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Malformations of the brain are common and vary in severity, from negligible to potentially fatal. Their causes have not been fully elucidated. Here, we report pathogenic variants in the core protein-folding machinery TRiC/CCT in individuals with brain malformations, intellectual disability, and seizures. The chaperonin TRiC is an obligate hetero-oligomer, and we identify variants in seven of its eight subunits, all of which impair function or assembly through different mechanisms. Transcriptome and proteome analyses of patient-derived fibroblasts demonstrate the various consequences of TRiC impairment. The results reveal an unexpected and potentially widespread role for protein folding in the development of the central nervous system and define a disease spectrum of "TRiCopathies."

Purpose: Seizures are characterized by periictal autonomic changes. Wearable devices could help improve our understanding of these phenomena through long-term monitoring. In this study, we used wearable electrocardiogram (ECG) data to evaluate differences between temporal and extratemporal focal impaired awareness (FIA) seizures monitored in the hospital and at home. We assessed periictal heart rate, respiratory rate, heart rate variability (HRV), and respiratory sinus arrhythmia (RSA)., Methods: We extracted ECG signals across three time points - five minutes baseline and preictal, ten minutes postictal - and the seizure duration. After automatic Rpeak selection, we calculated the heart rate and estimated the respiratory rate using the ECG-derived respiration methodology. HRV was calculated in both time and frequency domains. To evaluate the influence of other modulators on the HRV after removing the respiratory influences, we recalculated the residual power in the high-frequency (HF) and low-frequency (LF) bands using orthogonal subspace projections. Finally, 5-minute and 30-second (ultra-short) ECG segments were used to calculate RSA using three different methods. Seizures from temporal and extratemporal origins were compared using mixed-effects models and estimated marginal means., Results: The mean preictal heart rate was 69.95 bpm (95 % CI 65.6 - 74.3), and it increased to 82 bpm, 95 % CI (77.51 - 86.47) and 84.11 bpm, 95 % CI (76.9 - 89.5) during the ictal and postictal periods. Preictal, ictal and postictal respiratory rates were 16.1 (95 % CI 15.2 - 17.1), 14.8 (95 % CI 13.4 - 16.2) and 15.1 (95 % CI 14 - 16.2), showing not statistically significant bradypnea. HRV analysis found a higher baseline power in the LF band, which was still significantly higher after removing the respiratory influences. Postictally, we found decreased power in the HF band and the respiratory influences in both frequency bands. The RSA analysis with the new methods confirmed the lower cardiorespiratory interaction during the postictal period. Additionally, using ultra-short ECG segments, we found that RSA decreases before the electroclinical seizure onset. No differences were observed in the studied parameters between temporal and extratemporal seizures., Conclusions: We found significant increases in the ictal and postictal heart rates and lower respiratory rates. Isolating the respiratory influences on the HRV showed a postictal reduction of respiratory modulations on both LF and HF bands, suggesting a central role of respiratory influences in the periictal HRV, unlike the baseline measurements. We found a reduced cardiorespiratory interaction during the periictal period using other RSA methods, suggesting a blockade in vagal efferences before the electroclinical onset. These findings highlight the importance of respiratory influences in cardiac dynamics during seizures and emphasize the need to longitudinally assess HRV and RSA to gain insights into long-term autonomic dysregulation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

People with epilepsy frequently under- or inaccurately report their seizures, which poses a challenge for evaluating their treatment. The introduction of epilepsy health apps provides a novel approach that could improve seizure documentation. This study assessed the documentation performance of an app-based seizure diary and a conventional paper seizure diary. At two tertiary epilepsy centers patients were asked to use one of two offered methods to report their seizures (paper or app diary) during their stay in the epilepsy monitoring unit. The performances of both methods were assessed based on the gold standard of video-EEG annotations. In total 89 adults (54 paper and 35 app users) with focal epilepsy were included in the analysis, of which 58 (33 paper and 25 app users) experienced at least one seizure and made at least one seizure diary entry. We observed a high precision of 85.7% for the app group, whereas the paper group's precision was lower due to overreporting (66.9%). Sensitivity was similar for both methods. Our findings imply that performance of seizure self-reporting is patient-dependent but is more precise for patients who are willing to use digital apps. This may be relevant for treatment decisions and future clinical trial design., (© 2024. The Author(s).)

Tonic-clonic seizures (TCSs) pose a significant risk for sudden unexpected death in epilepsy (SUDEP). Previous research has highlighted the potential of multimodal wearable seizure detection systems in accurately detecting TCSs through continuous monitoring, enabling timely alarms and potentially preventing SUDEP. However, such multimodal systems carry a higher risk of sensor malfunction. In this paper, we propose a cyclic transformer approach to address these challenges. The cyclic transformer learns a robust representation by performing circular modal translations between the source and target modalities. It leverages back-translation as regularization technique to enhance the discriminative power of the learned representation. Notably, the proposed cyclic transformer is trained on paired multimodal data but requires only a single source modality during deployment. This characteristic ensures the robustness of the cyclic transformer to perturbations or missing information in the target modality. Experimental results demonstrate that the proposed cyclic transformer achieves competitive performance compared with existing multimodal systems. While both approaches were trained using EEG and EMG data, the cyclic transformer exclusively employs EEG data for testing, diverging from the state-of-the-art's utilization of both EEG and EMG data during test. This showcases the effectiveness of the cyclic transformer in multimodal TCSs detection, offering a promising approach for enhancing the accuracy and robustness of seizure detection systems while mitigating the risks associated with sensor malfunction.

Epileptic seizure detection aims to replace unreliable seizure diaries by a model that automatically detects seizures based on electroencephalography (EEG) sensors. However, developing such a model is difficult and time consuming as it requires manually searching for relevant features from complex EEG data. Domain experts may have a partial understanding of the EEG characteristics that indicate seizures, but this knowledge is often not sufficient to exhaustively enumerate all relevant features. To address this challenge, we investigate how automated feature construction may complement hand-crafted features for epileptic seizure detection. By means of an empirical comparison on a real-world seizure detection dataset, we evaluate the ability of automated feature construction to come up with new relevant features. We show that combining hand-crafted and automated features results in more accurate models compared to using hand-crafted features alone. Our findings suggest that future studies on developing EEG-based seizure detection models may benefit from features constructed using a combination of hand-crafted and automated feature engineering.

Objective: Seizure diaries kept by patients are unreliable. Automated electroencephalography (EEG)-based seizure detection systems are a useful support tool to objectively detect and register seizures during long-term video-EEG recording. However, this standard full scalp-EEG recording setup is of limited use outside the hospital, and a discreet, wearable device is needed for capturing seizures in the home setting. We are developing a wearable device that records EEG with behind-the-ear electrodes. In this study, we determined whether the recognition of ictal patterns using only behind-the-ear EEG channels is possible. Second, an automated seizure detection algorithm was developed using only those behind-the-ear EEG channels., Methods: Fifty-four patients with a total of 182 seizures, mostly temporal lobe epilepsy (TLE), and 5284 hours of data, were recorded with a standard video-EEG at University Hospital Leuven. In addition, extra behind-the-ear EEG channels were recorded. First, a neurologist was asked to annotate behind-the-ear EEG segments containing selected seizure and nonseizure fragments. Second, a data-driven algorithm was developed using only behind-the-ear EEG. This algorithm was trained using data from other patients (patient-independent model) or from the same patient (patient-specific model)., Results: The visual recognition study resulted in 65.7% sensitivity and 94.4% specificity. By using those seizure annotations, the automated algorithm obtained 64.1% sensitivity and 2.8 false-positive detections (FPs)/24 hours with the patient-independent model. The patient-specific model achieved 69.1% sensitivity and 0.49 FPs/24 hours., Significance: Visual recognition of ictal EEG patterns using only behind-the-ear EEG is possible in a significant number of patients with TLE. A patient-specific seizure detection algorithm using only behind-the-ear EEG was able to detect more seizures automatically than what patients typically report, with 0.49 FPs/24 hours. We conclude that a large number of refractory TLE patients can benefit from using this device., (© 2020 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.)

Purpose: Despite the availability of a broad range of treatments for epilepsy, a significant proportion of patients have ongoing seizures. This study aims to characterize the drug resistant population and to report long-term outcomes of patients undergoing different types of pharmacological and surgical treatment., Methods: Adult patients with drug resistant epilepsy (DRE) were identified from a largely retrospective database of 900 consecutive patients with epilepsy, recruited from two reference centers for DRE in Belgium. We report treatment trajectories and long-term seizure outcomes in the different treatment groups., Results: 640 patients had DRE. 249 (38.9%) underwent presurgical assessment, followed by surgical treatment in 197 (30.8%), resulting in seizure freedom in 86 (13.4%). 443 patients (69.2%) were treated only with further AED trials, of which 163 (25.5%) became seizure free. In the 391 patients with ongoing seizures (61.1%), mean age was 43.2 years, mean disease duration 23 years and mean number of AED trials 6.9. 291 (74.4%) had tonic-clonic seizures, and 43 (11.0%) had one or more episodes of status epilepticus. Patients with hippocampal sclerosis were significantly more likely to be seizure free, while patients with malformation of cortical development and those with temporal lobe epilepsy of unknown etiology were more likely to have ongoing seizures., Conclusion: Our findings demonstrate that - even with adequate access to surgical treatment and further AED trials - 61.1% of patients with DRE had ongoing seizures. This illustrates that there is a scope for ongoing development of novel treatments for DRE., (Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.)

Aim: To study the association between global hemodynamics, blood gases, epileptiform EEG activity and survival after out-of-hospital CA (0HCA)., Methods: We retrospectively analyzed 195 comatose post-CA patients. At least one EEG recording per patient was evaluated to diagnose epileptiform EEG activity. Refractory epileptiform EEG activity was defined as persisting epileptic activity on EEG despite the use of 2 or more anti-epileptics. The time weighted average mean arterial pressure 48h (TWA-MAP48), the percentage of time with a MAP below 65 and above 85mmHg and the percentage of time with normoxia, hypoxia (<70mmHg), hyperoxia (>150mmHg), normocapnia, hypocapnia (<35mmHg) and hypercapnia (>45mmHg) were calculated., Results: We observed epileptiform EEG activity in 57 patients (29%). A shockable rhythm was associated with a decreased likelihood of epileptic activity on the EEG (OR: 0.41, 95%CI 0.22-0.79). We did not identify an association between the TWA-MAP48, the percentage of time with MAP below 65mmHg or above 85mmHg, blood gas variables and the risk of post-CA epileptiform EEG activity. The presence of epileptiform activity decreased the likelihood of survival independently (OR: 0.10, 95% CI: 0.04-0.24). Interestingly, survival rates of patients in whom the epileptiform EEG resolved (n=20), were similar compared to patients without epileptiform activity on EEG (60% vs 67%,p=0.617). Other independent predictors of survival were presence of basic life support (BLS) (OR:5.08, 95% CI 1.98-13.98), presence of a shockable rhythm (OR: 7.03, 95% CI: 3.18-16.55), average PaO 2 (OR=0.93, CI 95% 0.90-0.96) and% time MAP<65mmHg (OR: 0.96, CI 95% 0.94-0.98)., Conclusion: Epileptiform EEG activity in post-CA patients is independently and inversely associated with survival and this effect is mainly driven by patients in whom this pattern is refractory over time despite treatment with anti-epileptic drugs. We did not identify an association between hemodynamic factors, blood gas variables and epileptiform EEG activity after CA, although both hypotension, hypoxia and epileptic EEG activity were predictors of survival., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Epileptic seizures are network-level phenomena. Hence, epilepsy may be regarded as a circuit-level disorder that cannot be understood outside this context. Better insight into the effective connectivity of the seizure onset zone and the manner in which seizure activity spreads could lead to specifically-tailored therapies for epilepsy. We applied the electrical amygdala kindling model in two rhesus monkeys until these animals displayed consistent stage IV seizures. At this stage, we investigated the effective connectivity of the amygdala by means of electrical microstimulation during fMRI (EM-fMRI). In addition, we imaged changes in perfusion during a seizure using ictal SPECT perfusion imaging. The spatial overlap between the connectivity network and the ictal perfusion network was assessed both at the regional level, by calculating Dice coefficients using anatomically defined regions of interest, and at the voxel level. The kindled amygdala was extensively connected to bilateral cortical and subcortical structures, which in many cases were connected multisynaptically to the amygdala. At the regional level, the spatial extents of many of these fMRI activations and deactivations corresponded to the respective increases and decreases in perfusion imaged during a stage IV seizure. At the voxel level, however, some regions showed residual seizure-specific activity (not overlapping with the EM-fMRI activations) or fMRI-specific activation (not overlapping with the ictal SPECT activations), indicating that frequently, only a part of a region anatomically connected to the seizure onset zone participated in seizure propagation. Thus, EM-fMRI in the amygdala of electrically-kindled monkeys reveals widespread areas that are often connected multisynaptically to the seizure focus. Seizure activity appears to spread, to a large extent, via these connected areas.

Objective: Amygdala kindling is a widely used animal model for studying mesial temporal lobe epileptogenesis. In the macaque monkey, electrical amygdala kindling develops slowly and provides an opportunity for investigating ictal perfusion changes during epileptogenesis., Methods: Two rhesus monkeys were electrically kindled through chronically implanted electrodes in the right amygdala over a period of 16 and 17 months. Ictal perfusion single photon emission computed tomography (SPECT) imaging was performed during each of the four predefined clinical stages., Results: Afterdischarge duration increased slowly over 477 days for monkey K and 515 days for monkey S (18 ± 8 s in stage I; 52 ± 13 s in stage IV). During this time, the animals progressed through four clinical stages ranging from interrupting ongoing behavior to bilateral convulsions. Ictal SPECT perfusion imaging showed well-localized but widely distributed regions of hyperperfusion and hypoperfusion, in both cortical and subcortical structures, at every seizure stage. A large portion of the ictal network was involved in the early stages of epileptogenesis and subsequently expanded over time as seizure severity evolved., Significance: Our data indicate that the different mesial temporal lobe seizure types occur within a common network affecting several parts of the brain, and that seizure severity may be determined by seizure-induced epileptogenesis within a bihemispheric network that is implicated from the start of the process., (Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.)

Changing from brand name to generic antiepileptic drugs (AEDs) is increasingly being advocated by the authorities, principally for budgetary reasons. However, caution should be exercised since AEDs may have a narrow therapeutic margin, the regimen with AEDs may be complex, the consequences of uncontrolled seizures may be severe, and risk of side effects is relatively high, particularly when seizures are difficult to control. This article focuses on the possible problems that can arise from the substitution of AEDs formulations, such as loss of seizure control and emergence of new side effects. We would advise that patients stay on the same formulation of the first AED, whether a brand name or generic AED. Switching AED formulations should always be done with the necessary caution and under the physician's supervision. Closer follow-up during the transitional period is necessary, and dosage adjustment may be required. The patient should be given full and correct advice about risks involved in switching AED formulations.

Long-term electroencephalographic (EEG) recordings are important in the presurgical evaluation of refractory partial epilepsy for the delineation of the irritative and ictal onset zones. In this paper we introduce a new algorithm for an automatic, fast and objective localizing of the ictal onset zone in ictal EEG recordings. We extracted the potential distribution of the ictal activity from EEG using the higher order canonical decomposition method, also referred to as the CP model. The CP model decomposes in a unique way a higher order tensor in a minimal sum of rank-1 'atoms'. We showed that only one atom is related to the seizure activity. Simulation experiments demonstrated that the method correctly extracted the potential distribution of the ictal activity even with low signal-to-noise ratios. In 37 ictal EEGs, the CP method correctly localized the seizure onset zone in 34 (92%) and visual assessment in 21 cases (57%) (p=0.00024). The CP method is a fast method to delineate the ictal onset zone in ictal EEGs and is more sensitive than visual interpretation of the ictal EEGs.

Seizures are a recognized complication of human immunodeficiency virus (HIV)-type-1 infection. CNS disease processes in these patients include encephalitis, focal brain lesions, and meningitis. Metabolic causes of seizures have received little attention. In a retrospective study, we selected 68 HIV-seropositive patients with new-onset seizures and information available for specified metabolic factors on the day of the first seizure. We sought an association of metabolic abnormalities with convulsive status epilepticus (CSE), which was the initial seizure in 12 patients, predominantly intravenous (i.v.) drug users. HIV-seropositive patients with new-onset seizures and hypomagnesemia or renal failure appeared to be at increased risk for CSE. All HIV-seropositive patients with new-onset seizures should undergo metabolic screening including renal function and serum magnesium levels.

The localizing value of ictal single-photon emission computed tomography (SPECT) performed with cerebral blood flow agents in patients with epilepsy is based on cerebral metabolic and perfusion coupling. Ictal hyperperfusion is used to localize the epileptogenic zone noninvasively, and is particularly useful in magnetic resonance (MR)-negative partial epilepsy and focal cortical dysplasias. Subtraction ictal SPECT coregistered with MRI (SISCOM) improves the localization of the area of hyperperfusion. Ictal SPECT should always be interpreted in the context of a full presurgical evaluation. Early ictal SPECT injections minimize the problem of seizure propagation and of nonlocalization due to an early switch from ictal hyperperfusion to postictal hypoperfusion during brief extratemporal seizures. The degree of thresholding of SISCOM images affects the sensitivity and specificity of ictal SPECT. Ictal hypoperfusion may reflect ictal inhibition or deactivation. Postictal and interictal SPECT studies are less useful to localize the ictal-onset zone. Statistical parametric mapping analysis of groups of selected ictal–interictal difference images has the potential to demonstrate the evolution of cortical, subcortical, and cerebellar perfusion changes during a particular seizure type, to study seizure-gating mechanisms, and to provide new insights into the pathophysiology of seizures. [ABSTRACT FROM AUTHOR]