first level is a hidden Markov process whose transition matrices are obtained through analyzing the real parameter sequences of a seizure onset area. These real parameter sequences are estimated from real depth-EEG signals via applying a parameter identification algorithm. In this paper both short-term and long-term validations of the proposed model are done. The long-term synthetic depth-EEG signals simulated by this model can be taken as a suitable tool for comparing different seizure prediction algorithms.

Progesterone therapy in women with intractable catamenial epilepsy

Background:

Catamenial epilepsy is a kind of epilepsy, known in this name, when the periodicity of the exacerbation of the seizure is in association with menstural cycle. The present study examined the progesterone effectiveness as a complementary treatment in women with intractable catamenial epilepsy.

Materials and Methods:

The present study was conducted as a double-blind randomized controlled trial on 38 women with intractable catamenial epilepsy. Patients were assessed in two groups: The case group received in addition to AEDs, two (Mejestrol) 40 mg progesterone tablets in the second half of the cycle from 15^th to 25^th day. And the control group received in addition to AEDs, two placebo tablets daily. Age, BMI, epilepsy duration, types of the drugs used, progesterone level, and the number of the seizures in 3 months before and after the study were compared.

Results:

Based on the results of which there was no statistically significant difference in regard to age, BMI, epilepsy duration, types of the drugs used, progesterone level between the case and the control groups (P-value > 0.05). The number of the seizures after treatment has significantly decreased compared to before-treatment state. The degree of decreasing in the case group receiving the progesterone was higher than in the control group receiving the placebo. The difference, thus, is significant, based on statistical tests (P-value = 0.024).

Conclusion:

Based on the findings of this study using progesterone in women with intractable catamenial epilepsy has a significant effect on the degree of decreasing in the number of the seizures.

Progesterone vs placebo therapy for women with epilepsy: A randomized clinical trial

OBJECTIVE

To assess progesterone treatment of intractable seizures in women with partial epilepsy.

METHODS

This randomized, double-blind, placebo-controlled, phase III, multicenter, clinical trial compared the efficacy and safety of adjunctive cyclic natural progesterone therapy vs placebo treatment of intractable seizures in 294 subjects randomized 2:1 to progesterone or placebo, stratified by catamenial and noncatamenial status. It compared treatments on proportions of ≥50% responders and changes in seizure frequency from 3 baseline to 3 treated menstrual cycles.

RESULTS

There was no significant difference in proportions of responders between progesterone and placebo in the catamenial and noncatamenial strata. Prespecified secondary analysis showed that the level of perimenstrual seizure exacerbation (C1 level) was a significant predictor of responders for progesterone but not placebo. With increasing C1 levels, responders increased from 21% to 57% with progesterone vs 19% to 20% with placebo. Reductions in seizure frequency correlated with increasing C1 levels for progesterone but not placebo, progressing from 26% to 71% for progesterone vs 25% to 26% for placebo. A prespecified clinically important separation between progesterone and placebo responders (37.8% vs 11.1%; p = 0.037) was realized among 21.4% of women who had C1 level ≥3.

CONCLUSION

There was no difference in the primary outcome of ≥50% responder rates between progesterone vs placebo for catamenial or noncatamenial groups. Post hoc findings suggest that the level of perimenstrual seizure exacerbation is a significant predictor of responder rate with progesterone and that progesterone may provide clinically important benefit for a subset of women with perimenstrually exacerbated seizures.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that cyclic progesterone is ineffective in women with intractable partial epilepsy. Post hoc analysis identified a subset of women with higher levels of perimenstrual seizure exacerbation that were responsive to treatment.

Seizure duration determined by subdural electrode recordings in adult patients with intractable focal epilepsy

BACKGROUND AND PURPOSE

To investigate the duration of seizures and its relationship to seizure type, epilepsy syndrome, and seizure clustering.

METHODS

We examined 1,251 seizures from 152 patients who underwent video-electrocorticographic monitoring with subdural electrodes. Their seizure duration, seizure types, epilepsy syndromes, and seizure clusters were analyzed.

RESULTS

The median seizure duration was 91.5s (4-1016s). There were 34 (2.7%) seizures lasting > 5 minutes in 20 (13.2%) patients. There was a significant difference in seizure duration according to seizure types (p < 0.0001), but not to epilepsy syndromes. There were 99 seizure clusters in 67 (44.1%) patients. The first seizure in a cluster of seizures tended to last longer than non-cluster seizures (median 98s versus 89s, p = 0.033). Seizure duration was significantly longer in mesial temporal lobe epilepsy than in neocortical lobe epilepsy (median 103s versus 87s, p = 0.041). Rate of seizure cluster was lower in mTLE (38.0%) than in NLE (47.1%), but this difference was not significant.

CONCLUSIONS

Seizure durations were different among seizure types. Seizure clustering also differ between patients with mTLE and those with NLE, which suggests different seizure generation and propagation among different epileptogenic foci. This study has implications for the identification of abnormally prolonged seizures.

An online diary for tracking epilepsy

My Epilepsy Diary is a free Web-based application on the public website epilepsy.com, available for patients to track epilepsy and to aid clinicians with data-based, individualized management. The first aim of this descriptive study was to outline electronic diary functions. Second, the study retrospectively profiled a large cohort of 2010 calendar year diary users including demographics, seizure types, temporal distribution of seizures, triggers, and use and side effects of antiepileptic drugs (AEDs). A total of 1944 users provided demographic information and 1877 recorded seizure data. Most (64%) users were women. Average age was 29.9±16.0 years. A total of 70,990 seizure entries and 15,630 AED entries were logged. Events were apportioned as 79% seizures and 21% seizure clusters. Specific AEDs were detailed in 7331 entries: monotherapy was used in 18% and polytherapy in 82%. Mood-related side effects were most commonly reported in 19% of 1027 users.

Modeling longitudinal daily seizure frequency data from pregabalin add-on treatment

The purpose of this study was to describe longitudinal daily seizure count data with respect to the effects of time and pregabalin add-on therapy. Models were developed in a stepwise manner: base model, time effect model, and time and drug effect (final) model, using a negative binomial distribution with Markovian features. Mean daily seizure count (λ) was estimated to be 0.385 (relative standard error [RSE] 3.09%) and was further increased depending on the seizure count on the previous day. An overdispersion parameter (OVDP), representing extra-Poisson variation, was estimated to be 0.330 (RSE 11.7%). Interindividual variances on λ and OVDP were 84.7% and 210%, respectively. Over time, λ tended to increase exponentially with a rate constant of 0.272 year⁻¹ (RSE 26.8%). A mixture model was applied to classify responders/nonresponders to pregabalin treatment. Within the responders, λ decreased exponentially with respect to dose with a constant of 0.00108 mg⁻¹ (RSE 11.9%). The estimated responder rate was 66% (RSE 27.6%). Simulation-based diagnostics showed the model reasonably reproduced the characteristics of observed data. Highly variable daily seizure frequency was successfully characterized incorporating baseline characteristics, time effect, and the effect of pregabalin with classification of responders/nonresponders, all of which are necessary to adequately assess the efficacy of antiepileptic drugs.

Catamenial epilepsy: hormonal aspects

The term catamenial epilepsy is used to describe the cyclical occurrence of seizure exacerbations during particular phases of menstrual cycle in women with preexisting epilepsy. Recent investigations have demonstrated the existence of at least three patterns of catamenial seizure exacerbation: perimenstrual and periovulatory in ovulatory cycle and entire luteal phase in anovulatory cycle. Cyclical changes in the circulating levels of estrogens (proconvulsant) and progesterone (anticonvulsant) play a central role in the development of catamenial epilepsy. Also, variations in concentrations of antiepileptic drugs across the menstrual cycle may contribute to increased seizure susceptibility. A variety of approaches have been proposed for the treatment of catamenial epilepsy.

Predicting seizures: a behavioral approach

This article reviews the epilepsy cycle, distinguishing the interictal, preictal, ictal, and postictal phases. Evidence suggesting that the preictal phase can sometimes be identified based on neurophysiologic signals, premonitory features, the presence of trigger factors, or self-report is also reviewed. Diary studies have shown that seizures are not randomly distributed in time and that a subgroup of persons with epilepsy can predict an impending seizure. Paper diary data and preliminary analysis of electronic diary data suggest that seizure prediction is feasible. Whereas all of this evidence sets the stage for seizure prediction and preemptive therapy, several questions remain unanswered. First, what proportion of persons with epilepsy can predict their seizures? Second, within and among individuals, how accurate is prediction? Third, can prediction be improved through education about group level or individual predictors? And finally, in a group that can make robust predictions what are the most effective interventions for reducing seizure probability at times of high risk? The answers to these questions could reduce the burden of epilepsy by making seizures predictable and setting the stage for preemptive therapy. This work could improve the understanding of epilepsy by providing a context for studying the transitions from the interictal to preictal and ictal states. More prospective studies are needed; challenges certainly exist, but as the studies discussed here demonstrate, the field is rich with promise for improving the lives of patients with epilepsy.

Continuous electroencephalographic monitoring with radio-telemetry in a rat model of perinatal hypoxia-ischemia reveals progressive post-stroke epilepsy

The development of acquired epilepsy after a perinatal hypoxic-ischemic (HI) insult was investigated in rats. After unilateral carotid ligation with hypoxia on postnatal day 7, cortical electroencephalographic and behavioral seizures were recorded with continuous radio-telemetry and video. Chronic recordings were obtained between 2 and 12 months of age in freely behaving HI-treated and sham control rats. The hypotheses were that the acquired epilepsy is directly associated with an ischemic infarct (i.e., no lesion, no epilepsy), and the resultant epilepsy is temporally progressive. Every HI-treated rat with a cerebral infarct developed spontaneous epileptiform discharges and recurrent seizures (100%); in contrast, no spontaneous epileptiform discharges or seizures were detected with continuous monitoring in the HI-treated rats without infarcts. The initial seizures at 2 months generally showed focal onset and were nonconvulsive. Subsequent seizures had focal onsets that propagated to the homotopic contralateral cortex and were nonconvulsive or partial; later seizures often appeared to have bilateral onset and were convulsive. Spontaneous epileptiform discharges were initially lateralized to ipsilateral neocortex but became bilateral over time. The severity and frequency of the spontaneous behavioral and electrographic seizures progressively increased over time. In every epileptic rat, seizures occurred in distinct clusters with seizure-free periods as long as a few weeks. The progressive increase in seizure frequency over time was associated with increases in cluster frequency and seizures within each cluster. Thus, prolonged, continuous seizure monitoring directly demonstrated that the acquired epilepsy after perinatal HI was progressive with seizure clusters and was consistently associated with a cerebral infarct.

The role of neurosteroids in the pathophysiology and treatment of catamenial epilepsy

Catamenial epilepsy is a multifaceted neuroendocrine condition in which seizures are clustered around specific points in the menstrual cycle, most often around perimenstrual or periovulatory period. Generally, a twofold or greater increase in seizure frequency during a particular phase of the menstrual cycle could be considered as catamenial epilepsy. Based on this criteria, recent clinical studies indicate that catamenial epilepsy affects 31-60% of the women with epilepsy. Three types of catamenial seizures (perimenstrual, periovulatory and inadequate luteal) have been identified. However, there is no specific drug available today for catamenial epilepsy, which has not been successfully treated with conventional antiepileptic drugs. Elucidation of the pathophysiology of catamenial epilepsy is a prerequisite to develop specific targeted approaches for treatment or prevention of the disorder. Cyclical changes in the circulating levels of estrogens and progesterone play a central role in the development of catamenial epilepsy. There is emerging evidence that endogenous neurosteroids with anticonvulsant or proconvulsant effects could play a critical role in catamenial epilepsy. It is thought that perimenstrual catamenial epilepsy is associated with the withdrawal of anticonvulsant neurosteroids. Progesterone and other hormonal agents have been shown in limited trials to be moderately effective in catamenial epilepsy, but may cause endocrine side effects. Synthetic neurosteroids, which enhance the tonic GABA-A receptor function, might provide an effective approach for the catamenial epilepsy therapy without producing hormonal side effects.

Neurosteroid replacement therapy for catamenial epilepsy

Perimenstrual catamenial epilepsy, the cyclical occurrence of seizure exacerbations near the time of menstruation, affects a high proportion of women of reproductive age with drug-refractory epilepsy. Enhanced seizure susceptibility in perimenstrual catamenial epilepsy is believed to be due to the withdrawal of the progesterone-derived GABA(A) receptor modulating neurosteroid allopregnanolone as a result of the fall in progesterone at the time of menstruation. Studies in a rat pseudopregnancy model of catamenial epilepsy indicate that after neurosteroid withdrawal there is enhanced susceptibility to chemoconvulsant seizures. There is also a transitory increase in the frequency of spontaneous seizures in epileptic rats that had experienced pilocarpine-induced status epilepticus. In the catamenial epilepsy model, there is a marked reduction in the antiseizure potency of anticonvulsant drugs, including benzodiazepines and valproate, but an increase in the anticonvulsant potency and protective index of neurosteroids such as allopregnanolone and the neurosteroid analog ganaxolone. The enhanced seizure susceptibility and benzodiazepine-resistance subsequent to neurosteroid withdrawal may be related to reduced expression and altered kinetics of synaptic GABA(A) receptors and increased expression of GABA(A) receptor subunits (such as alpha4) that confer benzodiazepine insensitivity. The enhanced potency of neurosteroids may be due to a relative increase after neurosteroid withdrawal in the expression of neurosteroid-sensitive delta-subunit-containing perisynaptic or extrasynaptic GABA(A) receptors. Positive allosteric modulatory neurosteroids and synthetic analogs such as ganaxolone may be administered to prevent catamenial seizure exacerbations, in what we call neurosteroid replacement therapy.

Hormonal therapies: progesterone

Seizures do not occur randomly in the majority of people with epilepsy. They tend to cluster. Seizure clusters, in turn, commonly occur with a temporal rhythmicity that shows a readily identifiable and predictable periodicity. When the periodicity of seizure exacerbation in women conforms to that of the menstrual cycle, it is commonly known as catamenial epilepsy. This may be attributable to 1) the neuroactive properties of steroid hormones and 2) the cyclic variation in their serum levels. If hormones play a role in seizure occurrence, hormones may also have a role in treatment. Progesterone has potent GABAergic metabolites that may provide safe and effective seizure control in women who have catamenial epilepsy.