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This narrative review provides an overview of the current knowledge on health-related quality of life (HRQOL), a relevant clinical outcome in patients with epilepsy. It shows that the most important factor determining HRQOL in this patient group is seizure frequency. In particular, seizure-freedom is associated with better HRQOL scores. Many other factors may impact perceived HRQOL aspects, but their interrelation is complex and requires further research. Novel analytical approaches, such as hierarchical cluster and symptom network analyses might shed further light on this, and may result in recommendations for interventions on the most 'central' factors influencing different aspects of HRQOL in patients with epilepsy. Next, an overview of the HRQOL tools and analytical methods currently used in epilepsy care, with a focus on clinical trials, is provided. The QOLIE-31 is the most frequently applied and best validated tool. Several other questionnaires focusing on specific aspects of HRQOL (e.g., mood, social impact) are less frequently used. We show some pitfalls that should be taken into account when designing study protocols including HRQOL endpoints. This includes standardized statistical analysis approaches and predefined reporting methods for HRQOL in epilepsy populations. It has been shown in other patient groups that the lack of such standardisation negatively impacts the quality and comparability of results. We conclude with a number of recommendations for future research., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Transcranial magnetic stimulation (TMS) with electroencephalography (EEG), that is TMS-EEG, may assist in managing epilepsy. We systematically reviewed the quality of reporting and findings in TMS-EEG studies on people with epilepsy and healthy controls, and on healthy individuals taking anti-seizure medication. We searched the Cochrane Library, Embase, PubMed and Web of Science databases for original TMS-EEG studies comparing people with epilepsy and healthy controls, and healthy subjects before and after taking anti-seizure medication. Studies should involve quantitative analyses of TMS-evoked EEG responses. We evaluated the reporting of study population characteristics and TMS-EEG protocols (TMS sessions and equipment, TMS trials and EEG protocol), assessed the variation between protocols, and recorded the main TMS-EEG findings. We identified 20 articles reporting 14 unique study populations and TMS methodologies. The median reporting rate for the group of people with epilepsy parameters was 3.5/7 studies and for the TMS parameters was 13/14 studies. TMS protocols varied between studies. Fifteen out of 28 anti-seizure medication trials in total were evaluated with time-domain analyses of single-pulse TMS-EEG data. Anti-seizure medication significantly increased N45, and decreased N100 and P180 component amplitudes but in marginal numbers (N45: 8/15, N100: 7/15, P180: 6/15). Eight articles compared people with epilepsy and controls using different analyses, thus limiting comparability. The reporting quality and methodological uniformity between studies evaluating TMS-EEG as an epilepsy biomarker is poor. The inconsistent findings question the validity of TMS-EEG as an epilepsy biomarker. To demonstrate TMS-EEG clinical applicability, methodology and reporting standards are required., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

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., (© 2022 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Purpose: Pathogenic variants in GABRB3 have been associated with a spectrum of phenotypes from severe developmental disorders and epileptic encephalopathies to milder epilepsy syndromes and mild intellectual disability (ID). In this study, we analyzed a large cohort of individuals with GABRB3 variants to deepen the phenotypic understanding and investigate genotype-phenotype correlations., Methods: Through an international collaboration, we analyzed electro-clinical data of unpublished individuals with variants in GABRB3, and we reviewed previously published cases. All missense variants were mapped onto the 3-dimensional structure of the GABRB3 subunit, and clinical phenotypes associated with the different key structural domains were investigated., Results: We characterized 71 individuals with GABRB3 variants, including 22 novel subjects, expressing a wide spectrum of phenotypes. Interestingly, phenotypes correlated with structural locations of the variants. Generalized epilepsy, with a median age at onset of 12 months, and mild-to-moderate ID were associated with variants in the extracellular domain. Focal epilepsy with earlier onset (median: age 4 months) and severe ID were associated with variants in both the pore-lining helical transmembrane domain and the extracellular domain., Conclusion: These genotype-phenotype correlations will aid the genetic counseling and treatment of individuals affected by GABRB3-related disorders. Future studies may reveal whether functional differences underlie the phenotypic differences., Competing Interests: Conflicts of Interest The authors of declare no conflicts of interest., (Copyright © 2021 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: Complete visual review of prolonged video-EEG recordings at an EMU (Epilepsy Monitoring Unit) is time consuming and can cause problems in times of paucity of educated personnel. In this study we aimed to show non inferiority for electroclinical diagnosis using sampled review in combination with EEG analysis softreferware (P13 software, Persyst Corporation), in comparison to complete visual review., Method: Fifty prolonged video-EEG recordings in adults were prospectively evaluated using sampled visual EEG review in combination with automated detection software of the complete EEG record. Visually assessed samples consisted of one hour during wakefulness, one hour during sleep, half an hour of wakefulness after wake-up and all clinical events marked by the individual and/or nurses. The final electro-clinical diagnosis of this new review approach was compared with the electro-clinical diagnosis after complete visual review as presently used., Results: The electro-clinical diagnosis based on sampled visual review combined with automated detection software did not differ from the diagnosis based on complete visual review. Furthermore, the detection software was able to detect all records containing epileptiform abnormalities and epileptic seizures., Conclusion: Sampled visual review in combination with automated detection using Persyst 13 is non-inferior to complete visual review for electroclinical diagnosis of prolonged video-EEG at an EMU setting, which makes this approach promising., Competing Interests: Declaration of competing interest None of the authors has any conflict of interest to disclose., (Copyright © 2020 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

Objective: No international guideline is available for minimum safety measures at epilepsy monitoring units (EMUs), although recommendations for preferred practices exist. These are mostly based on expert opinion, without evidence of effectiveness. We do not apply all of these preferred practices at our EMU setting. We audited adverse events and diagnostic utility at our EMU over one year., Methods: From May 2018 to May 2019, we prospectively collected data concerning adverse events and diagnostic utility of all EMU admissions (noninvasive video-electroencephalogram (EEG) recordings); during these admissions, individuals can be ambulant within their EMU room., Results: There were 1062 admissions comprising 1518 EMU days. In 2% of the admissions, a complication occurred, mostly a fall without injury (n = 6). In almost half of the falls, this was from the bed. Complications occurred most often during admissions for presurgical evaluation. Antiseizure medication (ASM) was tapered in 86% of presurgical cases, but no serious injury occurred, and occurring seizures were effectively treated with intranasal midazolam if needed., Conclusions: The overall adverse event rate was low. Falls are the most common adverse event comparable with previously published fall rates at other EMUs where people are restricted to their bed. We showed that restricted ambulation at a well-monitored EMU is not necessary and possibly unwanted. No serious injury due to tapering of ASM occurred, and intranasal midazolam was shown to be effective as acute seizure treatment., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: User safety and the quality of diagnostics on the epilepsy monitoring unit (EMU) depend on reaction to seizures. Online seizure detection might improve this. While good sensitivity and specificity is reported, the added value above staff response is unclear. We ascertained the added value of two electroencephalograph (EEG) seizure detection algorithms in terms of additional detected seizures or faster detection time., Methods: EEG-video seizure recordings of people admitted to an EMU over one year were included, with a maximum of two seizures per subject. All recordings were retrospectively analyzed using Encevis EpiScan and BESA Epilepsy. Detection sensitivity and latency of the algorithms were compared to staff responses. False positive rates were estimated on 30 uninterrupted recordings (roughly 24 h per subject) of consecutive subjects admitted to the EMU., Results: EEG-video recordings used included 188 seizures. The response rate of staff was 67%, of Encevis 67%, and of BESA Epilepsy 65%. Of the 62 seizures missed by staff, 66% were recognized by Encevis and 39% by BESA Epilepsy. The median latency was 31 s (staff), 10 s (Encevis), and 14 s (BESA Epilepsy). After correcting for walking time from the observation room to the subject, both algorithms detected faster than staff in 65% of detected seizures. The full recordings included 617 h of EEG. Encevis had a median false positive rate of 4.9 per 24 h and BESA Epilepsy of 2.1 per 24 h., Conclusions: EEG-video seizure detection algorithms may improve reaction to seizures by improving the total number of seizures detected and the speed of detection. The false positive rate is feasible for use in a clinical situation. Implementation of these algorithms might result in faster diagnostic testing and better observation during seizures., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Purpose: Caffeine is the most commonly used central nervous system (CNS) stimulant. The relationship between caffeine, seizures, epilepsy, and antiepileptic drugs (AEDs) is complex and not fully understood. Case reports suggest that caffeine triggers seizures in susceptible people. Our systematic review reports on the relationship between caffeine, seizures, and drugs in animal and human studies. Quantitative analyses were also done on animal studies regarding the effects of caffeine on AEDs., Methods: PubMed was searched for studies assessing the effects of caffeine on seizure susceptibility, epilepsy, and drug interactions in people and in animal models. To quantify the interaction between AEDs and caffeine, the data of six animal studies were pooled and analyzed using a general linear model univariate analysis or One-way Analysis of Variance (ANOVA)., Results: In total, 442 items were identified from which we included 105 studies. Caffeine can increase seizure susceptibility and protect from seizures, depending on the dose, administration type (chronic or acute), and the developmental stage at which caffeine exposure started. In animal studies, caffeine decreased the antiepileptic potency of some drugs; this effect was strongest in topiramate., Conclusion: Preclinical studies suggest that caffeine increases seizure susceptibility. In some cases, chronic use of caffeine may protect against seizures. Caffeine lowers the efficacy of several drugs, especially topiramate. It is unclear how these findings in models can be translated to the clinical condition. Until clinical studies suggest otherwise, caffeine intake should be considered as a factor in achieving and maintaining seizure control in epilepsy., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Cortical excitability, as measured by transcranial magnetic stimulation combined with electromyography, is a potential biomarker for the diagnosis and follow-up of epilepsy. We report on long-interval intracortical inhibition data measured in four different centres in healthy controls (n = 95), subjects with refractory genetic generalized epilepsy (n = 40) and with refractory focal epilepsy (n = 69). Long-interval intracortical inhibition was measured by applying two supra-threshold stimuli with an interstimulus interval of 50, 100, 150, 200 and 250 ms and calculating the ratio between the response to the second (test stimulus) and to the first (conditioning stimulus). In all subjects, the median response ratio showed inhibition at all interstimulus intervals. Using a mixed linear-effects model, we compared the long-interval intracortical inhibition response ratios between the different subject types. We conducted two analyses; one including data from the four centres and one excluding data from Centre 2, as the methods in this centre differed from the others. In the first analysis, we found no differences in long-interval intracortical inhibition between the different subject types. In all subjects, the response ratios at interstimulus intervals 100 and 150 ms showed significantly more inhibition than the response ratios at 50, 200 and 250 ms. Our second analysis showed a significant interaction between interstimulus interval and subject type (P = 0.0003). Post hoc testing showed significant differences between controls and refractory focal epilepsy at interstimulus intervals of 100 ms (P = 0.02) and 200 ms (P = 0.04). There were no significant differences between controls and refractory generalized epilepsy groups or between the refractory generalized and focal epilepsy groups. Our results do not support the body of previous work that suggests that long-interval intracortical inhibition is significantly reduced in refractory focal and genetic generalized epilepsy. Results from the second analysis are even in sharper contrast with previous work, showing inhibition in refractory focal epilepsy at 200 ms instead of facilitation previously reported. Methodological differences, especially shorter intervals between the pulse pairs, may have contributed to our inability to reproduce previous findings. Based on our results, we suggest that long-interval intracortical inhibition as measured by transcranial magnetic stimulation and electromyography is unlikely to have clinical use as a biomarker of epilepsy., (© The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objective: We aimed to test the potential of auto-regressive model residual modulation (ARRm), an artefact-insensitive method based on non-harmonicity of the high-frequency signal, to identify epileptogenic tissue during surgery., Methods: Intra-operative electrocorticography (ECoG) of 54 patients with refractory focal epilepsy were recorded pre- and post-resection at 2048Hz. The ARRm was calculated in one-minute epochs in which high-frequency oscillations (HFOs; fast ripples, 250-500Hz; ripples, 80-250Hz) and spikes were marked. We investigated the pre-resection fraction of HFOs and spikes explained by the ARRm (h 2 -index). A general ARRm threshold was set and used to compare the ARRm to surgical outcome in post-resection ECoG (Pearson X 2 )., Results: ARRm was associated strongest with the number of fast ripples in pre-resection ECoG (h 2 =0.80, P<0.01), but also with ripples and spikes. An ARRm threshold of 0.47 yielded high specificity (95%) with 52% sensitivity for channels with fast ripples. ARRm values >0.47 were associated with poor outcome at channel and patient level (both P<0.01) in post-resection ECoG., Conclusions: The ARRm algorithm might enable intra-operative delineation of epileptogenic tissue., Significance: ARRm is the first unsupervised real-time analysis that could provide an intra-operative, 'on demand' interpretation per electrode about the need to remove underlying tissue to optimize the chance of seizure freedom., (Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: Following a sudden death at a residential care unit, the Dutch Health and Care Inspectorate advised intensification of the use of video monitoring (VM) at the unit. We assessed whether VM resulted in increased identification of seizures that required clinical intervention., Methods: The unit provides care for 340 individuals with refractory epilepsy and severe learning disabilities. Acoustic detection systems (ADSs) cover all individuals; 37 people also have a bed motion sensor (BMS) and 46 people with possible nocturnal seizures are now monitored by VM. During a 6-month period, in all cases of a suspected seizure we asked the caregivers to specify which device alerted them and to indicate whether this led to an intervention. Staff costs of VM were estimated using payroll information., Results: We identified 1,208 seizures in 37 individuals: 4 had no nocturnal seizures and 393 (33%) seizures were seen only on video. In 169 (14%) of 1,208 seizures an intervention was made and this included 39 (10%) of 393 seizures seen only on video. When compared to seizures observed with an ADS or BMS, seizures seen only on video were more often tonic seizures (71% vs. 22%, p < 0.001) and occurred mostly in the beginning or at the end of the night (40% vs. 26%, p < 0.001). The extra staff costs of monitoring was 7,035 euro per seizure seen only on video and leading to an intervention., Significance: VM facilitates nocturnal surveillance, but the costs are high. This underscores the need for development of reliable seizure detection devices., (Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.)

High frequency oscillations (HFO) appear to be a promising marker for delineating the seizure onset zone (SOZ) in patients with localization related epilepsy. It remains, however, a purely observational phenomenon and no common mechanism has been proposed to relate HFOs and seizure generation. In this work we show that a cascade of two computational models, one on detailed compartmental scale and a second one on neural mass scale can explain both the autonomous generation of HFOs and the presence of epileptic seizures as emergent properties. To this end we introduce axonal-axonal gap junctions on a microscopic level and explore their impact on the higher level neural mass model (NMM). We show that the addition of gap junctions can generate HFOs and simultaneously shift the operational point of the NMM from a steady state network into bistable behavior that can autonomously generate epileptic seizures. The epileptic properties of the system, or the probability to generate epileptic type of activity, increases gradually with the increase of the density of axonal-axonal gap junctions. We further demonstrate that ad hoc HFO detectors used in previous studies are applicable to our simulated data.

Transcranial magnetic stimulation (TMS) can be used for safe, noninvasive probing of cortical excitability (CE). We review 50 studies that measured CE in people with epilepsy. Most showed cortical hyperexcitability, which can be corrected with anti-epileptic drug treatment. Several studies showed that decrease of CE after epilepsy surgery is predictive of good seizure outcome. CE is a potential biomarker for epilepsy. Clinical application may include outcome prediction of drug treatment and epilepsy surgery.

Ictal nystagmus (IN) is an uncommon phenomenon characterized by rhythmic saccadic eye movements occurring during epileptic seizures. We report a newborn baby with severe birth asphyxia, undergoing long-term video EEG monitoring with electro-oculogram (EOG), who showed irregular IN when eye movements crossed the midline from left to right and vice versa, resulting in large amplitude of the nystagmoid movements. The nystagmus was followed 15 to 29 seconds later by ictal discharges in the occipital regions. MRI of the brain showed features suggestive of periventricular leukomalacia. This interesting combination of findings suggests a complex mechanism for IN of cortical or subcortical ictal rhythms, which results in (a) the generation of subcortical electrical discharges in the pons and midbrain, causing nystagmoid eye movements, and (b) subsequent occipital spiking. We conclude that this clinical manifestation supports the existence of functioning cortical-subcortical connections between the brainstem ocular motor centers and the occipital cortex at birth.

Cortical excitability, as measured by transcranial magnetic stimulation combined with electromyography, is a potential biomarker for the diagnosis and follow-up of epilepsy. We report on long-interval intracortical inhibition data measured in four different centres in healthy controls (n = 95), subjects with refractory genetic generalized epilepsy (n = 40) and with refractory focal epilepsy (n = 69). Long-interval intracortical inhibition was measured by applying two supra-threshold stimuli with an interstimulus interval of 50, 100, 150, 200 and 250 ms and calculating the ratio between the response to the second (test stimulus) and to the first (conditioning stimulus). In all subjects, the median response ratio showed inhibition at all interstimulus intervals. Using a mixed linear-effects model, we compared the long-interval intracortical inhibition response ratios between the different subject types. We conducted two analyses; one including data from the four centres and one excluding data from Centre 2, as the methods in this centre differed from the others. In the first analysis, we found no differences in long-interval intracortical inhibition between the different subject types. In all subjects, the response ratios at interstimulus intervals 100 and 150 ms showed significantly more inhibition than the response ratios at 50, 200 and 250 ms. Our second analysis showed a significant interaction between interstimulus interval and subject type (P = 0.0003). Post hoc testing showed significant differences between controls and refractory focal epilepsy at interstimulus intervals of 100 ms (P = 0.02) and 200 ms (P = 0.04). There were no significant differences between controls and refractory generalized epilepsy groups or between the refractory generalized and focal epilepsy groups. Our results do not support the body of previous work that suggests that long-interval intracortical inhibition is significantly reduced in refractory focal and genetic generalized epilepsy. Results from the second analysis are even in sharper contrast with previous work, showing inhibition in refractory focal epilepsy at 200 ms instead of facilitation previously reported. Methodological differences, especially shorter intervals between the pulse pairs, may have contributed to our inability to reproduce previous findings. Based on our results, we suggest that long-interval intracortical inhibition as measured by transcranial magnetic stimulation and electromyography is unlikely to have clinical use as a biomarker of epilepsy. [ABSTRACT FROM AUTHOR]

It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15-61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal generalized EEG suppression. [ABSTRACT FROM AUTHOR]

People with epilepsy often report seizures precipitated by stress. This is believed to be due to effects of stress hormones, such as cortisol, on neuronal excitability. Cortisol, regardless of stress, is released in hourly pulses, whose effect on epileptic activity is unknown. We tested the relation between cortisol levels and the incidence of epileptiform abnormalities in the electroencephalogram of people with focal epilepsy. Morning cortisol levels were measured in saliva samples obtained every 15 min. Interictal epileptiform discharges were determined in the same time periods. We investigated the relationship between cortisol levels and the epileptiform discharges distinguishing persons with from those without stress-precipitated seizures (linear mixed model), and analysed the contribution of individual, epilepsy and recording characteristics with multivariable analysis. Twenty-nine recordings were performed in 21 individuals. Cortisol was positively related to incidence of epileptiform discharges (β = 0.26, P = 0.002) in people reporting stress-sensitive seizures, but not those who did not report stress sensitivity (β = -0.07, P = 0.64). The relationship between cortisol and epileptiform discharges was positively associated only with stress sensitivity of seizures (β = 0.31, P = 0.005). The relationship between cortisol levels and incidence of interictal epileptiform discharges in people with stress-sensitive seizures suggests that stress hormones influence disease activity in epilepsy, also under basal conditions. [ABSTRACT FROM AUTHOR]

• An automated non-contact algorithm for detection of central apneas is proposed. • It detects cessation of oscillatory movements of breathing in absence of body motion. • All apnea episodes were detected in the signals from at least one camera angle. • Integrating camera inputs capturing different angles improved detection sensitivity. • >99% specificity was achieved with individual cameras and integrated camera inputs. Central apneas occurring in the aftermath of epileptic seizures may lead to sudden death. Contact-sensors currently used to detect apneas are not always suitable or tolerated. We developed a robust automated non-contact algorithm for real-time detection of central apneas using video cameras. One video recording with simulated apneas and nine with real-life apneas associated with epileptic seizures, each recorded from 3 to 4 angles, were used to develop the algorithm. Videos were preprocessed using optical flow, from which translation, dilatation and shear rates were extracted. Presence of breathing motions was quantified in the time-frequency spectrum by calculating the relative power in the respiratory range (0.1–1 Hz). Sigmoid modulation was calculated over different scales to quantify sigmoid-like drops in respiratory range power. Each sigmoid modulation maximum constitutes a possible apnea event. Two event features were calculated to enable distinction between apnea events and movements: modulation maximum amplitude and total spectral power modulation at the time of the event. An ensemble support vector machine was trained to classify events using a bagging procedure and validated in a leave-one-subject-out cross validation procedure. All apnea episodes were detected in the signals from at least one camera angle. Integrating camera inputs capturing different angles increased overall detection sensitivity (>90%). Overall detection specificity of >99% was achieved with both individual cameras and integrated camera inputs. These results suggest that it is feasible to detect central apneas automatically in video, using this algorithm. When validated, the algorithm might be used as an online remote apnea detector for safety monitoring. [ABSTRACT FROM AUTHOR]

Absence epilepsy (AE) is related to both cognitive and physical impairments. In this narrative review, we critically discuss the pathophysiology of AE and the impairment of attention in children and adolescents with AE. In particular, we contextualize the attentive dysfunctions of AE with the associated risks, such as accidental injuries. An extensive literature search on attention deficits and the rate of accidental injuries in AE was run. The search was conducted on Scopus, Pubmed, and the online libraries of the University of Twente and Maastricht University. Relevant references of the included articles were added. Retrospective and prospective studies, case reports, meta-analysis, and narrative reviews were included. Only studies written in English were considered. Date of last search is February 2020. The keywords used were "absence epilepsy" AND "attention"/"awareness", "absence epilepsy" AND "accidental injuries"/"accident*"/"injuries". Ten retrospective and two prospective studies on cognition and AE were fully screened. Seventeen papers explicitly referring to attention in AE were reviewed. Just one paper was found to specifically focus on accidental injuries and AE, while twelve studies generally referring to epilepsy syndromes – among which AE – and related accidents were included. Absence epilepsy and attention deficits show some patterns of pathophysiological association. This relation may account for dysfunctions in everyday activities in the pediatric population. Particular metrics, such as the risk related to biking in children with AE, should be used in future studies to address the problem in a novel way and to impact clinical indications. • Absence epilepsy and attention deficits show patterns of pathophysiological association • Attentive dysfunctions in absence epilepsy account for dysfunctions in every-day activities • Patients with absence epilepsy may be more likely to incur in casualties • Quantitative measures of the risk of accidents in patients with asbences are relevant to formulate clinical indications [ABSTRACT FROM AUTHOR]

Epilepsy and migraine are paroxysmal neurological conditions associated with disturbances of cortical excitability. No useful biomarkers to monitor disease activity in these conditions are available. Phase clustering was previously described in electroencephalographic (EEG) responses to photic stimulation and may be a potential epilepsy biomarker. The objective of this study was to investigate EEG phase clustering in response to transcranial magnetic stimulation (TMS), compare it with photic stimulation in controls, and explore its potential as a biomarker of genetic generalized epilepsy or migraine with aura. People with (possible) juvenile myoclonic epilepsy (JME), migraine with aura, and healthy controls underwent single-pulse TMS with concomitant EEG recording during the interictal period. We compared phase clustering after TMS with photic stimulation across the groups using permutation-based testing. We included eight people with (possible) JME (five off medication, three on), 10 with migraine with aura, and 37 controls. The TMS and photic phase clustering spectra showed significant differences between those with epilepsy without medication and controls. Two phase clustering-based indices successfully captured these differences between groups. One participant was tested multiple times. In this case, the phase clustering-based indices were inversely correlated with the dose of antiepileptic medication. Phase clustering did not differ between people with migraine and controls. We present methods to quantify phase clustering using TMS–EEG and show its potential value as a measure of brain network activity in genetic generalized epilepsy. Our results suggest that the higher propensity to phase clustering is not shared between genetic generalized epilepsy and migraine. • Epilepsy and migraine are associated with disturbances of cortical excitability. • No useful biomarkers to monitor disease activity in these conditions exist. • We measured phase clustering in the EEG after transcranial magnetic stimulation. • Phase clustering was higher in people with epilepsy off drugs than in controls. • Phase clustering may be a biomarker of increased cortical excitability in epilepsy. [ABSTRACT FROM AUTHOR]