Artificial intelligence-enhanced epileptic seizure detection by wearables.

OBJECTIVE: Wrist- or ankle-worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom-developed deep-learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals. METHODS: Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable sensors on either wrists or ankles. We collected patients' electrodermal activity, accelerometry (ACC), and photoplethysmography, from which blood volume pulse (BVP) is derived. Board-certified epileptologists determined seizure onset, offset, and types using video and EEG recordings per the International League Against Epilepsy 2017 classification. We applied three neural network models-a convolutional neural network (CNN) and a CNN-long short-term memory (LSTM)-based generalized detection model and an autoencoder-based personalized detection model-to the raw time-series sensor data to detect seizures and utilized performance measures, including sensitivity, false positive rate (the number of false alarms divided by the total number of nonseizure segments), number of false alarms per day, and detection delay. We applied a 10-fold patientwise cross-validation scheme to the multisignal biosensor data and evaluated model performance on 28 seizure types. RESULTS: We analyzed 166 patients (47.6% female, median age = 10.0 years) and 900 seizures (13 254 h of sensor data) for 28 seizure types. With a CNN-LSTM-based seizure detection model, ACC, BVP, and their fusion performed better than chance; ACC and BVP data fusion reached the best detection performance of 83.9% sensitivity and 35.3% false positive rate. Nineteen of 28 seizure types could be detected by at least one data modality with area under receiver operating characteristic curve > .8 performance. SIGNIFICANCE: Results from this in-hospital study contribute to a paradigm shift in epilepsy care that entails noninvasive seizure detection, provides time-sensitive and accurate data on additional clinical seizure types, and proposes a novel combination of an out-of-the-box monitoring algorithm with an individualized person-oriented seizure detection approach.

Wearable device assessments of antiseizure medication effects on diurnal patterns of electrodermal activity, heart rate, and heart rate variability.

Patient-generated health data provide a great opportunity for more detailed ambulatory monitoring and more personalized treatments in many diseases. In epilepsy, robust diagnostics applicable to the ambulatory setting are needed as diagnosis and treatment decisions in current clinical practice are primarily reliant on patient self-reports, which are often inaccurate. Recent work using wearable devices has focused on methods to detect and forecast epileptic seizures. Whether wearable device signals may also contain information about the effect of antiseizure medications (ASMs), which may ultimately help to better monitor their efficacy, has not been evaluated yet. Here we systematically investigated the effect of ASMs on different data modalities (electrodermal activity, EDA, heart rate, HR, and heart rate variability, HRV) simultaneously recorded by a wearable device in 48 patients with epilepsy over several days in the epilepsy long-term monitoring unit at a tertiary hospital. All signals exhibited characteristic diurnal variations. HRV, but not HR or EDA-based metrics, were reduced by ASMs. By assessing multiple signals related to the autonomic nervous system simultaneously, our results provide novel insights into the effects of ASMs on the sympathetic and parasympathetic interplay in the setting of epilepsy and indicate the potential of easy-to-wear wearable devices for monitoring ASM action. Future work using longer data may investigate these metrics on multidien cycles and their utility for detecting seizures, assessing seizure risk, or informing treatment interventions.

Twenty-four-hour patterns in electrodermal activity recordings of patients with and without epileptic seizures.

OBJECTIVE: Daytime and nighttime patterns affect the dynamic modulation of brain and body functions and influence the autonomic nervous system response to seizures. Therefore, we aimed to evaluate 24-hour patterns of electrodermal activity (EDA) in patients with and without seizures. METHODS: We included pediatric patients with (a) seizures (SZ), including focal impaired awareness seizures (FIAS) or generalized tonic-clonic seizures (GTCS), (b) no seizures and normal electroencephalography (NEEG), or (c) no seizures but epileptiform activity in the EEG (EA) during vEEG monitoring. Patients wore a device that continuously recorded EDA and temperature (TEMP). EDA levels, EDA spectral power, and TEMP levels were analyzed. To investigate 24-hour patterns, we performed a nonlinear mixed-effects model analysis. Relative mean pre-ictal (-30 min to seizure onset) and post-ictal (I: 30 min after seizure offset; II: 30 to 60 min after seizure offset) values were compared for SZ subgroups. RESULTS: We included 119 patients (40 SZ, 17 NEEG, 62 EA). EDA level and power group-specific models (SZ, NEEG, EA) (h = 1; P < .01) were superior to the all-patient cohort model. Fifty-nine seizures were analyzed. Pre-ictal EDA values were lower than respective 24-hour modulated SZ group values. Post hoc comparisons following the period-by-seizure type interaction (EDA level: χ2  = 18.50; P < .001, and power: χ2  = 6.73; P = .035) revealed that EDA levels were higher in the post-ictal period I for FIAS and GTCS and in post-ictal period II for GTCS only compared to the pre-ictal period. SIGNIFICANCE: Continuously monitored EDA shows a pattern of change over 24 hours. Curve amplitudes in patients with recorded seizures were lower as compared to patients who did not exhibit seizures during the recording period. Sympathetic skin responses were greater and more prolonged in GTCS compared to FIAS. EDA recordings from wearable devices offer a noninvasive tool to continuously monitor sympathetic activity with potential applications for seizure detection, prediction, and potentially sudden unexpected death in epilepsy (SUDEP) risk estimation.

Seizure detection using wearable sensors and machine learning: Setting a benchmark.

OBJECTIVE: Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may miss seizures. Wearable devices may be better tolerated and more suitable for long-term ambulatory monitoring. This study evaluates the seizure detection performance of custom-developed machine learning (ML) algorithms across a broad spectrum of epileptic seizures utilizing wrist- and ankle-worn multisignal biosensors. METHODS: We enrolled patients admitted to the epilepsy monitoring unit and asked them to wear a wearable sensor on either their wrists or ankles. The sensor recorded body temperature, electrodermal activity, accelerometry (ACC), and photoplethysmography, which provides blood volume pulse (BVP). We used electroencephalographic seizure onset and offset as determined by a board-certified epileptologist as a standard comparison. We trained and validated ML for two different algorithms: Algorithm 1, ML methods for developing seizure type-specific detection models for nine individual seizure types; and Algorithm 2, ML methods for building general seizure type-agnostic detection, lumping together all seizure types. RESULTS: We included 94 patients (57.4% female, median age = 9.9 years) and 548 epileptic seizures (11 066 h of sensor data) for a total of 930 seizures and nine seizure types. Algorithm 1 detected eight of nine seizure types better than chance (area under the receiver operating characteristic curve [AUC-ROC] = .648-.976). Algorithm 2 detected all nine seizure types better than chance (AUC-ROC = .642-.995); a fusion of ACC and BVP modalities achieved the best AUC-ROC (.752) when combining all seizure types together. SIGNIFICANCE: Automatic seizure detection using ML from multimodal wearable sensor data is feasible across a broad spectrum of epileptic seizures. Preliminary results show better than chance seizure detection. The next steps include validation of our results in larger datasets, evaluation of the detection utility tool for additional clinical seizure types, and integration of additional clinical information.

Benzodiazepine administration patterns before escalation to second-line medications in pediatric refractory convulsive status epilepticus.

OBJECTIVE: This study was undertaken to evaluate benzodiazepine (BZD) administration patterns before transitioning to non-BZD antiseizure medication (ASM) in pediatric patients with refractory convulsive status epilepticus (rSE). METHODS: This retrospective multicenter study in the United States and Canada used prospectively collected observational data from children admitted with rSE between 2011 and 2020. Outcome variables were the number of BZDs given before the first non-BZD ASM, and the number of BZDs administered after 30 and 45 min from seizure onset and before escalating to non-BZD ASM. RESULTS: We included 293 patients with a median (interquartile range) age of 3.8 (1.3-9.3) years. Thirty-six percent received more than two BZDs before escalating, and the later the treatment initiation was after seizure onset, the less likely patients were to receive multiple BZD doses before transitioning (incidence rate ratio [IRR] = .998, 95% confidence interval [CI] = .997-.999 per minute, p = .01). Patients received BZDs beyond 30 and 45 min in 57.3% and 44.0% of cases, respectively. Patients with out-of-hospital seizure onset were more likely to receive more doses of BZDs beyond 30 min (IRR = 2.43, 95% CI = 1.73-3.46, p < .0001) and beyond 45 min (IRR = 3.75, 95% CI = 2.40-6.03, p < .0001) compared to patients with in-hospital seizure onset. Intermittent SE was a risk factor for more BZDs administered beyond 45 min compared to continuous SE (IRR = 1.44, 95% CI = 1.01-2.06, p = .04). Forty-seven percent of patients (n = 94) with out-of-hospital onset did not receive treatment before hospital arrival. Among patients with out-of-hospital onset who received at least two BZDs before hospital arrival (n = 54), 48.1% received additional BZDs at hospital arrival. SIGNIFICANCE: Failure to escalate from BZDs to non-BZD ASMs occurs mainly in out-of-hospital rSE onset. Delays in the implementation of medical guidelines may be reduced by initiating treatment before hospital arrival and facilitating a transition to non-BZD ASMs after two BZD doses during handoffs between prehospital and in-hospital settings.

Association between semiologic, autonomic, and electrographic seizure characteristics in children with generalized tonic-clonic seizures.

INTRODUCTION: Generalized tonic-clonic seizures (GTCS) are associated with elevated electrodermal activity (EDA) and postictal generalized electroencephalographic suppression (PGES), markers that may indicate sudden unexpected death in epilepsy (SUDEP) risk. This study investigated the association of GTCS semiology, EDA, and PGES in children with epilepsy. METHODS: Patients admitted to the Boston Children's Hospital long-term video-EEG monitoring unit wore a sensor that records EDA. We selected patients with at least one GTCS and reviewed video-EEGs for semiology, tonic and clonic phase duration, total clinical seizure duration, electrographic onset, offset, and PGES. We grouped patients into three semiology classes: GTCS 1: bilateral symmetric tonic arm extension, GTCS 2: no specific tonic arm extension or flexion, GTCS 3: unilateral or asymmetrical arm extension, tonic arm flexion or posturing that does not fit into GTCS 1 or 2. We analyzed the correlation between semiology, EDA, and PGES, and measured the area under the curve (AUC) of the ictal EDA (seizure onset to one hour after), subtracting baseline EDA (one-hour seizure-free before seizure onset). Using generalized estimating equation (GEE) and linear regression, we analyzed all seizures and single episodes per patient. RESULTS: We included 30 patients (median age 13.8 ±â€¯3.6 years, 46.7% females) and 53 seizures. With GEE, GTCS 1 was associated with longer PGES duration compared to GTCS 2 (Estimate (ß) = -26.32 s, 95% Confidence Interval (CI): -36.46 to -16.18, p < 0.001), and the presence of PGES was associated with greater EDA change (ß = 429604 µS, 95% CI: 3550.96 to 855657.04, p = 0.048). With single-episode analysis, GTCS 1 had greater EDA change than GTCS 2 ((ß = -601339 µS, 95% CI: -1167016.56 to -35661.44, p = 0.047). EDA increased with PGES presence (ß = 637500 µS, 95% CI: 183571.84 to 1091428.16, p = 0.01) and duration (ß = 16794 µS, 95% CI: 5729.8 to 27858.2, p = 0.006). Patients with GTCS 1 had longer PGES duration compared to GTCS 2 (ß = -30.53 s, 95% CI: -44.6 to -16.46, p < 0.001) and GTCS 3 (ß = -22.07 s, 95% CI: -38.95 to -5.19, p = 0.016). CONCLUSION: In children with epilepsy, PGES correlates with greater ictal EDA. GTCS 1 correlated with longer PGES duration and may indirectly correlate with greater ictal EDA. Our study suggests potential applications in monitoring and preventing SUDEP in these patients.

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessment is in principle possible, these early approaches relied largely on complex, often invasive setups including intracranial electrocorticography, implanted devices, and multichannel electroencephalography, and required patient-specific adaptation or learning to perform optimally, all of which limit translation to broad clinical application. To facilitate broader adaptation of seizure forecasting in clinical practice, noninvasive, easily applicable techniques that reliably assess seizure risk without much prior tuning are crucial. Wristbands that continuously record physiological parameters, including electrodermal activity, body temperature, blood volume pulse, and actigraphy, may afford monitoring of autonomous nervous system function and movement relevant for such a task, hence minimizing potential complications associated with invasive monitoring and avoiding stigma associated with bulky external monitoring devices on the head. METHODS: Here, we applied deep learning on multimodal wristband sensor data from 69 patients with epilepsy (total duration > 2311 hours, 452 seizures) to assess its capability to forecast seizures in a statistically significant way. RESULTS: Using a leave-one-subject-out cross-validation approach, we identified better-than-chance predictability in 43% of the patients. Time-matched seizure surrogate data analyses indicated forecasting not to be driven simply by time of day or vigilance state. Prediction performance peaked when all sensor modalities were used, and did not differ between generalized and focal seizure types, but generally increased with the size of the training dataset, indicating potential further improvement with larger datasets in the future. SIGNIFICANCE: Collectively, these results show that statistically significant seizure risk assessments are feasible from easy-to-use, noninvasive wearable devices without the need of patient-specific training or parameter optimization.

Photoplethysmographic evaluation of generalized tonic-clonic seizures.

OBJECTIVE: Photoplethysmography (PPG) is an optical technique measuring variations of blood perfusion in peripheral tissues. We evaluated alterations in PPG signals in relationship to the occurrence of generalized tonic-clonic seizures (GTCSs) in patients with epilepsy to evaluate the feasibility of seizure detection. METHODS: During electroencephalographic (EEG) long-term monitoring, patients wore portable wristband sensor(s) on their wrists or ankles recording PPG signals. We analyzed PPG signals during three time periods, which were defined with respect to seizures detected on EEG: (1) baseline (>30 minutes prior to seizure), (2) preseizure period, and (3) postseizure period. Furthermore, we selected five random control segments during seizure-free periods. PPG features, including frequency, amplitude, duration, slope, smoothness, and area under the curve, were automatically calculated. We used a linear mixed-effect model to evaluate changes in PPG features between different time periods in an attempt to identify signal changes that detect seizures. RESULTS: We prospectively enrolled 174 patients from the epilepsy monitoring unit at Boston Children's Hospital. Twenty-five GTCSs were recorded from 13 patients. Data from the first recorded GTCS of each patient were included in the analysis. We observed an increase in PPG frequency during pre- and postseizure periods that was higher than the changes during seizure-free periods (frequency increase: preseizure = 0.22 Hz, postseizure = 0.58 Hz vs changes during seizure-free period = 0.05 Hz). The PPG slope decreased significantly by 56.71 nW/s during preseizure periods compared to seizure-free periods. Additionally, the smoothness increased significantly by 0.22 nW/s during the postseizure period compared to seizure-free periods. SIGNIFICANCE: Monitoring of PPG signals may assist in the detection of GTCSs in patients with epilepsy. PPG may serve as a promising biomarker for future seizure detection systems and may contribute to future seizure prediction systems.

Photoplethysmography: A measure for the function of the autonomic nervous system in focal impaired awareness seizures.

OBJECTIVES: Photoplethysmography (PPG) reflects variations of blood perfusion in tissues, which may signify seizure-related autonomic changes. The aim of this study is to assess the variability of PPG signals and their value in detecting peri-ictal changes in patients with focal impaired awareness seizures (FIASs). METHODS: PPG data were recorded using a wearable sensor placed on the wrist or ankle of children with epilepsy admitted for long-term video-electroencephalographic monitoring. We analyzed PPG data in four different periods: seizure-free, preictal, ictal, and postictal. Multiple features were automatically extracted from the PPG signal-frequency, duration, amplitude, increasing and decreasing slopes, smoothness, and area under the curve (AUC)-and were used to identify preictal, ictal, or postictal changes by comparing them with seizure-free periods and with each other using a linear mixed-effects model. RESULTS: We studied PPG in 11 patients (18 FIASs), including seizure-free, preictal, and postictal periods, and a subset of eight patients (12 FIASs) including the ictal period. Compared to the seizure-free period, we found significant changes in PPG (1) during the ictal period across all features; (2) during the preictal period in amplitude, duration, increasing slope, and AUC; and (3) during the postictal period in decreasing slope. SIGNIFICANCE: Specific PPG changes can be seen before, during, and after FIASs. The peri-ictal changes in the PPG features of patients with FIASs suggest potential applications of PPG monitoring for seizure detection.

Response to clobazam in continuous spike-wave during sleep.

AIM: To evaluate the efficacy of clobazam treatment in reducing epileptiform discharges and modifying neuropsychological function in continuous spike-wave during slow wave sleep. METHOD: We performed a prospective clinical trial in patients with continuous spike-wave during sleep aged 4 to 10 years. Patients underwent neuropsychological assessment and overnight electroencephalographic monitoring before treatment, and subsequent repeat assessment and overnight electroencephalographic monitoring 3 months after treatment. Treatment consisted of 1mg/kg clobazam up to a maximum dose of 30mg during the first night, followed by 0.5mg/kg nightly for 3 months. RESULTS: Nine patients completed the study and had pre- and post-neuropsychological evaluation. There was a qualitative reduction in median (p25 -p75 ) spike percentage after 3 months (72.2 [68.0-75.8] vs 32.7 [4.7-81.7]). There were no marked changes in median (p25 -p75 ) IQ comparing pre- and post-clobazam treatment (80.0 [74.0-88.0] vs 80.0 [67.0-89.0]). There was a qualitative increase in Verbal IQ (83.0 [69.0-92.0] vs 95.0 [83.0-99.0]) and a qualitative decrease in Non-verbal IQ (84.0 [74.0-87.0] vs 71.0 [60.0-84.0]). INTERPRETATION: Qualitative improvements in epileptiform activity and cognition occurred in patients treated with clobazam for 3 months and the relationship between epileptiform activity and cognitive outcome should be studied in larger studies. WHAT THIS PAPER ADDS: Verbal IQ in patients with continuous spike-wave during sleep improved following short-term treatment with clobazam. Other neuropsychological improvements were observed, but varied by patient. Cognitive improvement was observed despite some worsening of epileptiform discharges.

Effect of vigabatrin on seizure control and safety profile in different subgroups of children with epilepsy.

OBJECTIVE: To evaluate the efficacy and safety of vigabatrin in pediatric epilepsy. METHODS: We retrospectively reviewed patients with epilepsy treated with vigabatrin over a 2-year period at a pediatric tertiary center. We assessed the relationship between seizure frequency, etiology, vigabatrin dose, adverse events, medication discontinuation reasons, and electroencephalography (EEG) characteristics. RESULTS: One hundred three patients followed at Boston Children's Hospital were treated with vigabatrin and had complete medical records. Within the follow-up interval, 69 (67%) of 103 patients had discontinued vigabatrin therapy. Two patients (1.9%) died during therapy for unknown reasons. Median age at vigabatrin initiation was 8 months (interquartile range [IQR] 5-15). Median starting dose was 48.1 mg/kg per day (IQR 29.8-52.3) with a median target of 100 mg/kg (IQR 81.9-107.9). Median treatment duration was 12.1 months (n = 89, IQR 5.0-22.9) overall, and 13.3 months (IQR 5.2-23.2) for patients who discontinued vigabatrin. The most common reasons for discontinuation were controlled seizures in 31 (43.7%) of 71 and unsatisfactory therapeutic effect in 23 (32.4%) of 71. Median percent seizure reduction from baseline to first follow-up was 83.3% (IQR 27.4-99.8) and 96.7% (IQR 43.3-100) to last follow-up. Twenty-four (38.7%) of 62 patients with a follow-up posttreatment remained seizure-free. Four patients who had initially achieved seizure freedom relapsed. Patients with structural/metabolic etiology had greater median percent seizure reduction at first follow-up than patients with genetic etiology (98.7% vs. 61.4%, respectively, p = 0.001). Hypsarrhythmia resolved after therapy in 18 of 20 (90%, 95% confidence interval [CI] 70-97) patients with pretreatment hypsarrhythmia, and 2 patients presented with hypsarrhythmia posttreatment. Risk of having hypsarrhythmia was reduced by 32% (95% CI 14.9-49.1) posttreatment. SIGNIFICANCE: Vigabatrin is efficacious in all seizure types and resolved hypsarrhythmia in most patients. In this series with a median treatment duration of 12.1 months, vigabatrin had a good safety profile with a low rate of discontinuation due to nonophthalmologic and ophthalmologic adverse effects.

Developmental expression of N-methyl-D-aspartate (NMDA) receptor subunits in human white and gray matter: potential mechanism of increased vulnerability in the immature brain.

The pathophysiology of perinatal brain injury is multifactorial and involves hypoxia-ischemia (HI) and inflammation. N-methyl-d-aspartate receptors (NMDAR) are present on neurons and glia in immature rodents, and NMDAR antagonists are protective in HI models. To enhance clinical translation of rodent data, we examined protein expression of 6 NMDAR subunits in postmortem human brains without injury from 20 postconceptional weeks through adulthood and in cases of periventricular leukomalacia (PVL). We hypothesized that the developing brain is intrinsically vulnerable to excitotoxicity via maturation-specific NMDAR levels and subunit composition. In normal white matter, NR1 and NR2B levels were highest in the preterm period compared with adult. In gray matter, NR2A and NR3A expression were highest near term. NR2A was significantly elevated in PVL white matter, with reduced NR1 and NR3A in gray matter compared with uninjured controls. These data suggest increased NMDAR-mediated vulnerability during early brain development due to an overall upregulation of individual receptors subunits, in particular, the presence of highly calcium permeable NR2B-containing and magnesium-insensitive NR3A NMDARs. These data improve understanding of molecular diversity and heterogeneity of NMDAR subunit expression in human brain development and supports an intrinsic prenatal vulnerability to glutamate-mediated injury; validating NMDAR subunit-specific targeted therapies for PVL.

Refractory Status Epilepticus in Children: Intention to Treat With Continuous Infusions of Midazolam and Pentobarbital.

OBJECTIVE: To describe pediatric patients with convulsive refractory status epilepticus in whom there is intention to use an IV anesthetic for seizure control. DESIGN: Two-year prospective observational study evaluating patients (age range, 1 mo to 21 yr) with refractory status epilepticus not responding to two antiepileptic drug classes and treated with continuous infusion of anesthetic agent. SETTING: Nine pediatric hospitals in the United States. PATIENTS: In a cohort of 111 patients with refractory status epilepticus (median age, 3.7 yr; 50% male), 54 (49%) underwent continuous infusion of anesthetic treatment. MAIN RESULTS: The median (interquartile range) ICU length of stay was 10 (3-20) days. Up to four "cycles" of serial anesthetic therapy were used, and seizure termination was achieved in 94% by the second cycle. Seizure duration in controlled patients was 5.9 (1.9-34) hours for the first cycle and longer when a second cycle was required (30 [4-120] hr; p = 0.048). Midazolam was the most frequent first-line anesthetic agent (78%); pentobarbital was the most frequently used second-line agent after midazolam failure (82%). An electroencephalographic endpoint was used in over half of the patients; higher midazolam dosing was used with a burst suppression endpoint. In midazolam nonresponders, transition to a second agent occurred after a median of 1 day. Most patients (94%) experienced seizure termination with these two therapies. CONCLUSIONS: Midazolam and pentobarbital remain the mainstay of continuous infusion therapy for refractory status epilepticus in the pediatric patient. The majority of patients experience seizure termination within a median of 30 hours. These data have implications for the design and feasibility of future intervention trials. That is, testing a new anesthetic anticonvulsant after failure of both midazolam and pentobarbital is unlikely to be feasible in a pediatric study, whereas a decision to test an alternative to pentobarbital, after midazolam failure, may be possible in a multicenter multinational study.

Chloride cotransporter NKCC1 inhibitor bumetanide protects against white matter injury in a rodent model of periventricular leukomalacia.

BACKGROUND: Periventricular leukomalacia (PVL) is a major form of preterm brain injury. Na(+)-K(+)-Cl(-) 1 cotransporter (NKCC1) expression on neurons and astrocytes is developmentally regulated and mediates Cl(-) reversal potential. We hypothesized that NKCC1 is highly expressed on oligodendrocytes (OLs) and increases vulnerability to hypoxia-ischemia (HI) mediated white matter injury, and that the NKCC1 inhibitor bumetanide would be protective in a rodent PVL model. METHODS: Immunohistochemistry in Long-Evans rats and PLP-EGFP transgenic mice was used to establish cell-specific expression of NKCC1 in the immature rodent brain. HI was induced on postnatal day 6 (P6) in rats and the protective efficacy of bumetanide (0.3 mg/kg/i.p. q12h × 60 h) established. RESULTS: NKCC1 was expressed on OLs and subplate neurons through the first 2 postnatal weeks, peaking in white matter and the subplate between P3-7. Following HI, NKCC1 is expressed on OLs and neurons. Bumetanide treatment significantly attenuates myelin basic protein loss and neuronal degeneration 7 d post-HI. CONCLUSION: Presence and relative overexpression of NKCC1 in rodent cerebral cortex coincides with a period of developmental vulnerability to HI white matter injury in the immature prenatal brain. The protective efficacy of bumetanide in this model of preterm brain injury suggests that Cl(-) transport is a factor in PVL and that its inhibition may have clinical application in premature human infants.

Ciliary neurotrophic factor receptor regulation of adult forebrain neurogenesis.

Appropriately targeted manipulation of endogenous neural stem progenitor (NSP) cells may contribute to therapies for trauma, stroke, and neurodegenerative disease. A prerequisite to such therapies is a better understanding of the mechanisms regulating adult NSP cells in vivo. Indirect data suggest that endogenous ciliary neurotrophic factor (CNTF) receptor signaling may inhibit neuronal differentiation of NSP cells. We challenged subventricular zone (SVZ) cells in vivo with low concentrations of CNTF to anatomically characterize cells containing functional CNTF receptors. We found that type B "stem" cells are highly responsive, whereas type C "transit-amplifying" cells and type A neuroblasts are remarkably unresponsive, as are GFAP(+) astrocytes found outside the SVZ. CNTF was identified in a subset of type B cells that label with acute BrdU administration. Disruption of in vivo CNTF receptor signaling in SVZ NSP cells, with a "floxed" CNTF receptor α (CNTFRα) mouse line and a gene construct driving Cre recombinase (Cre) expression in NSP cells, led to increases in SVZ-associated neuroblasts and new olfactory bulb neurons, as well as a neuron subtype-specific, adult-onset increase in olfactory bulb neuron populations. Adult-onset receptor disruption in SVZ NSP cells with a recombinant adeno-associated virus (AAV-Cre) also led to increased neurogenesis. However, the maintenance of type B cell populations was apparently unaffected by the receptor disruption. Together, the data suggest that endogenous CNTF receptor signaling in type B stem cells inhibits adult neurogenesis, and further suggest that the regulation may occur in a neuron subtype-specific manner.

Treatment for continuous spikes and waves during sleep (CSWS): survey on treatment choices in North America.

OBJECTIVE: Current literature does not allow an evidence-based approach to the treatment of continuous spikes and waves during sleep (CSWS). The aim of this study was to describe treatment choices made by clinicians caring for patients with CSWS in North America. METHODS: A 24-question survey on treatment choices for CSWS was distributed to the members of the American Epilepsy Society (AES). The survey presented a clinical vignette of CSWS. The questions addressed treatment choices for that clinical scenario. Surveys were self-administered and collected using an online survey website (www.surveymonkey.com). RESULTS: Two-hundred thirty-two surveys were completed. Prominent sleep-potentiated spiking was considered to warrant treatment by 81% of respondents. The proportion of patients in whom cognitive improvement occurs when sleep-potentiated spiking is effectively treated is in >75% of patients (according to 16% of respondents), in 25-75% of patients (according to 52% of respondents), in <25% of patients (according to 20% of respondents), and no or unclear cognitive changes (according to 12% of respondents). The preferred first choice to reduce sleep-potentiated epileptiform activity was high-dose benzodiazepines (47%), valproate (26%), and corticosteroids (15%). The preferred second-choice was valproate (26%), high-dose benzodiazepines (24%), and corticosteroids (23%). Among high-dose benzodiazepines, the preferred one was diazepam 1 mg/kg for one night followed by 0.5 mg/kg/day. The preferred dose of valproate was 30-49 mg/kg/day. Among corticosteroids the preferred choice was oral prednisone 2 mg/kg/day. The most commonly considered endpoints of treatment efficacy were (in decreasing order): response of epileptiform activity in electroencephalography (EEG), cognitive function, and seizure reduction. Results were consistent among respondents with different levels of training and clinical experience. There were differences in conceptualization and treatment approaches between pediatric and adult neurologists. SIGNIFICANCE: Most clinicians considered that prominent sleep-potentiated epileptiform activity should be treated. There was no agreement on best treatment, but potential candidates included high-dose benzodiazepines, valproate, levetiracetam, and corticosteroids.

Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy.

Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy.

Serum antibodies and DNA indicate a high prevalence of equine papillomavirus 2 (EcPV2) among horses in Switzerland.

BACKGROUND: The DNA of equine papillomavirus type 2 (EcPV2) is consistently found in equine papillomas and squamous cell carcinomas, indicating a causal association of EcPV2 in the pathogenesis of these tumours; however, little is known about the prevalence of this virus. HYPOTHESIS/OBJECTIVES: The aim of this study was to determine the geno- and seroprevalence of EcPV2 in clinically healthy horses in Switzerland. ANIMALS: Fifty horses presented to the equine department of the university clinic, displaying no skin or mucous membrane lesions or severe signs of other diseases, were sampled. METHODS: Cytobrush samples from the penis or vulva and serum samples were collected. To determine the genoprevalence of EcPV2, DNA was extracted from cytobrush samples and tested for viral DNA with a PCR assay amplifying a 338 bp fragment of the E7/E1 region of the viral genome. Seroprevalence was tested using an enzyme-linked immunosorbent assay aimed to detect antibodies against the major capsid protein (L1) of EcPV2. RESULTS: In five of 50 horses (10%), EcPV2-specific DNA was amplified but no antibodies could be detected, whereas in 14 of 50 horses (28%), antibodies against EcPV2 but no DNA were demonstrated. Both antibodies and viral DNA were detected in four of 50 horses (8%). Neither antibodies nor viral DNA were found in 27 of 50 horses (54%). CONCLUSIONS AND CLINICAL IMPORTANCE: The seroprevalence suggests that EcPV2 is prevalent in the Swiss equine population, while the genoprevalence indicates that currently ongoing infections are less common. The discrepancy between geno- and seroprevalence probably indicates different stages of infection in the tested cohort.

AMPA receptor antagonist NBQX attenuates later-life epileptic seizures and autistic-like social deficits following neonatal seizures.

PURPOSE: To determine whether AMPA receptor (AMPAR) antagonist NBQX can prevent early mammalian target of rapamycin (mTOR) pathway activation and long-term sequelae following neonatal seizures in rats, including later-life spontaneous recurrent seizures, CA3 mossy fiber sprouting, and autistic-like social deficits. METHODS: Long-Evans rats experienced hypoxia-induced neonatal seizures (HS) at postnatal day (P)10. NBQX (20 mg/kg) was administered immediately following HS (every 12 h × 4 doses). Twelve hours post-HS, we assessed mTOR activation marker phosphorylated p70-S6 kinase (p-p70S6K) in hippocampus and cortex of vehicle (HS + V) or NBQX-treated post-HS rats (HS + N) versus littermate controls (C + V). Spontaneous seizure activity was compared between groups by epidural cortical electroencephalography (EEG) at P70-100. Aberrant mossy fiber sprouting was measured using Timm staining. Finally, we assessed behavior between P30 and P38. KEY FINDINGS: Postseizure NBQX treatment significantly attenuated seizure-induced increases in p-p70S6K in the hippocampus (p < 0.01) and cortex (p < 0.001). Although spontaneous recurrent seizures increased in adulthood in HS + V rats compared to controls (3.22 ± 1 seizures/h; p = 0.03), NBQX significantly attenuated later-life seizures (0.14 ± 0.1 seizures/h; p = 0.046). HS + N rats showed less aberrant mossy fiber sprouting (115 ± 8.0%) than vehicle-treated post-HS rats (174 ± 10%, p = 0.004), compared to controls (normalized to 100%). Finally, NBQX treatment prevented alterations in later-life social behavior; post-HS rats showed significantly decreased preference for a novel over a familiar rat (71.0 ± 12 s) compared to controls (99.0 ± 15.6 s; p < 0.01), whereas HS + N rats showed social novelty preference similar to controls (114.3 ± 14.1 s). SIGNIFICANCE: Brief NBQX administration during the 48 h postseizure in P10 Long-Evans rats suppresses transient mTOR pathway activation and attenuates spontaneous recurrent seizures, social preference deficits, and mossy fiber sprouting observed in vehicle-treated adult rats after early life seizures. These results suggest that acute AMPAR antagonist treatment during the latent period immediately following neonatal HS can modify seizure-induced activation of mTOR, reduce the frequency of later-life seizures, and protect against CA3 mossy fiber sprouting and autistic-like social deficits.

Explainable AI for wearable seizure logging: Impact of data quality, patient age, and antiseizure medication on performance.

OBJECTIVE: Objective seizure count estimates are crucial for ambulatory epilepsy management. Wearables have shown promise for the detection of tonic-clonic seizures but may suffer from false alarms and undetected seizures. Seizure signatures recorded by wearables often occur over prolonged periods, including increased levels of electrodermal activity and heart rate long after seizure EEG onset, however, previous detection methods only partially exploited these signatures. Understanding the utility of these prolonged signatures for seizure count estimation and what factors generally determine seizure logging performance, including the role of data quality vs. algorithm performance, is thus crucial for improving wearables-based epilepsy monitoring and determining which patients benefit most from this technology. METHODS: In this retrospective study we examined 76 pediatric epilepsy patients during multiday video-EEG monitoring equipped with a wearable (Empatica E4; records of electrodermal activity, EDA, accelerometry, ACC, heart rate, HR; 1983 h total recording time; 45 tonic-clonic seizures). To log seizures on prolonged data trends, we applied deep learning on continuous overlapping 1-hour segments of multimodal data in a leave-one-subject-out approach. We systematically examined factors influencing logging performance, including patient age, antiseizure medication (ASM) load, seizure type and duration, and data artifacts. To gain insights into algorithm function and feature importance we applied Uniform Manifold Approximation and Projection (UMAP, to represent the separability of learned features) and SHapley Additive exPlanations (SHAP, to represent the most informative data signatures). RESULTS: Performance for tonic-clonic seizure logging increased systematically with patient age (AUC 0.61 for patients 〈 11 years, AUC 0.77 for patients between 11-15 years, AUC 0.85 for patients 〉 15 years). Across all ages, AUC was 0.75 corresponding to a sensitivity of 0.52 and a false alarm rate of 0.28/24 h. Seizures under high ASM load or with shorter duration were detected worse (P=.025, P=.033, respectively). UMAP visualized discriminatory power at the individual patient level, SHAP analyses identified clonic motor activity and peri/postictal increases in HR and EDA as most informative. In contrast, in missed seizures, these features were absent indicating that recording quality but not the algorithm caused the low sensitivity in these patients. SIGNIFICANCE: Our results demonstrate the utility of prolonged, postictal data segments for seizure logging, contribute to algorithm explainability and point to influencing factors, including high ASM dose and short seizure duration. Collectively, these results may help to identify patients who particularly benefit from such technology.