Refractory Epilepsy: Clinical Overview

Improvement of FDG PET/CT and MRI concordance in temporal lobe epilepsy pre-surgical assessment using statistical parametric mapping Z-scores

AIM

This retrospective study evaluates the diagnostic performance of statistical parametric mapping (SPM) analysis of interictal F18-fluoro-deoxy-D-glucose positron emission tomography computed tomography (FDG PET/CT) in temporal lobe epilepsy (TLE) patients, aiming to enhance image reporting consistency and correlation between magnetic resonance imaging (MRI) and FDG PET/CT findings and boost confidence in the surgical decision-making.

MATERIALS AND METHODS

Forty-nine TLE patients undergoing MRI and FDG PET/CT imaging at a tertiary epilepsy service were included. Images were visually interpreted by an experienced radiologist and nuclear medicine physician. SPM-based quantitative analysis for FDG PET/CT including Z score asymmetric index (ZAI) was performed. Statistical analyses include receiver operating characteristic curve and Cohen's k statistics.

RESULTS

Significant differences in the standardised uptake value (SUV) ratio and ZAI were observed among left TLE, nonepilepsy, and right TLE (p < 0.01). The areas under the curves for left/nonleft and right/nonright groups were 0.838 and 0.780, respectively. The cutoff value to separate left TLE from nonepilepsy and right TLE was 0.305 with 89.7% sensitivity, 80.0% specificity, 94.6% positive predictive value (PPV), 66.7% negative predictive value (NPV), and a 0.697 Youden index for diagnosis. It was 0.190 to separate right TLE from the other 2 with 87.5% sensitivity, 75.6% specificity, 41.2% PPV, 96.9% NPV, and a 0.631 Youden index for diagnosis. The intermethod agreement between MRI and SUV ratio was moderate (k = 0.48; 95% CI, 0.32-0.65) and that between FDG PET/CT qualitative assessment and ZAI was moderate (k = 0.43; 95% CI, 0.10-0.76).

CONCLUSION

FDG PET/CT-based SUV ratios and ZAI show promising diagnostic value in TLE patients, facilitating the integration of FDG PET/CT practice into presurgical assessment for medically refractory epilepsy.

VNS-induced dose-dependent pupillary response in refractory epilepsy

PURPOSE

The Locus Coeruleus (LC) plays a vital role by releasing norepinephrine, which contributes to the antiepileptic effects of Vagus Nerve Stimulation (VNS). LC activity also influences pupil dilation. Investigating VNS dose-dependent Pupillary Dilation Response (PDR) may provide novel neurophysiological insights into therapeutic response and allow for an objective and personalized optimization of stimulation parameters.

METHODS

Fourteen VNS-implanted patients (9 responders, 5 non-responders) treated for at least 6 months were retrospectively recruited. VNS intensities were adjusted from 0.25 mA to 2.25 mA, or to the highest tolerable level. Concurrently, we tracked pupil size in the left eye and gathered patients' subjective perception scores. Individual curve fitting was used to explore the relationship between VNS intensity and PDR.

RESULTS

PDR increased with stimulation intensity, particularly in responders. In 6 patients, an inverted U-shaped relationship between intensity and PDR was observed 2-3 s after stimulation onset. A significant interaction was found between VNS intensity and responder status, independent of subjective perception.

CONCLUSIONS

VNS induces a dose-dependent PDR, which differs between responders and non-responders. In nearly half the patients, the dose-response relationship was characterized by an inverted U-shape with a maximal VNS effect.

SIGNIFICANCE

We propose VNS-induced PDR as a novel biomarker of VNS response.

Self-regulation of slow cortical potential and seizure suppression by scalp electroencephalography: Early prediction of therapeutic efficacy

OBJECTIVE

Seizure suppression using the neurofeedback (NFB) method by self-regulation of scalp-recorded slow cortical potential (SCP) is effective for patients with refractory focal epilepsy. However, the prolonged training period required prevents it from wider implementation as the standard treatment in clinical practice. Therefore, we examined whether it would be appropriate to shorten the training period, in spite of the small number of patients.

METHODS

12 patients participated the NFB training. 1 course of NFB training consisted of 35 sessions divided into 2 phases. After each phase we evaluated whether each patient acquired NFB control, and seizure reduction was assessed compared to that before training.

RESULTS

Of 11 patients who completed the first training phase, 4 showed reduced post-training seizure frequency, of whom 3 could regulate the SCP polarity (NFB control). Of the remaining 7, 2 acquired NFB control during the second training phase but seizure frequency did not decrease. Furthermore, the other 5 did not acquire NFB control, and seizure frequency did not decrease.

CONCLUSIONS

Patients who acquired NFB control within a short period, i.e., 3 weeks, were more likely to exhibit a lower post-training seizure frequency.

SIGNIFICANCE

SCP self-regulation can be acquired within a short period and is associated with seizure reduction.

Illuminating the Safety, Tolerability, and Efficacy of Different Ketogenic Diets for Individuals with Epilepsy: A Scoping Meta-Review

BACKGROUND

Diet therapies for epilepsy, including the ketogenic diets (KDs), have been used as a treatment for both pediatric and adult populations. Recent studies have focused on the safety, efficacy, and tolerability of various diet therapies for epilepsy. The objective of this scoping meta- review was to evaluate the evidence regarding different ketogenic diets for epilepsy.

METHODS

This study followed the Arksey and O'Malley framework and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for scoping reviews (PRISMA-ScR) reporting standards. The research question was formulated using the Population, Concept, Context (PCC) framework. A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science up to August 14, 2024.

RESULTS

Out of the 152 papers identified, 38 systematic reviews and meta-analyses were included. The review examined the safety, tolerability, and efficacy of diet therapies for epilepsy, particularly in drug-resistant cases. The findings underscore the significant benefits of classic ketogenic diet (CKD) in reducing seizure frequency. The Modified Atkins Diet (MAD) and Medium-Chain Triglyceride (MCT) KD were found to be effective with improved tolerability. The Low Glycemic Index Diet (LGID) may be less effective. Further research is needed to refine these dietary approaches.

CONCLUSION

The KDs are effective in reducing seizure frequency in epilepsy, especially in drug-resistant cases. The results highlight the valuable advantages of the CKD in decreasing the frequency of seizures. The MCT KD and the MAD are also effective options and are generally better tolerated. The LGID shows potential but may be less effective. Further research is needed to enhance these dietary treatments and investigate their long-term impact.

Head-to-Head comparison of [18F]FDG, [18F]FMZ, and [18F]SynVesT-1 positron emission tomography imaging in patients with drug-resistant epilepsy

PURPOSE

The loss of synaptic vesicle glycoprotein 2 A (SV2A) can lead to dysfunction of GABAergic neurons, but a direct comparison of SV2A and GABAA receptor densities in humans has not been assessed. This study evaluated SV2A and GABAA receptor abnormalities in patients with drug-resistant epilepsy (DRE) and compared the patterns to glucose hypometabolism.

METHODS

Eleven patients with DRE were retrospectively recruited and underwent PET imaging with [18F]fluorodeoxyglucose ([18F]FDG), [18F]Flumazenil (FMZ), and [18F]SynVesT-1. Visual assessments counted abnormal metabolic brain regions based on the Anatomical Automatic Labeling (AAL) atlas, while voxel-level analyses delineated the abnormal metabolic distributions. The relationship between hypo-metabolic distributions and the age of epilepsy onset was analyzed.

RESULTS

The hypometabolic regions in [18F]FDG PET, identified in the AAL atlas, was significantly broader than in [18F]FMZ (p = 0.0005) and [18F]SynVesT-1 (p = 0.0010) PET, with no statistical difference observed between [18F]FMZ and [18F]SynVesT-1 PET (p > 0.05). The voxel number in [18F]FDG PET was significantly higher than that of the [18F]FMZ and [18F]SynVesT-1 PET in both hypo-intensity area and severe hypo-intensity area. The ratio of the voxel number between these two area was higher for [18F]SynVesT-1 PET compared to [18F]FDG PET (p = 0.0195) and [18F]FMZ PET (p = 0.0237), and positively correlated with the age of epilepsy onset (r = 0.7397, p = 0.0145).

CONCLUSIONS

[18F]FMZ and [18F]SynVesT-1 PET images revealed a more restricted pattern of reduced uptake compared to [18F]FDG PET in DRE patients. The age of epilepsy onset correlated with a reduction in [18F]SynVesT-1 uptake but not in [18F]FMZ or [18F]FDG uptake.

Towards user-centered design of medical devices for SUDEP prediction and prevention: Insights from persons with epilepsy and caregivers

OBJECTIVES

As epilepsy management medical devices emerge as potential technological solutions for prediction and prevention of sudden death in epilepsy (SUDEP), there is a gap in understanding the features and priorities that should be included in the design of these devices. This study aims to bridge the gap between current technology and emerging needs by leveraging insights from persons with epilepsy (PWE) and caregivers (CG) on current epilepsy management devices and understanding how SUDEP awareness influences preferences and design considerations for potential future solutions.

METHODS

Two cross-sectional surveys were designed to survey PWE and CG on medical device design features, SUDEP awareness, and participation in medical device research. Data analysis included both qualitative thematic analysis and quantitative statistical analysis.

RESULTS

The survey revealed that among 284 responses, CG were more aware of SUDEP than PWE. Comfort was identified as the primary concern regarding wearable medical devices for epilepsy management with significant differences between PWE and CG regarding acceptance and continuous use preferences. The thematic analysis identified integration with daily life, aesthetic and emotional resonance, adaptability to seizure characteristics, and user-centric design specifications as crucial factors to be considered for enhanced medical device adoption. The integration of a companion app is seen as an important tool to enhance communication and data sharing.

DISCUSSION

This study reveals that while SUDEP awareness can promote the development of future SUDEP predictive and preventive medical devices, these should be designed to mitigate its impact on daily life and anxiety of both PWE and CG. Comfort and acceptance are seen as key priorities to support continuous use and are seen as a technical requirement of future medical devices for SUDEP prediction and prevention. Widespread adoption requires these technologies to be customizable to adapt to different lifestyles and social situations. A holistic approach should be used in the design of future medical devices to capture several dimensions of PWE and CG epilepsy management journey and uphold communication between healthcare professionals, PWE and CG.

CONCLUSION

Data from this study highlight the importance of considering user preferences and experiences in the design of epilepsy management medical devices with potential applicability for SUDEP prediction and prevention. By employing user-centered design methods this research provides valuable insights to inform the development of future SUDEP prediction and prevention devices.

Thalamocortical Hodology to Personalize Electrical Stimulation for Focal Epilepsy

Targeted electrical stimulation to specific thalamic regions offers a therapeutic approach for patients with refractory focal and generalized epilepsy who are not candidates for resective surgery. However, clinical outcome varies significantly, in particular for focal epilepsy, influenced by several factors, notably the precise anatomical and functional alignment between cortical regions generating epileptic discharges and the targeted thalamic stimulation sites. Here we hypothesized that targeting thalamic nuclei with precise anatomical and functional connections to epileptic cortical areas (an approach that we refer to as hodological matching) could enhance neuromodulatory effects on focal epileptic discharges. To investigate this, we examined three thalamic subnuclei (pulvinar nucleus, anterior nucleus, and ventral intermediate nucleus/ventral oral posterior nuclei) in a retrospective study involving 32 focal epilepsy patients. Specifically, we first identified hodologically organized thalamocortical fibers connecting these nuclei to individual seizure onset zones (SOZs), combining neuroimaging and electrophysiological techniques. Further, analysis of 216 spontaneous seizures revealed the critical role of matched thalamic nuclei in seizure development and termination. Importantly, electrical stimulation of hodologically-matched thalamic nuclei immediately suppressed intracortical interictal epileptiform discharges, contrasting with ineffective outcomes from stimulation of unmatched targets. Finally, we retrospectively evaluated 7 patients with a chronic hodologically-matched neurostimulation system, which led to a clinically relevant reduction in seizure frequency (median reduction 86.5%), that outstands the current clinical practice of unmatched targets (39%). Our results underscore the potential of hodological thalamic targeting to modulate epileptiform activity in specific cortical regions, highlighting the promise of precision medicine in thalamic neuromodulation for focal refractory epilepsy.

Wnt Signaling Modulators Exhibit Neuroprotective Effects via Combating Astrogliosis and Balancing Synaptic Density at Early and Late Stage Temporal Lobe Epilepsy

Temporal Lobe Epilepsy (TLE) is a severe neurological condition characterized by recurrent seizures that often do not respond well to available anti-seizure medications. TLE has been associated with epileptogenesis, a process that starts during the latent period following a neurologic insult and is followed by chronic phase. Recent research has linked canonical Wnt signaling to the pathophysiology of epileptogenesis and TLE. Our previous study demonstrated differential regulation of canonical Wnt signaling during early and late stage post status epilepticus (SE) induction. Building on these findings, our current study utilized Wnt modulators: GSK-3β inhibitor 6-bromoindirubin-3'-oxime (6-Bio) and disheveled inhibitor niclosamide and investigated their impact on canonical Wnt signaling during the early (30 days) and later stages (60 days) following SE induction. We assessed several parameters, including seizure frequency, astrogliosis, synaptic density, and neuronal counts in hippocampal tissue. We used immunohistochemistry and Nissl staining to evaluate gliosis, synaptic density, and neuronal counts in micro-dissected hippocampi. Western blotting was used to examine the expression of proteins involved in canonical Wnt/β-catenin signaling, and real-time PCR was conducted to analyze their relative mRNA expression. Wnt modulators, 6-Bio and Niclosamide were found to reduce seizure frequency and various other parameters including behavioral parameters, hippocampal morphology, astrogliosis and synaptic density at different stages of TLE.

Riluzole attenuates acute neural injury and reactive gliosis, hippocampal-dependent cognitive impairments and spontaneous recurrent generalized seizures in a rat model of temporal lobe epilepsy

Background

Riluzole exhibits neuroprotective and therapeutic effects in several neurological disease models associated with excessive synaptic glutamate (Glu) release. We recently showed riluzole prevents acute excitotoxic hippocampal neural injury at 3 days in the kainic acid (KA) model of temporal lobe epilepsy (TLE). Currently, it is unknown if preventing acute neural injury and the neuroinflammatory response is sufficient to suppress epileptogenesis.

Methods

The KA rat model of TLE was used to determine if riluzole attenuates acute hippocampal neural injury and reactive gliosis. KA was administered to adult male Sprague-Dawley (250 g) rats at 5 mg/kg/hr until status epilepticus (SE) was observed, and riluzole was administered at 10 mg/kg 1 h and 4 h after SE and once per day for the next 2 days. Immunostaining was used to assess neural injury (FJC and NeuN), microglial activation (Iba1 and ED-1/CD68) and astrogliosis (GFAP and vimentin) at day 7 and day 14 after KA-induced SE. Learning and memory tests (Y-maze, Novel object recognition test, Barnes maze), behavioral hyperexcitability tests, and spontaneous generalized recurrent seizure (SRS) activity (24-hour video monitoring) were assessed at 11-15 weeks.

Results

Here we show that KA-induced hippocampal neural injury precedes the neuroimmune response and that riluzole attenuates acute neural injury, microglial activation, and astrogliosis at 7 and 14 days. We find that reducing acute hippocampal injury and the associated neuroimmune response following KA-induced SE by riluzole attenuates hippocampal-dependent cognitive impairment, behavioral hyperexcitability, and tonic/clonic generalized SRS activity after 3 months. We also show that riluzole attenuates SE-associated body weight loss during the first week after KA-induced SE.

Discussion

Riluzole acts on multiple targets that are involved to prevent excessive synaptic Glu transmission and excitotoxic neuronal injury. Attenuating KA-induced neural injury and subsequent microglia/astrocyte activation in the hippocampus and extralimbic regions with riluzole reduces TLE-associated cognitive deficits and generalized SRS and suggests that riluzole could be a potential antiepileptogenic drug.

An Efficient Epilepsy Prediction Model on European Dataset With Model Evaluation Considering Seizure Types

This paper develops a computationally efficient model for automatic patient-specific seizure prediction using a two-layer LSTM from multichannel intracranial electroencephalogram time-series data. We decrease the number of parameters by employing a smaller input size and fewer electrodes, thereby making the model a viable option for wearable and implantable devices. We test the proposed prediction model on 26 patients from the European iEEG dataset, which is the largest epileptic seizure dataset. We also apply an automatic preprocessing technique based on a common average reference to remove artifacts from this dataset. The simulation results show that the model with its simple structure in conjunction with the mean post-processing procedure performed the best, with an average AUC of 0.885. This study is the first that utilizes the European database for epilepsy prediction application and the first that analyzes the effect of the seizure type on the system performance and demonstrates that the seizure type has a considerable impact.

Lipophilic compounds restore function to neurodevelopmental-associated KCNQ3 mutations

A major driver of neuronal hyperexcitability is dysfunction of K+ channels, including voltage-gated KCNQ2/3 channels. Their hyperpolarized midpoint of activation and slow activation and deactivation kinetics produce a current that regulates membrane potential and impedes repetitive firing. Inherited mutations in KCNQ2 and KCNQ3 are linked to a wide spectrum of neurodevelopmental disorders (NDDs), ranging from benign familial neonatal seizures to severe epileptic encephalopathies and autism spectrum disorders. However, the impact of these variants on the molecular mechanisms underlying KCNQ3 channel function remains poorly understood and existing treatments have significant side effects. Here, we use voltage clamp fluorometry, molecular dynamic simulations, and electrophysiology to investigate NDD-associated variants in KCNQ3 channels. We identified two distinctive mechanisms by which loss- and gain-of function NDD-associated mutations in KCNQ3 affect channel gating: one directly affects S4 movement while the other changes S4-to-pore coupling. MD simulations and electrophysiology revealed that polyunsaturated fatty acids (PUFAs) primarily target the voltage-sensing domain in its activated conformation and form a weaker interaction with the channel's pore. Consistently, two such compounds yielded partial and complete functional restoration in R227Q- and R236C-containing channels, respectively. Our results reveal the potential of PUFAs to be developed into therapies for diverse KCNQ3-based channelopathies.

Label-free functional imaging of vagus nerve stimulation-evoked potentials at the cortical surface

Vagus nerve stimulation (VNS) is an FDA-approved stimulation therapy to treat patients with refractory epilepsy. In this work, we use a coherent holographic imaging system to characterize vagus nerve-evoked potentials (VEPs) in the cortex in response to VNS stimulation paradigms without electrode placement or any genetic, structural, or functional labels. We analyze stimulation amplitude up to saturation, pulse width up to 800 μs, and frequency from 10 Hz to 30 Hz, finding that stimulation amplitude strongly modulates VEPs response magnitude (effect size 0.401), while pulse width has a moderate modulatory effect (effect size 0.127) and frequency has almost no modulatory effect (effect size 0.009) on the evoked potential magnitude. We find mild interactions between pulse width and frequency. This non-contact label-free functional imaging technique may serve as a non-invasive rapid-feedback tool to characterize VEPs and may increase the efficacy of VNS in patients with refractory epilepsy.

A data augmentation procedure to improve detection of spike ripples in brain voltage recordings

Epilepsy is a major neurological disorder characterized by recurrent, spontaneous seizures. For patients with drug-resistant epilepsy, treatments include neurostimulation or surgical removal of the epileptogenic zone (EZ), the brain region responsible for seizure generation. Precise targeting of the EZ requires reliable biomarkers. Spike ripples - high-frequency oscillations that co-occur with large amplitude epileptic discharges - have gained prominence as a candidate biomarker. However, spike ripple detection remains a challenge. The gold-standard approach requires an expert manually visualize and interpret brain voltage recordings, which limits reproducibility and high-throughput analysis. Addressing these limitations requires more objective, efficient, and automated methods for spike ripple detection, including approaches that utilize deep neural networks. Despite advancements, dataset heterogeneity and scarcity severely limit machine learning performance. Our study explores long-short term memory (LSTM) neural network architectures for spike ripple detection, leveraging data augmentation to improve classifier performance. We highlight the potential of combining training on augmented and in vivo data for enhanced spike ripple detection and ultimately improving diagnostic accuracy in epilepsy treatment.

Drug-Resistant Epilepsy: Experience From a Tertiary Care Center in Saudi Arabia

Objectives This study aimed to describe the clinical characteristics, investigational results, and management strategies in patients with drug-resistant epilepsy (DRE). Methods This retrospective cohort study included all adult and adolescent patients (aged 14 years or older) diagnosed with DRE who visited the adult neurology clinic at King Abdulaziz Medical City, Jeddah, Saudi Arabia from January 2019 to December 2021. DRE was defined as failure to achieve seizure freedom despite undergoing adequate trials of two well-tolerated and appropriately selected antiseizure medications. Results This study included 299 patients with DRE. Most patients were in their second to fourth decade, with a mean age of 37 ± 17 years. Focal onset epilepsy was diagnosed in 52.5% of the patients, and an etiology for epilepsy was determined in 44.1% of the patients. Findings in brain magnetic resonance imaging were abnormal in 49% of the patients, whereas abnormal findings in electroencephalograms were found in 27.5%. The most common antiseizure medication was levetiracetam (67.6% of cases). Conclusion The findings of this study confirm the challenges in diagnosing and managing patients with DRE and emphasize the necessity for careful and comprehensive patient evaluation. Further research is needed to investigate the effectiveness, safety, and accessibility of diagnostic and therapeutic resources for patients with DRE.

The Traf2 and NcK interacting kinase inhibitor NCB-0846 suppresses seizure activity involving the decrease of GRIA1

Epilepsy, one of the most common neurological disorders, is characterized by spontaneous recurrent seizures. Temporal lobe epilepsy (TLE) is one of the most common medically intractable seizure disorders. Traf2-and NcK-interacting kinase (TNIK) has recently attracted attention as a critical modulation target of many neurological and psychiatric disorders, but its role in epilepsy remains unclear. In this study, we hypothesized the involvement of TNIK in epilepsy and investigated TNIK expression in patients with intractable TLE and in a pilocarpine-induced rat model of epilepsy by western blotting, immunofluorescence, and immunohistochemistry. A pentylenetetrazole (PTZ)-induced epilepsy rat model was used to determine the effect of the TNIK inhibitor NCB-0846 on behavioral manifestations of epilepsy. Coimmunoprecipitation (Co-IP)/mass spectrometry (MS) was used to identify the potential mechanism. Through Co-IP, we detected and confirmed the main potential TNIK interactors. Subcellular fractionation was used to establish the effect of NCB-0846 on the expression of the main interactors in postsynaptic density (PSD) fractions. We found that TNIK was primarily located in neurons and decreased significantly in epilepsy model rats and TLE patients compared with controls. NCB-0846 delayed kindling progression and decreased seizure severity. Co-IP/MS identified 63 candidate TNIK interactors in rat hippocampi, notably CaMKII. Co-IP showed that TNIK might correlate with endogenous GRIA1, SYN2, PSD-95, CaMKIV, GABRG1, and GABRG2. In addition, the significant decrease in GRIA1 in hippocampal total lysate and PSDs after NCB-0846 treatment might help modify the progression of PTZ kindling. Our results suggest that TNIK contributes to epileptic pathology and is a potential antiepileptic drug target.

Epileptic seizure detection using CHB-MIT dataset: The overlooked perspectives

Epilepsy is a life-threatening neurological condition. Manual detection of epileptic seizures (ES) is laborious and burdensome. Machine learning techniques applied to electroencephalography (EEG) signals are widely used for automatic seizure detection. Some key factors are worth considering for the real-world applicability of such systems: (i) continuous EEG data typically has a higher class imbalance; (ii) higher variability across subjects is present in physiological signals such as EEG; and (iii) seizure event detection is more practical than random segment detection. Most prior studies failed to address these crucial factors altogether for seizure detection. In this study, we intend to investigate a generalized cross-subject seizure event detection system using the continuous EEG signals from the CHB-MIT dataset that considers all these overlooked aspects. A 5-second non-overlapping window is used to extract 92 features from 22 EEG channels; however, the most significant 32 features from each channel are used in experimentation. Seizure classification is done using a Random Forest (RF) classifier for segment detection, followed by a post-processing method used for event detection. Adopting all the above-mentioned essential aspects, the proposed event detection system achieved 72.63% and 75.34% sensitivity for subject-wise 5-fold and leave-one-out analyses, respectively. This study presents the real-world scenario for ES event detectors and furthers the understanding of such detection systems.

Cognitive dysfunction at epilepsy onset as a marker for seizure recurrence

BACKGROUND

Cognitive dysfunction has been correlated with seizure control in chronic epilepsy and in newly diagnosed epilepsy, which potentially makes it a good marker for predicting disease course and seizure control. However, there is a lack of prospective studies examining the role of cognitive dysfunction in predicting seizure recurrence at the earliest stages of the disease, such as following the first unprovoked seizure (UFS) or new onset epilepsy (NOE).

METHODS

Thirty three adult participants (FS=18, NOE=15) from the Halifax First Seizure Clinic (HFSC) completed a cognitive screening assessment at baseline (typically 3 months following diagnosis); seizure-recurrence was evaluated one year after the initial HFSC visit.

RESULTS

Cognitive impairment, defined as at least one z-score in the impaired range (≤-1.5) relative to published test norms, was documented in 76% of the patients with seizure recurrence at follow-up and in 55% without seizure recurrence. Speed/executive functions and Memory were the most frequently affected domains, with impaired performance noted in 35% and 29% of the entire sample, respectively. Although the seizure recurrence vs. non-recurrence groups did not differ significantly on likelihood of impairment in any specific cognitive domains, a regression model of seizure recurrence that included years of education, baseline mood and anxiety scores, normal vs. abnormal baseline MRI, and impaired (vs. unimpaired) function in six cognitive domains was significant overall (Χ2 (10) = 24.04, p =.007*, R2N =.77). The regression model was no longer significant with the cognitive variables removed.

CONCLUSIONS

Subtle cognitive dysfunction, especially in the domains of executive functions and memory are prevalent in individuals at the earliest stages of epilepsy. In addition to abnormal MRI and EEG findings at baseline, which are far less prevalent in FS and NOE, cognitive factors show promise in helping predict seizure recurrence in these populations.

Seizure prediction based on improved vision transformer model for EEG channel optimization

Epileptic seizures are unpredictable events caused by abnormal discharges of a patient's brain cells. Extensive research has been conducted to develop seizure prediction algorithms based on long-term continuous electroencephalogram (EEG) signals. This paper describes a patient-specific seizure prediction method that can serve as a basis for the design of lightweight, wearable and effective seizure-prediction devices. We aim to achieve two objectives using this method. The first aim is to extract robust feature representations from multichannel EEG signals, and the second aim is to reduce the number of channels used for prediction by selecting an optimal set of channels from multichannel EEG signals while ensuring good prediction performance. We design a seizure-prediction algorithm based on a vision transformer (ViT) model. The algorithm selects channels that play a key role in seizure prediction from 22 channels of EEG signals. First, we perform a time-frequency analysis of processed time-series signals to obtain EEG spectrograms. We then segment the spectrograms of multiple channels into many non-overlapping patches of the same size, which are input into the channel selection layer of the proposed model, named Sel-JPM-ViT, enabling it to select channels. Application of the Sel-JPM-ViT model to the Boston Children's Hospital-Massachusetts Institute of Technology scalp EEG dataset yields results using only three to six channels of EEG signals that are slightly better that the results obtained using 22 channels of EEG signals. Overall, the Sel-JPM-ViT model exhibits an average classification accuracy of 93.65%, an average sensitivity of 94.70% and an average specificity of 92.78%.

Effectiveness of Shugan Jieyu capsules for psychiatric symptoms of epilepsy: a systematic review and meta-analysis

BACKGROUND

The relationship between epilepsy and depression is bidirectional. One condition exacerbates the other. However, there are no current guidelines for treating depression in epilepsy patients. In some cases, seizures worsen when antidepressants (AD) are prescribed or when they are discontinued due to adverse events. The Shugan Jieyu capsule, composed of Acanthopanax senticosus and Hypericum perforatum, is a widely used herbal medicine for treating depression. This study aimed to explore the effectiveness and safety of Shugan Jieyu capsules (SJC) in relieving depression in patients with epilepsy.

METHODS

We searched English, Korean, Japanese, and Chinese databases in October 2023 to collect all relevant randomized clinical trials (RCTs). The primary outcomes were the depression scale scores and seizure frequency. The secondary outcomes were quality of life (QoL) and adverse events.

RESULTS

Nine RCTs were included in this meta-analysis. Compared with AD, SJC showed significant differences in the improvement of depression (SMD: 3.82, 95% CI: 3.25, 4.39) and reduction in seizure frequency (MD: 0.39 times/month, 95% CI: 0.28, 0.50). SJC showed more beneficial results than antiepileptic drugs (AED) in terms of antidepressant effects (SMD: 1.10, 95% CI: 0.69, 1.51) and QoL (MD: 11.75, 95% CI: 10.55, 12.95). When patients were prescribed AED, the additional administration of SJC improved depression symptoms (SMD: 0.96, 95% CI: 0.28, 1.63). The SJC treatment group had a lower incidence of side effects than the control group. However, the difference was not statistically significant.

CONCLUSIONS

Our results suggest that SJC may be effective in treating depression in patients with epilepsy. Additionally, SJC has the potential to help reduce seizure frequency in epilepsy patients with depression.

Utility of Chronic Intracranial Electroencephalography in Responsive Neurostimulation Therapy

Responsive neurostimulation (RNS) therapy is an effective treatment for reducing seizures in some patients with focal epilepsy. Utilizing a chronically implanted device, RNS involves monitoring brain activity signals for user-defined patterns of seizure activity and delivering electrical stimulation in response. Devices store chronic data including counts of detected activity patterns and brief recordings of intracranial electroencephalography signals. Data platforms for reviewing stored chronic data retrospectively may be used to evaluate therapy performance and to fine-tune detection and stimulation settings. New frontiers in RNS research can leverage raw chronic data to reverse engineer neurostimulation mechanisms and improve therapy effectiveness.

Economic evaluations of nonpharmacological treatments for drug-resistant epilepsy: A systematic review

This study was undertaken to systematically identify and critically appraise all published full economic evaluations assessing the cost-effectiveness of nonpharmacological interventions for patients with drug-resistant epilepsy. The Population, Intervention, Comparison, Outcome, Study criteria was used to design search strategies for the identification and selection of relevant studies. Literature search was performed using the MEDLINE (via PubMed), Embase, International Health Technology Assessment, National Institute for Health Research Economic Evaluation Database, and Cost-Effectiveness Analysis Registry databases to identify articles published between January 2000 and May 2023. Web of Science was additionally used to perform forward and backward referencing. Title, abstract, and full-text screening was performed by two independent researchers. The Consensus Health Economic Criteria (CHEC) checklist and Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 were applied for quality assessment. A total of 4470 studies were identified, of which 18 met our inclusion criteria. Twelve of the studies conducted model-based economic evaluation, and others were trial-based. Three studies showed that epilepsy surgery was cost-effective in adults, whereas this remained inconclusive for children (two positive, three negative). Three studies showed negative economic outcome for ketogenic diet in children. One of four studies showed positive results for self-management. For vagus nerve stimulation, one study showed positive results in adults and another one negative results in children. One recent study showed cost-effectiveness of responsive neurostimulation (RNS) in adults. Finally, one study showed promising but inconclusive results for deep brain stimulation (DBS). The mean scores for risk of bias assessment (based on CHEC) and for reporting quality (CHEERS 2022) were 95.8% and 80.5%, respectively. This review identified studies that assessed the cost-effectiveness of nonpharmacological treatments in both adults and children with drug-resistant epilepsy, suggesting that in adults, epilepsy surgery, vagus nerve stimulation, and RNS are cost-effective, and that DBS and self-management appear to be promising. In children, the cost-effectiveness of epilepsy surgery remains inconclusive. Finally, the use of ketogenic diet was shown not to be cost-effective. However, limited long-term data were available for newer interventions (i.e., ketogenic diet, DBS, and RNS).

Evaluating the concordance of functional MRI-based language lateralization and Wada testing in epilepsy patients: A single-center analysis

BACKGROUND

For patients with drug-resistant epilepsy, surgery may be effective in controlling their disease. Surgical evaluation may involve localization of the language areas using functional magnetic resonance imaging (fMRI) or Wada testing. We evaluated the accuracy of task-based fMRI versus Wada-based language lateralization in a cohort of our epilepsy patients.

METHODS

In a single-center, retrospective analysis, we identified patients with medically intractable epilepsy who participated in presurgical language mapping (n = 35) with fMRI and Wada testing. Demographic variables and imaging metrics were obtained. We calculated the laterality index (LI) from task-evoked fMRI activation maps across language areas during auditory and reading tasks to determine lateralization. Possible scores for LI range from -1 (strongly left-hemisphere dominant) to 1 (strongly right-hemisphere dominant). Concordance between fMRI and Wada was estimated using Cohen's Kappa coefficient. Association between the LI scores from the auditory and reading tasks was tested using Spearman's rank correlation coefficient.

RESULTS

The fMRI-based laterality indices were concordant with results from Wada testing in 91.4% of patients during the reading task (κ = .55) and 96.9% of patients during the auditory task (κ = .79). The mean LIs for the reading and auditory tasks were -0.52 ± 0.43 and -0.68 ± 0.42, respectively. The LI scores for the language and reading tasks were strongly correlated, r(30) = 0.57 (p = 0.001).

CONCLUSION

Our findings suggest that fMRI is generally an accurate, low-risk alternative to Wada testing for language lateralization. However, when fMRI indicates atypical language lateralization (e.g., bilateral dominance), patients may benefit from subsequent Wada testing or intraoperative language mapping.

Hereditary convulsions in an outbred prairie vole line

Patients with epilepsy are significantly burdened by the disease due to long-term health risks, the severe side effect profiles of anti-epileptic drugs, and the strong possibility of pharmacoresistant refractory seizures. New animal models of epilepsy with unique characteristics promise to further research to address these ongoing problems. Here, we characterize a newly developed line of prairie voles (Microtus ochrogaster, UTol:HIC or "Toledo" line) that presents with a hereditary, adult-onset, handling-induced convulsion phenotype. Toledo voles were bred for four generations and tested to determine whether the observed phenotype was consistent with epileptic seizures. Toledo voles maintained a stable 22 % incidence of convulsions across generations, with an average age of onset of 12-16 weeks. Convulsions in Toledo voles were reliably evoked by rodent seizure screens and were phenotypically consistent with murine seizures. At the colony level, Toledo voles had a 7-fold increase in risk for sudden unexpected death from unknown causes, which parallels sudden unexpected death in epilepsy (SUDEP) in human patients. Finally, convulsions in Toledo voles were reduced or prevented by treatment with the anti-epileptic drug levetiracetam. Taken in combination, these results suggest that convulsions in Toledo voles may be epileptic seizures. The Toledo prairie vole strain may serve as a new rodent model of epilepsy in an undomesticated, outbred species.

Efficacy of cannabidiol in convulsive and nonconvulsive seizure types associated with treatment-resistant epilepsies in the Expanded Access Program

The cannabidiol (CBD) Expanded Access Program (EAP), initiated in 2014, provided CBD (Epidiolex) to patients with treatment-resistant epilepsy (TRE). In the final pooled analysis of 892 patients treated through January 2019 (median exposure = 694 days), CBD treatment was associated with a 46%-66% reduction in median monthly total (convulsive plus nonconvulsive) seizure frequency. CBD was well tolerated, and adverse events were consistent with previous findings. We used pooled EAP data to investigate the effectiveness of add-on CBD therapy for individual convulsive seizure types (clonic, tonic, tonic-clonic, atonic, focal to bilateral tonic-clonic), nonconvulsive seizure types (focal with and without impaired consciousness, absence [typical and atypical], myoclonic, myoclonic absence), and epileptic spasms. CBD treatment was associated with a reduction in the frequency of convulsive seizure types (median percentage reduction = 47%-100%), and nonconvulsive seizure types and epileptic spasms (median percentage reduction = 50%-100%) across visit intervals through 144 weeks of treatment. Approximately 50% of patients had ≥50% reduction in convulsive and nonconvulsive seizure types and epileptic spasms at nearly all intervals. These results show a favorable effect of long-term CBD use in patients with TRE, who may experience various convulsive and nonconvulsive seizure types. Future controlled trials are needed to confirm these findings.

Localized proteomic differences in the choroid plexus of Alzheimer's disease and epilepsy patients

Introduction

Alzheimer's disease (AD) and epilepsy are reciprocally related. Among sporadic AD patients, clinical seizures occur in 10-22% and subclinical epileptiform abnormalities occur in 22-54%. Cognitive deficits, especially short-term memory impairments, occur in most epilepsy patients. Common neurophysiological and molecular mechanisms occur in AD and epilepsy. The choroid plexus undergoes pathological changes in aging, AD, and epilepsy, including decreased CSF turnover, amyloid beta (Aβ), and tau accumulation due to impaired clearance and disrupted CSF amino acid homeostasis. This pathology may contribute to synaptic dysfunction in AD and epilepsy.

Methods

We evaluated control (n = 8), severe AD (n = 8; A3, B3, C3 neuropathology), and epilepsy autopsy cases (n = 12) using laser capture microdissection (LCM) followed by label-free quantitative mass spectrometry on the choroid plexus adjacent to the hippocampus at the lateral geniculate nucleus level.

Results

Proteomics identified 2,459 proteins in the choroid plexus. At a 5% false discovery rate (FDR), 616 proteins were differentially expressed in AD vs. control, 1 protein in epilepsy vs. control, and 438 proteins in AD vs. epilepsy. There was more variability in the epilepsy group across syndromes. The top 20 signaling pathways associated with differentially expressed proteins in AD vs. control included cell metabolism pathways; activated fatty acid beta-oxidation (p = 2.00 x 10^-7, z = 3.00), and inhibited glycolysis (p = 1.00 x 10^-12, z = -3.46). For AD vs. epilepsy, the altered pathways included cell metabolism pathways, activated complement system (p = 5.62 x 10^-5, z = 2.00), and pathogen-induced cytokine storm (p = 2.19 x 10^-2, z = 3.61). Of the 617 altered proteins in AD and epilepsy vs. controls, 497 (81%) were positively correlated (p < 0.0001, R² = 0.27).

Discussion

We found altered signaling pathways in the choroid plexus of severe AD cases and many correlated changes in the protein expression of cell metabolism pathways in AD and epilepsy cases. The shared molecular mechanisms should be investigated further to distinguish primary pathogenic changes from the secondary ones. These mechanisms could inform novel therapeutic strategies to prevent disease progression or restore normal function. A focus on dual-diagnosed AD/epilepsy cases, specific epilepsy syndromes, such as temporal lobe epilepsy, and changes across different severity levels in AD and epilepsy would add to our understanding.

Tolerability and Effectiveness of Cathodal Transcranial Direct Current Stimulation in Children with Refractory Epilepsy: A Case Series

There are limited treatment options for drug-resistant epilepsy (DRE) in children. We performed a pilot study to investigate the tolerability and effectiveness of cathodal transcranial direct current stimulation (tDCS) in DRE. Twelve children with DRE of varied etiology underwent three to four daily sessions of cathodal tDCS. The seizure frequency at 2 weeks before and after tDCS was obtained from seizure diaries; clinic reviews at 3 and 6 months assessed any longer-term benefits or adverse effects. The spike wave index (SWI) was analyzed in the EEGs done immediately before and after tDCS on the first and last day of tDCS. One child remained seizure free for a year after tDCS. One child had reduced frequency of ICU admissions for status epilepticus for 2 weeks, likely due to reduced severity of seizures. In four children, an improvement in alertness and mood was reported for 2-4 weeks after tDCS. There was no benefit following tDCS in the other children. There were no unexpected or serious adverse effects in any child. Benefit was seen in two children, and the reasons for the lack of benefit in the other children need further study. It is likely that tDCS stimulus parameters will need to be tailored for different epilepsy syndromes and etiologies.

Ketogenic diet in children and adolescents: The effects on growth and nutritional status

The ketogenic diet is known to be a possible adjuvant treatment in several medical conditions, such as in patients with severe or drug-resistant forms of epilepsy. Its use has recently been increasing among adolescents and young adults due to its supposed weight-loss effect, mediated by lipolysis and lowered insulin levels. However, there are still no precise indications on the possible use of ketogenic diets in pediatric age for weight loss. This approach has also recently been proposed for other types of disorder such as inherited metabolic disorders, Prader-Willi syndrome, and some specific types of cancers. Due to its unbalanced ratio of lipids, carbohydrates and proteins, a clinical evaluation of possible side effects with a strict evaluation of growth and nutritional status is essential in all patients following a long-term restrictive diet such as the ketogenic one. The prophylactic use of micronutrients supplementation should be considered before starting any ketogenic diet. Lastly, while there is sufficient literature on possible short-term side effects of ketogenic diets, their possible long-term impact on growth and nutritional status is not yet fully understood, especially when started in pediatric age.

Animal Models of Drug-Resistant Epilepsy as Tools for Deciphering the Cellular and Molecular Mechanisms of Pharmacoresistance and Discovering More Effective Treatments

In the last 30 years, over 20 new anti-seizure medicines (ASMs) have been introduced into the market for the treatment of epilepsy using well-established preclinical seizure and epilepsy models. Despite this success, approximately 20-30% of patients with epilepsy have drug-resistant epilepsy (DRE). The current approach to ASM discovery for DRE relies largely on drug testing in various preclinical model systems that display varying degrees of ASM drug resistance. In recent years, attempts have been made to include more etiologically relevant models in the preclinical evaluation of a new investigational drug. Such models have played an important role in advancing a greater understanding of DRE at a mechanistic level and for hypothesis testing as new experimental evidence becomes available. This review provides a critical discussion of the pharmacology of models of adult focal epilepsy that allow for the selection of ASM responders and nonresponders and those models that display a pharmacoresistance per se to two or more ASMs. In addition, the pharmacology of animal models of major genetic epilepsies is discussed. Importantly, in addition to testing chemical compounds, several of the models discussed here can be used to evaluate other potential therapies for epilepsy such as neurostimulation, dietary treatments, gene therapy, or cell transplantation. This review also discusses the challenges associated with identifying novel therapies in the absence of a greater understanding of the mechanisms that contribute to DRE. Finally, this review discusses the lessons learned from the profile of the recently approved highly efficacious and broad-spectrum ASM cenobamate.

Predicting epileptic seizures based on EEG signals using spatial depth features of a 3D-2D hybrid CNN

Epilepsy is a recurrent chronic brain disease that affects nearly 75 million people around the world. Therefore, the ability to reliably predict epileptic seizures would be instrumental for implementing interventions to reduce brain injury and improve patients' quality of life. In addition to classical machine learning algorithms and feature engineering methods, the use of electroencephalography (EEG) to predict seizures has gradually become a mainstream trend. Here, we propose a patient-specific method to predict epileptic seizures based on EEG data acquired using spatial depth features of a three-dimensional-two-dimensional hybrid convolutional neural network (3D-2D HyCNN) model. This method facilitates the acquisition of abundant and reliable deep features from multi-channel EEG signals. We first developed a reliable data preprocessing method to reconstruct time-series EEG signals into 3D feature images. Then, the 3D-2D HyCNN model was used to extract correlation features between multiple channels of EEG signals, which are automatically exploited by the network to improve seizure prediction. The method achieved accuracy of 98.43% and 93.11%, sensitivity of 98.58% and 90.98%, and specificity of 96.86% and 92.39% on the CHB-MIT Scalp EEG dataset and the American Epilepsy Society Epilepsy Prediction Challenge dataset, respectively. The results revealed that the new algorithm is reliable. Graphical Abstract A new patient-specific epilepsy prediction approach.

Medial Pulvinar Stimulation in Temporal Lobe Epilepsy: A Literature Review and a Hypothesis Based on Neuroanatomical Findings

While bilateral stimulation of the anterior thalamic nuclei remains the only approved deep brain stimulation (DBS) option for focal epilepsy, two additional thalamic targets have been proposed. Earlier work indicated the potential of centromedian thalamic nucleus stimulation with recent findings highlighting the medial pulvinar nucleus. The latter has been shown to exhibit electrophysiological and imaging alterations in patients with partial status epilepticus and temporal lobe epilepsy. On this basis, recent studies have begun assessing the feasibility and efficacy of pulvinar stimulation, with encouraging results on the reduction of seizure frequency and severity. Building on existing neuroanatomical knowledge, indicating that the medial pulvinar is connected to the temporal lobe via the temporopulvinar bundle of Arnold, we hypothesize that this is one of the routes through which medial pulvinar stimulation affects temporal lobe structures. We suggest that further anatomic, imaging, and electrophysiologic studies are warranted to deepen our understanding of the subject and guide future clinical applications.

Nrf2 is predominantly expressed in hippocampal neurons in a rat model of temporal lobe epilepsy

BACKGROUND

Drug resistance is a particular problem in patients with temporal lobe epilepsy, where seizures originate mainly from the hippocampus. Many of these epilepsies are acquired conditions following an insult to the brain such as a prolonged seizure. Such conditions are characterized by pathophysiological mechanisms including massive oxidative stress that synergistically mediate the secondary brain damage, contributing to the development of epilepsy. The transcription factor nuclear factor (erythroid-derived 2)-like 2 (Nrf2) has emerged in recent years as an attractive therapeutic approach targeting to upregulate the antioxidative defenses in the cell, to ameliorate the oxidative stress-induced damage. Thus, it is important to understand the characteristics of Nrf2 activation during epileptogenesis and epilepsy. Here, we studied the temporal, regional, and cell-type specific expression of Nrf2 in the brain, in a rat model of temporal lobe epilepsy.

RESULTS

Early after status-epilepticus, Nrf2 is mainly activated in the hippocampus and maintained during the whole period of epileptogenesis. Only transient expression of Nrf2 was observed in the cortex. Nevertheless, the expression of several Nrf2 antioxidant target genes was increased within 24 h after status-epilepticus in both the cortex and the hippocampus. We demonstrated that after status-epilepticus in rats, Nrf2 is predominantly expressed in neurons in the CA1 and CA3 regions of the hippocampus, and only astrocytes in the CA1 increase their Nrf2 expression.

CONCLUSIONS

In conclusion, our data identify previously unrecognized spatial and cell-type dependent activation of Nrf2 during epilepsy development, highlighting the need for a time-controlled, and cell-type specific activation of the Nrf2 pathway for mediating anti-oxidant response after brain insult, to modify the development of epilepsy.

Gut dysbiosis following organophosphate, diisopropylfluorophosphate (DFP), intoxication and saracatinib oral administration

Organophosphate nerve agents (OPNAs) act as irreversible inhibitors of acetylcholinesterase and can lead to cholinergic crisis including salivation, lacrimation, urination, defecation, gastrointestinal distress, respiratory distress, and seizures. Although the OPNAs have been studied in the past few decades, little is known about the impact on the gut microbiome which has become of increasing interest across fields. In this study, we challenged animals with the OPNA, diisopropylfluorophosphate (DFP, 4mg/kg, s.c.) followed immediately by 2mg/kg atropine sulfate (i.m.) and 25mg/kg 2-pralidoxime (i.m.) and 30 minutes later by 3mg/kg midazolam (i.m.). One hour after midazolam, animals were treated with a dosing regimen of saracatinib (SAR, 20mg/kg, oral), a src family kinase inhibitor, to mitigate DFP-induced neurotoxicity. We collected fecal samples 48 hours, 7 days, and 5 weeks post DFP intoxication. 16S rRNA genes (V4) were amplified to identify the bacterial composition. At 48 hours, a significant increase in the abundance of Proteobacteria and decrease in the abundance of Firmicutes were observed in DFP treated animals. At 7 days there was a significant reduction in Firmicutes and Actinobacteria, but a significant increase in Bacteroidetes in the DFP groups compared to controls. The taxonomic changes at 5 weeks were negligible. There was no impact of SAR administration on microbial composition. There was a significant DFP-induced reduction in alpha diversity at 48 hours but not at 7 days and 5 weeks. There appeared to be an impact of DFP on beta diversity at 48 hours and 7 days but not at 5 weeks. In conclusion, acute doses of DFP lead to short-term gut dysbiosis and SAR had no effect. Understanding the role of gut dysbiosis in long-term toxicity may reveal therapeutic targets.

Online survey of medicinal cannabis users: Qualitative analysis of patient-level data

Aim: To characterize perceived benefits and challenges experienced by medicinal cannabis users.

Methods: An anonymous online survey collected demographics, health information, and open-ended responses from medicinal cannabis users regarding perceptions, motivations, and experience of treatment. Qualitative open-ended responses were thematically analyzed.

Results: Respondents (N = 808) were predominantly White (79%), female (63%), with a mean (SD) age of 38 (20). Two hundred eighty-four (35%) respondents provided data on a dependent family member (e.g., child; 22% of total sample). Most used cannabidiol (CBD)-dominant products (58%), primarily for neurological disorders (38%) or pain (25%). Primary motivations for medicinal cannabis use were based on beliefs that traditional treatments were ineffective and/or had intolerable side effects (51%), positive scientific or media portrayals of the safety/efficacy of cannabis as a therapeutic (29%), or preference for “natural” treatments over pharmaceuticals (21%). A majority of respondents (77%) attributed positive effects to the medicinal use of cannabis/cannabinoids. These included physical symptom improvements such as reduced pain (28%), improved sleep (18%), and seizure reduction (18%), and mental health improvements including reduced anxiety (22%) and improved mood (11%). Additionally, respondents reported reduced use of other medications (e.g., opioids) (12%), and improved quality of life (14%). Problems associated with use were cited by 41% of respondents, and included unwanted side effects (16%), lack of information or medical support (16%), prohibitive costs (12%), and legal concerns (10%).

Conclusion: Most participants reported benefits from cannabis use for a variety of conditions where traditional treatments were ineffective or unacceptable. Concerns regarding cannabis side effects, legality, lack of information, and cost were raised. Data indicate greater research and education on the safety and efficacy of medicinal cannabis/cannabinoid use is warranted.

A sparse representation strategy to eliminate pseudo-HFO events from intracranial EEG for seizure onset zone localization

Objective.High-frequency oscillations (HFOs) are considered a biomarker of the epileptogenic zone in intracranial EEG recordings. However, automated HFO detectors confound true oscillations with spurious events caused by the presence of artifacts.Approach.We hypothesized that, unlike pseudo-HFOs with sharp transients or arbitrary shapes, real HFOs have a signal characteristic that can be represented using a small number of oscillatory bases. Based on this hypothesis using a sparse representation framework, this study introduces a new classification approach to distinguish true HFOs from the pseudo-events that mislead seizure onset zone (SOZ) localization. Moreover, we further classified the HFOs into ripples and fast ripples by introducing an adaptive reconstruction scheme using sparse representation. By visualizing the raw waveforms and time-frequency representation of events recorded from 16 patients, three experts labeled 6400 candidate events that passed an initial amplitude-threshold-based HFO detector. We formed a redundant analytical multiscale dictionary built from smooth oscillatory Gabor atoms and represented each event with orthogonal matching pursuit by using a small number of dictionary elements. We used the approximation error and residual signal at each iteration to extract features that can distinguish the HFOs from any type of artifact regardless of their corresponding source. We validated our model on sixteen subjects with thirty minutes of continuous interictal intracranial EEG recording from each.Main results.We showed that the accuracy of SOZ detection after applying our method was significantly improved. In particular, we achieved a 96.65% classification accuracy in labeled events and a 17.57% improvement in SOZ detection on continuous data. Our sparse representation framework can also distinguish between ripples and fast ripples.Significance.We show that by using a sparse representation approach we can remove the pseudo-HFOs from the pool of events and improve the reliability of detected HFOs in large data sets and minimize manual artifact elimination.

Implanting intracranial electrodes does not affect spikes or network connectivity in nearby or connected brain regions

To determine the effect of implanting electrodes on electrographic features of nearby and connected brain regions in patients with drug-resistant epilepsy, we analyzed intracranial EEG recordings from 10 patients with drug-resistant epilepsy who underwent implant revision (placement of additional electrodes) during their hospitalization. We performed automated spike detection and measured EEG functional networks. We analyzed the original electrodes that remained in place throughout the full EEG recording, and we measured the change in spike rates and network connectivity in these original electrodes in response to implanting new electrodes. There was no change in overall spike rate pre- to post-implant revision (t(9) = 0.1, p = 0.95). The peri-revision change in the distribution of spike rate and connectivity across electrodes was no greater than chance (Monte Carlo method, spikes: p = 0.40, connectivity: p = 0.42). Electrodes closer to or more functionally connected to the revision site had no greater change in spike rate or connectivity than more distant or less connected electrodes. Changes in electrographic features surrounding electrode implantation are no greater than baseline fluctuations occurring throughout the intracranial recording. These findings argue against an implant effect on spikes or network connectivity in nearby or connected brain regions.

Multi-Channel Vision Transformer for Epileptic Seizure Prediction

Epilepsy is a neurological disorder that causes recurrent seizures and sometimes loss of awareness. Around 30% of epileptic patients continue to have seizures despite taking anti-seizure medication. The ability to predict the future occurrence of seizures would enable the patients to take precautions against probable injuries and administer timely treatment to abort or control impending seizures. In this study, we introduce a Transformer-based approach called Multi-channel Vision Transformer (MViT) for automated and simultaneous learning of the spatio-temporal-spectral features in multi-channel EEG data. Continuous wavelet transform, a simple yet efficient pre-processing approach, is first used for turning the time-series EEG signals into image-like time-frequency representations named Scalograms. Each scalogram is split into a sequence of fixed-size non-overlapping patches, which are then fed as inputs to the MViT for EEG classification. Extensive experiments on three benchmark EEG datasets demonstrate the superiority of the proposed MViT algorithm over the state-of-the-art seizure prediction methods, achieving an average prediction sensitivity of 99.80% for surface EEG and 90.28-91.15% for invasive EEG data.

Characterization of Cortical Glial Scars in the Diisopropylfluorophosphate (DFP) Rat Model of Epilepsy

Glial scars have been observed following stab lesions in the spinal cord and brain but not observed and characterized in chemoconvulsant-induced epilepsy models. Epilepsy is a disorder characterized by spontaneous recurrent seizures and can be modeled in rodents. Diisopropylfluorophosphate (DFP) exposure, like other real-world organophosphate nerve agents (OPNAs) used in chemical warfare scenarios, can lead to the development of status epilepticus (SE). We have previously demonstrated that DFP-induced SE promotes epileptogenesis which is characterized by the development of spontaneous recurrent seizures (SRS), gliosis, and neurodegeneration. In this study, we report classical glial scars developed in the piriform cortex, but not in the hippocampus, by 8 days post-exposure. We challenged both male and female rats with 4–5 mg/kg DFP (s.c.) followed immediately by 2 mg/kg atropine sulfate (i.m.) and 25 mg/kg pralidoxime (i.m.) and one hour later by midazolam (i.m). Glial scars were present in the piriform cortex/amygdala region in 73% of the DFP treated animals. No scars were found in controls. Scars were characterized by a massive clustering of reactive microglia surrounded by hypertrophic reactive astrocytes. The core of the scars was filled with a significant increase of IBA1 and CD68 positive cells and a significant reduction in NeuN positive cells compared to the periphery of the scars. There was a significantly higher density of reactive GFAP, complement 3 (C3), and inducible nitric oxide synthase (iNOS) positive cells at the periphery of the scar compared to similar areas in controls. We found a significant increase in chondroitin sulfate proteoglycans (CS-56) in the periphery of the scars compared to a similar region in control brains. However, there was no change in TGF-β1 or TGF-β2 positive cells in or around the scars in DFP-exposed animals compared to controls. In contrast to stab-induced scars, we did not find fibroblasts (Thy1.1) in the scar core or periphery. There were sex differences with respect to the density of iNOS, CD68, NeuN, GFAP, C3 and CS-56 positive cells. This is the first report of cortical glial scars in rodents with systemic chemoconvulsant-induced SE. Further investigation could help to elucidate the mechanisms of scar development and mitigation strategies.

Persistence of neural function in animals submitted to seizure-suppressing scale-free nonperiodic electrical stimulation applied to the amygdala

Based on the rationale that neural hypersynchronization underlies epileptic phenomena, nonperiodic stimulation (NPS) was designed and successfully tested as an electrical stimulus with robust anticonvulsant action. Considering the scale-free temporal structure of NPS mimics natural-like activity, here we hypothesized its application to the amygdala would induce minor to none impairment of neural function in treated animals. Wistar rats underwent gold-standard behavioral tests such as open field (OF), elevated plus-maze (EPM), novel object recognition, and social interaction test in order to evaluate the functions of base-level anxiety, motor function, episodic memory, and sociability. We also performed daily (8 days, 6 h per day) electrophysiological recordings (local field potential/LFP and electromyography) to assess global forebrain dynamics and the sleep-wake cycle architecture and integrity. All animals displayed an increased proportion of time exploring new objects, spent more time in the closed arms of the EPM and in the periphery of the OF arena, with similar numbers of crossing between quadrants and no significant changes of social behaviors. In the sleep-wake cycle electrophysiology experiments, we found no differences regarding duration and proportion of sleep stages and the number of transitions between stages. Finally, the power spectrum of LFP recordings and neurodynamics were also unaltered. We concluded that NPS did not impair neural functions evaluated and thus, it may be safe for clinical studies. Additionally, results corroborate the notion that NPS may exert an on-demand only desynchronization effect by efficiently competing with epileptiform activity for the physiological and healthy recruitment of neural circuitry. Considering the very dynamical nature of circuit activation and functional activity underlying neural function in general (including cognition, processing of emotion, memory acquisition, and sensorimotor integration) and its corruption leading to disorder, such mechanism of action may have important implications in the investigation of neuropsychological phenomena and also in the development of rehabilitation neurotechnology.

Automated seizure activity tracking and onset zone localization from scalp EEG using deep neural networks

We propose a novel neural network architecture, SZTrack, to detect and track the spatio-temporal propagation of seizure activity in multichannel EEG. SZTrack combines a convolutional neural network encoder operating on individual EEG channels with recurrent neural networks to capture the evolution of seizure activity. Our unique training strategy aggregates individual electrode level predictions for patient-level seizure detection and localization. We evaluate SZTrack on a clinical EEG dataset of 201 seizure recordings from 34 epilepsy patients acquired at the Johns Hopkins Hospital. Our network achieves similar seizure detection performance to state-of-the-art methods and provides valuable localization information that has not previously been demonstrated in the literature. We also show the cross-site generalization capabilities of SZTrack on a dataset of 53 seizure recordings from 14 epilepsy patients acquired at the University of Wisconsin Madison. SZTrack is able to determine the lobe and hemisphere of origin in nearly all of these new patients without retraining the network. To our knowledge, SZTrack is the first end-to-end seizure tracking network using scalp EEG.

A Novel method of seizure onset zone localization by serial Tc-99 m ECD brain perfusion SPECT clearance patterns

In this prospective study, we postulate that there is a difference between clearance of [99mTc]Tc- ethyl cysteinate dimer (ECD) in the seizure onset zone (SOZ) and other brain areas and thus SOZ localization by clearance patterns might become a potential novel method for SOZ localization in epilepsy. The parametric images of brain ECD clearance were generated by linear regression model analysis from serial brain SPECT scans from 30 to 240 min after ECD injection (7-times point) in 7 patients with drug-resistant epilepsy and 3 normal volunteers. Clearance patterns of the SOZ confirmed by good surgical outcome or consensus with other investigations were analyzed quantitatively and semi-quantitatively by visual grading (slower or faster washout than contralateral brain regions). The average [^99mTc]Tc-ECD clearance rates of SOZs were + 1.08% ± 2.57%/hr (wash in), -7.02% ± 2.56%/hr (washout), and -5.37% ± 1.71%/hr (washout) in ictal, aura and interictal states, respectively. Paired t-tests between the SOZ and contralateral regions showed statistically significant difference (p = 0.039 in interictal state). Clearance patterns that can define the SOZs were 1) wash in and slow washout on ictal slope, 2) fast washout on aura slope and interictal slope with 100% (6/6), 100% (2/2) and 75% (6/8) localization using ictal, aura, and interictal slope maps, respectively. Our study provided the evidence that clearance pattern methods are potential additive diagnostic tools for SOZ localization when routine one-time point SPECT are unable to define the SOZ.

Activation of Calcium-Activated Chloride Channels Suppresses Inherited Seizure Susceptibility in Genetically Epilepsy-Prone Rats

Inherited seizure susceptibility in genetically epilepsy-prone rats (GEPR-3s) is associated with increased voltage-gated calcium channel currents suggesting a massive calcium influx resulting in increased levels of intraneuronal calcium. Cytosolic calcium, in turn, activates many processes, including chloride channels, to restore normal membrane excitability and limit repetitive firing of the neurons. Here we used EACT and T16Ainh-A01, potent activator and inhibitor of calcium-activated channels transmembrane protein 16A (TMEM16A), respectively, to probe the role of these channels in the pathophysiology of acoustically evoked seizures in the GEPR-3s. We used adult male and female GEPR-3s. Acoustically evoked seizures consisted of wild running seizures (WRSs) that evolved into generalized tonic-clonic seizures (GTCSs) and eventually culminated into forelimb extension (partial tonic seizures). We found that acute EACT treatment at relatively higher tested doses significantly reduced the incidences of WRSs and GTCSs, and the seizure severity in male GEPR-3s. Furthermore, these antiseizure effects were associated with delayed seizure onset and reduced seizure duration. Interestingly, the inhibition of TMEM16A channels reversed EACT’s antiseizure effects on seizure latency and seizure duration. No notable antiseizure effects were observed in female GEPR-3s. Together, these findings suggest that activation of TMEM16A channels may represent a putative novel cellular mechanism for suppressing GTCSs.

Automatic annotation correction for wearable EEG based epileptic seizure detection

OBJECTIVE

Video-electroencephalography (vEEG), which defines the ground truth for the detection of epileptic seizures, is inadequate for long-term home monitoring. Thanks to their advantages in comfort and unobtrusiveness, wearable EEG devices have been suggested as a solution for home monitoring. However, one of the challenges in data-driven automated seizure detection with wearable EEG data is to have reliable seizure annotations. Seizure annotations on the gold-standard 25-channel vEEG recordings may not be optimal to delineate seizure activity on the concomitantly recorded wearable EEG, due to artifacts or absence of ictal activity on the limited set of electrodes of the wearable EEG. This paper aims to develop an automatic approach to correct the imperfect annotations of seizure activity on wearable EEG, which can be used to train seizure detection algorithms.

APPROACH

This paper first investigates the effectiveness of correcting the seizure annotations for the training set with a visual annotation correction. Then a novel approach has been proposed to automatically remove non-seizure data from wearable EEG in epochs annotated as seizures in gold-standard video-EEG recordings. The performance of the automatic annotation correction approach was evaluated by comparing the seizure detection models trained with 1. original vEEG seizure annotations, 2. visually corrected seizure annotations, and 3. automatically corrected seizure annotations.

RESULTS

The automatic seizure detection approach trained with automatically corrected seizure annotations was more sensitive and had fewer false-positive detections compared to the approach trained with visually corrected seizure annotations, and the approach trained with the original seizure annotations from gold-standard vEEG.

SIGNIFICANCE

The wearable EEG seizure detection approach performs better when trained with automatic seizure annotation correction.

Mobile Applications for Epilepsy: Where Are We? Where Should We Go? A Systematic Review

The development of mobile health for epilepsy has grown in the last years, bringing new applications (apps) to the market and improving already existing ones. In this systematic review, we analyse the scope of mobile apps for seizure detection and epilepsy self-management, with two research questions in mind: what are the characteristics of current solutions and do they meet users’ requirements? What should be considered when designing mobile health for epilepsy? We used PRISMA methodology to search within App Store and Google Play Store from February to April of 2021, reaching 55 potential apps. A more thorough analysis regarding particular features was performed on 26 of those apps. The content of these apps was evaluated in five categories, regarding if there was personalisable content; features related to medication management; what aspects of seizure log were present; what type of communication prevailed; and if there was any content related to seizure alarm or seizure action plans. Moreover, the 26 apps were evaluated through using MARS by six raters, including two neurologists. The analysis of MARS categories was performed for the top and bottom apps, to understand the core differences. Overall, the lowest MARS scores were related to engagement and information, which play a big part in long-term use, and previous studies raised the concern of assuring continuous use, especially in younger audiences. With that in mind, we identified conceptual improvement points, which were divided in three main topics: customisation, simplicity and healthcare connection. Moreover, we summarised some ideas to improve m-health apps catered around long-term adherence. We hope this work contributes to a better understanding of the current scope in mobile epilepsy management, endorsing healthcare professionals and developers to provide off-the-shelf solutions that engage patients and allows them to better manage their condition.

Physicians' perspectives on adverse drug reactions in pediatric routine care: a survey

BACKGROUND

Children and adolescents are at particular risk for adverse drug reactions (ADRs). We investigated physicians' perceptions on ADRs in pediatric routine care.

METHODS

In this exploratory study from April to November 2020, we invited physicians treating pediatric patients across Germany to complete an online questionnaire consisting mainly of closed questions.

RESULTS

Completion rate was 98% (127/129). Of all participants, 23% (29/127) stated they were not able to estimate how many of their pediatric patients experienced ADRs during drug therapy. The remaining physicians estimated that 7.5% (median; Q25/Q75 3%/20%) of their pediatric patients were affected by ADRs. Regarding counseling on ADRs, 61% (77/127) stated they do not ask regularly the extent to which parents want to be informed. In total, 26% (33/127) stated they avoid counseling on ADRs concerning commonly used approved therapies, whereas only 4% (5/127) did so concerning off-label use (P < 0.001). Altogether, 16% (20/127) stated they rather prescribe new medicines as they hope for better effectiveness; 72% (91/127) said they are cautious about doing so owing to yet unknown ADRs. Of all respondents, 46% (58/127) stated they do not report ADRs to the authorities. Concerning the black triangle symbol, a European pharmacovigilance measure, 11% (14/127) stated they knew it and 6% (7/127) stated they reported any suspected ADR for drugs with that symbol.

CONCLUSIONS

Physicians' perspectives on ADRs were ambivalent: ADRs influenced their parent counseling and drug prescribing; yet, they struggled to estimate the impact of ADRs on their patients and were not aware of specific pharmacovigilance measures.

Temporal Lobectomy: Does It Worsen or Improve Presurgical Psychiatric Disorders?

Temporal lobe epilepsy (TLE) is the type of epilepsy most frequently associated with psychiatric morbidity. Respective surgery for focal epilepsy remains the preferred treatment for medically resistant epilepsy. The aim of this chapter is to review what happens with psychiatric disorders once patients have undergone surgery.Early studies demonstrated a post-surgical increase in the incidence rates of anxiety and depressive disorders, while recent studies found that the prevalence of depression and anxiety decreased 12 months after surgery. In spite of this improvement, de novo anxiety and depressive or psychotic cases can be seen. In particular, de novo psychosis ranges from 1% to 14%, with risk factors including bilateral temporal damage, tumors rather than mesial temporal sclerosis, and seizures emerging after surgery again.Personality changes after temporal lobectomy are yet to be established, but decline in schizotypal behavior and neuroticism is the most replicated so far.In children's studies surgery resolved 16% of the participants' psychiatric problems, while 12% presented a de novo psychiatric diagnosis, but further, more conclusive results are needed.The main limitations of these studies are the inconsistent systematic post-surgical psychiatric evaluations, the small sample sizes of case series, the short follow-up post-surgical periods, and the small number of controlled studies.A psychiatric assessment should be conducted before surgery, and most of all, patients with a psychiatric history should be followed after surgery.

An Automatic Method for Epileptic Seizure Detection Based on Deep Metric Learning

Electroencephalography (EEG) is a commonly used clinical approach for the diagnosis of epilepsy which is a life-threatening neurological disorder. Many algorithms have been proposed for the automatic detection of epileptic seizures using traditional machine learning and deep learning. Although deep learning methods have achieved great success in many fields, their performance in EEG analysis and classification is still limited mainly due to the relatively small sizes of available datasets. In this paper, we propose an automatic method for the detection of epileptic seizures based on deep metric learning which is a novel strategy tackling the few-shot problem by mitigating the demand for massive data. First, two one-dimensional convolutional embedding modules are proposed as a deep feature extractor, for single-channel and multichannel EEG signals respectively. Then, a deep metric learning model is detailed along with a stage-wise training strategy. Experiments are conducted on the publicly-available Bonn University dataset which is a benchmark dataset, and the CHB-MIT dataset which is larger and more realistic. Impressive averaged accuracy of 98.60% and specificity of 100% are achieved on the most difficult classification of interictal (subset D) vs ictal (subset E) of the Bonn dataset. On the CHB-MIT dataset, an averaged accuracy of 86.68% and specificity of 93.71% are reached. With the proposed method, automatic and accurate detection of seizures can be performed in real time, and the heavy burden of neurologists can be effectively reduced.

Clinical Efficacy and Safety of Lacosamide as an Adjunctive Treatment in Adults With Refractory Epilepsy

Background: Lacosamide (LCM), a novel AED (antiepileptic drug), was used as an adjunctive treatment in patients with partial-onset seizures or without secondary generalization. However, no meta-analysis was performed to evaluate the efficacy of LCM as an adjunctive treatment in post-marketing clinical studies.

Aims: To assess the safety and efficacy of LCM as an adjunctive treatment in adults with refractory epilepsy, a systematic review and meta-analysis of randomized controlled trials (RCTs) and real-world studies were performed.

Methods: All studies were identified from electronic databases. Both RCTs and observational prospective studies were included. Primary outcomes included responder rate, adverse effects (AEs) and withdraw rate. The pooled rates (PR) with their corresponding 95% confidence intervals (CI) were calculated. Publication bias was assessed with Begg's or Egger's tests.

Results: Total 16 studies (3,191 patients) including 5 RCTs and 11 real-word studies were enrolled. The pooled 50% responder rate and seizure-free rate were 48% (95% CI: 0.42, 0.54) and 9% (95% CI: 0.06, 0.11) in all studies, respectively. Subgroup analysis showed that the pooled 50% responder rate were 53% (95% CI: 0.44, 0.62) from observational studies and 38% (95% CI: 0.35, 0.42) from RCTs, respectively; the pooled seizure-free rate were 13% (95% CI: 0.09, 0.18) from observational studies and 4% (95% CI: 0.06, 0.11) from RCTs, respectively. Similar incidence of AEs were reported in real-world studies (0.57, 95% CI: 0.43, 0.72) and RCTs (0.59, 95% CI: 0.42–0.76). Finally, a total of 13% (95%CI: 0.09, 0.16) and 13% (95% CI: 0.08, 0.16) of all patients prescribed with LCM was withdrawn in RCTs and real-world studies, respectively, due to the occurrence of AEs. Furthermore, similar to the 50% responder rate, seizure-free rate, incidence of AEs and withdraw rate were reported at 6-month or at least 12-month of LCM adjunction. Publication bias was not detected in these studies.

Conclusions: Our results revealed that LCM adjunctive therapy even with long-term treatment was efficacious and well tolerated in adults with refractory epilepsy.

Altered expression of DENND5B in patients with epilepsy and its regulation of seizures in mice

Epilepsy is a high incidence neurological disease, and its repeated attacks cause serious physical and psychological damage to the patient. Differentially expressed in normal and neoplastic cells (DENN) domain containing 5B (DENND5B) is a lipoprotein binding protein that mediates synaptic vesicle transport and regulates neuroplasticity and lipid metabolism. Nevertheless, the effect of DENND5B on seizures remains unclear. We aimed to investigate the association of DENND5B with epilepsy, detect its expression and distribution in the nervous system, and explore its role in epileptogenesis through western blot, immunofluorescence staining, and behavioral studies. In this experiment, two C57BL/6 mice models, which induced seizures by pentylenetetrazole and kainic acid, were established. We observed that the expression of DENND5B was reduced in the brains of patients with temporal lobe epilepsy, and its expression was also similarly decreased in both chronic epileptic mice. The findings strongly suggest that DENND5B may be associated with epileptic seizures. Results of immunofluorescence showed that DENND5B was mainly expressed in the hippocampal region and co-located with neurons but not with astrocytes. Next, we used lentivirus to induce both lentiviral vector-mediated overexpression and knockdown of DENND5B in mice to test the change of susceptibility and severity of seizures in the two chronic seizure models. Knockdown of DENND5B was found to promote epileptic seizures, increase chronic spontaneous recurrent epileptic seizures and epileptic discharge, and reduce the incubation period. However, overexpression of DENND5B showed the opposite effect. These results suggest that DENND5B overexpression decreased the behavioral phenotype of epileptic seizures, but DENND5B downregulation had the opposite effect. In summary, our findings suggest that DENND5B can regulate epileptic seizures and may provide a new target for antiepileptic therapy.