Discovering Neurophysiological Characteristics of Pathological High-Frequency Oscillations in Epilepsy with an Explainable Deep Generative Model.

Interictal high-frequency oscillation (HFO) is a promising biomarker of the epileptogenic zone (EZ). However, objective definitions to distinguish between pathological and physiological HFOs have remained elusive, impeding HFOs' clinical applications. We employed self-supervised deep generative variational autoencoders to learn such discriminative HFO features directly from their morphologies in a data-driven manner. We studied a large retrospective cohort of 185 patients who underwent intracranial monitoring and analyzed 686,410 candidate HFO events collected from 18,265 brain contacts across diverse brain regions. The model automatically clustered HFOs into distinct morphological groups in the latent space. One cluster consisted of putative morphologically defined pathological HFOs (mpHFOs): HFOs in that cluster were observed to be associated with spikes and exhibited high signal intensity both in the HFO band (>80 Hz) at detection and in the sub-HFO band (10-80 Hz) surrounding the detection and were primarily localized in the seizure onset zone (SOZ). Moreover, resection of brain regions based on a higher prevalence of interictal mpHFOs better predicted postoperative seizure outcomes than current clinical standards based on SOZ removal. Our self-supervised, explainable, deep generative model distills pathological HFOs and thus potentially helps delineate the EZ purely from interictal intracranial EEG data.

Outcome of emergency neurosurgery in patients with refractory and super-refractory status epilepticus: a systematic review and individual participant data meta-analysis.

Background: Refractory (RSE) and super-refractory status epilepticus (SRSE) are serious neurological conditions requiring aggressive management. Beyond anesthetic agents, there is a lack of evidence guiding management in these patients. This systematic review and individual participant data meta-analysis (IPDMA) seeks to evaluate and compare the currently available surgical techniques for the acute treatment of RSE and SRSE. Methods: A systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Individual Participant Data (PRISMA-IPD). Only patients who underwent surgery while in RSE and SRSE were included. Descriptive statistics were used to compare various subgroups. Multivariable logistic regression models were constructed to identify predictors of status epilepticus (SE) cessation, long-term overall seizure freedom, and favorable functional outcome (i.e., modified Rankin score of 0-2) at last follow-up. Results: A total of 87 studies including 161 participants were included. Resective surgery tended to achieve better SE cessation rate (93.9%) compared to non-resective techniques (83.9%), but this did not reach significance (p = 0.071). Resective techniques were also more likely to achieve seizure freedom (69.1% vs. 34.4%, p = <0.0001). Older age at SE (OR = 1.384[1.046-1.832], p = 0.023) was associated with increased likelihood of SE cessation, while longer duration of SE (OR = 0.603[0.362-1.003], p = 0.051) and new-onset seizures (OR = 0.244[0.069-0.860], p = 0.028) were associated with lower likelihood of SE cessation, but this did not reach significance for SE duration. Only shorter duration of SE prior to surgery (OR = 1.675[1.168-2.404], p = 0.0060) and immediate termination of SE (OR = 3.736 [1.323-10.548], p = 0.014) were independently associated with long-term seizure status. Rates of favorable functional outcomes (mRS of 0-2) were comparable between resective (44.4%) and non-resective (44.1%) techniques, and no independent predictors of outcome were identified. Conclusion: Our findings suggest that emergency neurosurgery may be a safe and effective alternative in patients with RSE/SRSE and may be considered earlier during the disease course. However, the current literature is limited exclusively to small case series and case reports with high risk of publication bias. Larger clinical trials assessing long-term seizure and functional outcomes are warranted to establish robust management guidelines.

Bilateral centromedian nucleus of thalamus responsive neurostimulation for pediatric-onset drug-resistant epilepsy.

Neuromodulation therapies offer an efficacious treatment alternative for patients with drug-resistant epilepsy (DRE), particularly those unlikely to benefit from surgical resection. Here we present our retrospective single-center case series of patients with pediatric-onset DRE who underwent responsive neurostimulation (RNS) depth electrode implantation targeting the bilateral centromedian nucleus (CM) of the thalamus between October 2020 and October 2022. Sixteen patients were identified; seizure outcomes, programming parameters, and complications at follow-up were reviewed. The median age at implantation was 13 years (range 3.6-22). Six patients (38%) were younger than 12 years of age at the time of implantation. Ictal electroencephalography (EEG) patterns during patients' most disabling seizures were reliably detected. Ten patients (62%) achieved 50% or greater reduction in seizure frequency at a median 1.3 years (range 0.6-2.6) of follow-up. Eight patients (50%) experienced sensorimotor side effects, and three patients (19%) had superficial pocket infection, prompting the removal of the RNS device. Side effects of stimulation were experienced mostly in monopolar-cathodal configuration and alleviated with programming change to bipolar configuration or low-frequency stimulation. Closed-loop neurostimulation using RNS targeting bilateral CM is a feasible and useful therapy for patients with pediatric-onset DRE.

Decoding imagined speech with delay differential analysis.

Speech decoding from non-invasive EEG signals can achieve relatively high accuracy (70-80%) for strictly delimited classification tasks, but for more complex tasks non-invasive speech decoding typically yields a 20-50% classification accuracy. However, decoder generalization, or how well algorithms perform objectively across datasets, is complicated by the small size and heterogeneity of existing EEG datasets. Furthermore, the limited availability of open access code hampers a comparison between methods. This study explores the application of a novel non-linear method for signal processing, delay differential analysis (DDA), to speech decoding. We provide a systematic evaluation of its performance on two public imagined speech decoding datasets relative to all publicly available deep learning methods. The results support DDA as a compelling alternative or complementary approach to deep learning methods for speech decoding. DDA is a fast and efficient time-domain open-source method that fits data using only few strong features and does not require extensive preprocessing.

PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application.

Objective. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.Approach. We introduced PyHFO, which enables time-efficient high-frequency oscillation (HFO) detection algorithms like short-term energy and Montreal Neurological Institute and Hospital detectors. It incorporates DL models for artifact and HFO with spike classification, designed to operate efficiently on standard computer hardware.Main results. The validation of PyHFO was conducted on three separate datasets: the first comprised solely of grid/strip electrodes, the second a combination of grid/strip and depth electrodes, and the third derived from rodent studies, which sampled the neocortex and hippocampus using depth electrodes. PyHFO demonstrated an ability to handle datasets efficiently, with optimization techniques enabling it to achieve speeds up to 50 times faster than traditional HFO detection applications. Users have the flexibility to employ our pre-trained DL model or use their EEG data for custom model training.Significance. PyHFO successfully bridges the computational challenge faced in applying DL techniques to EEG data analysis in epilepsy studies, presenting a feasible solution for both clinical and research settings. By offering a user-friendly and computationally efficient platform, PyHFO paves the way for broader adoption of advanced EEG data analysis tools in clinical practice and fosters potential for large-scale research collaborations.

Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset.

OBJECTIVE: Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. METHODS: We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset. RESULTS: In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. SIGNIFICANCE: It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

Outcomes following surgical interventions for hypothalamic hamartomas: protocol for a systematic review and individual patient data meta-analysis.

INTRODUCTION: Hypothalamic hamartomas (HHs) are deep-seated congenital lesions that typically lead to pharmacoresistant epilepsy and a catastrophic encephalopathic syndrome characterised by severe neuropsychological impairment and decline in quality of life. A variety of surgical approaches and technologies are available for the treatment of HH-related pharmacoresistant epilepsy. There remains, however, a paucity of literature directly comparing their relative efficacy and safety. This protocol aims to facilitate a systematic review and meta-analysis that will characterise and compare the probability of seizure freedom and relevant postoperative complications across different surgical techniques performed for the treatment of HH-related pharmacoresistant epilepsy. METHODS AND ANALYSIS: This protocol was developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Individual Participant Data guidelines. Three major databases, PubMed, Embase and Scopus, will be systematically searched from database inception and without language restrictions for relevant articles using our predefined search strategy. Title-abstract and full text screening using inclusion and exclusion criteria created a priori will be performed by two independent reviewers to identify eligible articles. Conflicts will be resolved via discussion with a third team member. Following data extraction of both study-level and individual patient data (IPD), a study-level and IPD meta-analysis will be performed. Study-level analysis will focus on assessing the degree of heterogeneity in the data and quantifying overall seizure outcomes for each surgical technique. The IPD analysis will use multivariable regression to determine perioperative predictors of seizure freedom and complications that can guide patient and technique selection. ETHICS AND DISSEMINATION: This work will not require ethics approval as it will be solely based on previously published and available data. The results of this review will be shared via conference presentation and submission to peer-reviewed neurosurgical journals. PROSPERO REGISTRATION: CRD42022378876.

Functional magnetic resonance imaging (fMRI) as adjunct for planning laser interstitial thermal therapy (LITT) near eloquent structures.

LITT is a minimally-invasive laser ablation technique used to treat a wide variety of intracranial lesions. Difficulties performing intraoperative mapping have limited its adoption for lesions in/near eloquent regions. In this institutional case series, we demonstrate the utility of fMRI-adjunct planning for LITT near language or motor areas. Six out of 7 patients proceeded with LITT after fMRI-based tractography determined adequate safety margins for ablation. All underwent successful ablation without new or worsening postoperative symptoms requiring adjuvant corticosteroids, including those with preexisting deficits. fMRI is an easily accessible adjunct which may potentially reduce chances of complications in LITT near eloquent structures.

Hemimegalencephaly: A Systematic Comparison of Functional and Anatomic Hemispherectomy for Drug-Resistant Epilepsy.

BACKGROUND AND OBJECTIVES: Hemimegalencephaly (HME) is a rare diffuse malformation of cortical development characterized by unihemispheric hypertrophy, drug-resistant epilepsy (DRE), hemiparesis, and developmental delay. Definitive treatment for HME-related DRE is hemispheric surgery through either anatomic (AH) or functional hemispherectomy (FH). This individual patient data meta-analysis assessed seizure outcomes of AH and FH for HME with pharmacoresistant epilepsy, predictors of Engel I, and efficacy of different FH approaches. METHODS: PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature were searched from inception to Jan 13th, 2023, for primary literature reporting seizure outcomes in >3 patients with HME receiving AH or FH. Demographics, neurophysiology findings, and Engel outcome at the last follow-up were extracted. Postsurgical seizure outcomes were compared through 2-tailed t -test and Fisher exact test. Univariate and multivariate Cox regression analyses were performed to identify independent predictors of Engel I outcome. RESULTS: Data from 145 patients were extracted from 26 studies, of which 89 underwent FH (22 vertical, 33 lateral), 47 underwent AH, and 9 received an unspecified hemispherectomy with a median last follow-up of 44.0 months (FH cohort) and 45.0 months (AH cohort). Cohorts were similar in preoperative characteristics and at the last follow-up; 77% (n = 66) of the FH cohort and 81% (n = 38) and of the AH cohort were Engel I. On multivariate analysis, only the presence of bilateral ictal electroencephalography abnormalities (hazard ratio = 11.5; P = .002) was significantly associated with faster time-to-seizure recurrence. A number-needed-to-treat analysis to prevent 1 additional case of posthemispherectomy hydrocephalus reveals that FH, compared with AH, was 3. There was no statistical significance for any differences in time-to-seizure recurrence between lateral and vertical FH approaches (hazard ratio = 2.59; P = .101). CONCLUSION: We show that hemispheric surgery is a highly effective treatment for HME-related DRE. Unilateral ictal electroencephalography changes and using the FH approach as initial surgical management may result in better outcomes due to significantly lower posthemispherectomy hydrocephalus probability. However, larger HME registries are needed to further delineate the predictors of seizure outcomes.

Global trends and decision-making in the management of arachnoid cysts.

OBJECTIVE: In pediatric patients, middle cranial fossa (MCF) arachnoid cysts are often discovered incidentally on imaging in asymptomatic patients during workup for other indications. This study aims to describe current management gestalt and threshold for surgical intervention by surveying an international cohort of neurosurgeons. METHODS: A web-based survey was circulated via email list of attendants of the 2019 Canadian Pediatric Neurosurgery Study Group (CPNSG) and International Society of Pediatric Neurosurgery (ISPN) mailing list. The survey consisted of 8 clinical scenarios involving patients with MCF arachnoid cysts. Demographic variables of respondents and their decisions regarding management for each scenario were analyzed using R computing software. RESULTS: A total of 107 respondents were included. Cysts in asymptomatic patients (92%), younger age at diagnosis (81%), and presence of a mild learning delay were predominantly managed non-surgically (80.7 ± 9.4%). Patients with cyst enlargement, headaches, new seizures, or hemorrhage were divided between non-surgical (55.8 ± 3.3%) and surgical (44.2 ± 2.9%) management. Patients with contralateral hemiparesis were treated predominantly surgically (67%). For both Galassi I and II, papilledema was favored as the primary indication for surgical intervention in 54% of patients. Those inclined to surgery (n = 17) were more likely to practice and train outside North America compared to those not pro-surgical (adjusted P = 0.092). CONCLUSION: Incidental MCF arachnoid cysts in asymptomatic patients and younger age of diagnosis are predominantly managed non-surgically. Mild learning delay was not considered an indication to intervene. In contrast, radiological progression, hemorrhagic evolution, or non-focal neurological deficits lead to uncertainty in management, while focal neurological deficits and papilledema with MCF cysts were favored to be intervened surgically. Among the provider level factors, only location of training and practice trended towards a pro-surgery approach.

Hemispheric epilepsy surgery for hemimegalencephaly: The UCLA experience.

OBJECTIVES: Hemimegalencephaly (HME) is a rare congenital brain malformation presenting predominantly with drug-resistant epilepsy. Hemispheric disconnective surgery is the mainstay of treatment; however, little is known about how postoperative outcomes compare across techniques. Thus we present the largest single-center cohort of patients with HME who underwent epilepsy surgery and characterize outcomes. METHODS: This observational study included patients with HME at University of California Los Angeles (UCLA) from 1984 to 2021. Patients were stratified by surgical intervention: anatomic hemispherectomy (AH), functional hemispherectomy (FH), or less-than-hemispheric resection (LTH). Seizure freedom, functional outcomes, and operative complications were compared across surgical approaches. Regression analysis identified clinical and intraoperative variables that predict seizure outcomes. RESULTS: Of 56 patients, 43 (77%) underwent FH, 8 (14%) underwent AH, 2 (4%) underwent LTH, 1 (2%) underwent unknown hemispherectomy type, and 2 (4%) were managed non-operatively. At median last follow-up of 55 months (interquartile range [IQR] 20-92 months), 24 patients (49%) were seizure-free, 17 (30%) required cerebrospinal fluid (CSF) shunting for hydrocephalus, 9 of 43 (21%) had severe developmental delay, 8 of 38 (21%) were non-verbal, and 15 of 38 (39%) were non-ambulatory. There was one (2%) intraoperative mortality due to exsanguination earlier in this cohort. Of 12 patients (29%) requiring revision surgery, 6 (50%) were seizure-free postoperatively. AH, compared to FH, was not associated with statistically significant improved seizure freedom (hazard ratio [HR] = .48, p = .328), although initial AH trended toward greater odds of seizure freedom (75% vs 46%, p = .272). Younger age at seizure onset (HR = .29, p = .029), lack of epilepsia partialis continua (EPC) (HR = .30, p = .022), and no contralateral seizures on electroencephalography (EEG) (HR = .33, p = .039) independently predicted longer duration of seizure freedom. SIGNIFICANCE: This study helps inform physicians and parents of children who are undergoing surgery for HME by demonstrating that earlier age at seizure onset, absence of EPC, and no contralateral EEG seizures were associated with longer postoperative seizure freedom. At our center, initial AH for HME may provide greater odds of seizure freedom with complications and functional outcomes comparable to those of FH.

Structural connections of the centromedian nucleus of thalamus and their relevance for neuromodulation in generalized drug-resistant epilepsy: insight from a tractography study.

Background: Epilepsy is a widespread neurologic disorder and almost one-third of patients suffer from drug-resistant epilepsy (DRE). Neuromodulation targeting the centromediannucleus of the thalamus (CM) has been showing promising results for patients with generalized DRE who are not surgical candidates. Recently, the effect of CM- deep brain stimulation (DBS) in DRE patients was investigated in the Electrical Stimulation of Thalamus for Epilepsy of Lennox-Gastaut phenotype (ESTEL) trial, a monocentric randomized-controlled study. The same authors described a 'cold-spot' and a 'sweet-spot', which are defined as the volume of stimulation in the thalamus yielding the least and the best clinical response, respectively. However, it remains unclear which structural connections may contribute to the anti-seizure effect of the stimulation. Objective: We investigated the differences in structural connectivity among CM, the sweet-spot and the cold-spot. Furthermore, we tried to validate our results in a cohort of DRE patients who underwent CM-DBS or CM-RNS (responsive neurostimulation). We hypothesized that the sweet-spot would share similar structural connectivity with responder patients. Methods: By using the software FMRIB Software Library (FSL), probabilistic tractography was performed on 100 subjects from the Human Connectome Project to calculate the probability of connectivity of the whole CM, the sweet-spot and the cold-spot to 45 cortical and subcortical areas. Results among the three seeds were compared with multivariate analysis of variance (MANOVA). Similarly, the structural connectivity of volumes of tissue activated (VTAs) from eight DRE patients was investigated. Patients were divided into responders and non-responders based on the degree of reduction in seizure frequency, and the mean probabilities of connectivity were similarly compared between the two groups. Results: The sweet-spot demonstrated a significantly higher probability of connectivity (p < 0.001) with the precentral gyrus, superior frontal gyrus, and the cerebellum than the whole CM and the cold-spot. Responder patients displayed a higher probability of connectivity with both ipsilateral (p = 0.011) and contralateral cerebellum (p = 0.04) than the non-responders. Conclusion: Cerebellar connections seem to contribute to the beneficial effects of CM-neuromodulation in patients with drug-resistant generalized epilepsy.

Added value of corpus callosotomy following vagus nerve stimulation in children with Lennox-Gastaut syndrome: A multicenter, multinational study.

OBJECTIVE: Lennox-Gastaut syndrome (LGS) is a severe form of epileptic encephalopathy, presenting during the first years of life, and is very resistant to treatment. Once medical therapy has failed, palliative surgeries such as vagus nerve stimulation (VNS) or corpus callosotomy (CC) are considered. Although CC is more effective than VNS as the primary neurosurgical treatment for LGS-associated drop attacks, there are limited data regarding the added value of CC following VNS. This study aimed to assess the effectiveness of CC preceded by VNS. METHODS: This multinational, multicenter retrospective study focuses on LGS children who underwent CC before the age of 18 years, following prior VNS, which failed to achieve satisfactory seizure control. Collected data included epilepsy characteristics, surgical details, epilepsy outcomes, and complications. The primary outcome of this study was a 50% reduction in drop attacks. RESULTS: A total of 127 cases were reviewed (80 males). The median age at epilepsy onset was 6 months (interquartile range [IQR] = 3.12-22.75). The median age at VNS surgery was 7 years (IQR = 4-10), and CC was performed at a median age of 11 years (IQR = 8.76-15). The dominant seizure type was drop attacks (tonic or atonic) in 102 patients. Eighty-six patients underwent a single-stage complete CC, and 41 an anterior callosotomy. Ten patients who did not initially have a complete CC underwent a second surgery for completion of CC due to seizure persistence. Overall, there was at least a 50% reduction in drop attacks and other seizures in 83% and 60%, respectively. Permanent morbidity occurred in 1.5%, with no mortality. SIGNIFICANCE: CC is vital in seizure control in children with LGS in whom VNS has failed. Surgical risks are low. A complete CC has a tendency toward better effectiveness than anterior CC for some seizure types.

Machine learning models for predicting seizure outcome after MR-guided laser interstitial thermal therapy in children.

OBJECTIVE: MR-guided laser interstitial thermal therapy (MRgLITT) is associated with lower seizure-free outcome but better safety profile compared to open surgery. However, the predictors of seizure freedom following MRgLITT remain uncertain. This study aimed to use machine learning to predict seizure-free outcome following MRgLITT and to identify important predictors of seizure freedom in children with drug-resistant epilepsy. METHODS: This multicenter study included children treated with MRgLITT for drug-resistant epilepsy at 13 epilepsy centers. The authors used clinical data, diagnostic investigations, and ablation features to predict seizure-free outcome at 1 year post-MRgLITT. Patients from 12 centers formed the training cohort, and patients in the remaining center formed the testing cohort. Five machine learning algorithms were developed on the training data by using 10-fold cross-validation, and model performance was measured on the testing cohort. The models were developed and tested on the complete feature set. Subsequently, 3 feature selection methods were used to identify important predictors. The authors then assessed performance of the parsimonious models based on these important variables. RESULTS: This study included 268 patients who underwent MRgLITT, of whom 44.4% had achieved seizure freedom at 1 year post-MRgLITT. A gradient-boosting machine algorithm using the complete feature set yielded the highest area under the curve (AUC) on the testing set (AUC 0.67 [95% CI 0.50-0.82], sensitivity 0.71 [95% CI 0.47-0.88], and specificity 0.66 [95% CI 0.50-0.81]). Logistic regression, random forest, support vector machine, and neural network yielded lower AUCs (0.58-0.63) compared to the gradient-boosting machine but the findings were not statistically significant (all p > 0.05). The 3 feature selection methods identified video-EEG concordance, lesion size, preoperative seizure frequency, and number of antiseizure medications as good prognostic features for predicting seizure freedom. The parsimonious models based on important features identified by univariate feature selection slightly improved model performance compared to the complete feature set. CONCLUSIONS: Understanding the predictors of seizure freedom after MRgLITT will assist with prognostication.

Uncovering Spatiotemporal Dynamics of the Corticothalamic Network during Seizures.

Objective: Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human EEG recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. Methods: We analyzed ten patients (aged 2.7-28.1) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic coverage. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM). Results: In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. Interpretation: It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network during seizures, and this knowledge could guide personalized neuromodulation treatment strategies.

Characteristics of ictal thalamic EEG in pediatric-onset neocortical focal epilepsy.

OBJECTIVE: To characterize ictal EEG change in the centromedian (CM) and anterior nucleus (AN) of the thalamus, using stereoelectroencephalography (SEEG) recordings. METHODS: Forty habitual seizures were analyzed in nine patients with pediatric-onset neocortical drug-resistant epilepsy who underwent SEEG (age 2-25 y) with thalamic coverage. Both visual and quantitative analysis was used to evaluate ictal EEG signal in the cortex and thalamus. The amplitude and cortico-thalamic latencies of broadband frequencies at ictal onset were measured. RESULTS: Visual analysis demonstrated consistent detection of ictal EEG changes in both the CM nucleus and AN nucleus with latency to thalamic ictal EEG changes of less than 400 ms in 95% of seizures, with low-voltage fast activity being the most common ictal pattern. Quantitative broadband amplitude analysis showed consistent power changes across the frequency bands, corresponding to ictal EEG onset, while while ictal EEG latency was variable from -18.0 seconds to 13.2 seconds. There was no significant difference between detection of CM and AN ictal activity on visual or amplitude analysis. Four patients with subsequent thalamic responsive neurostimulation (RNS) demonstrated ictal EEG changes consistent with SEEG findings. CONCLUSIONS: Ictal EEG changes were consistently seen at the CM and AN of the thalamus during neocortical seizures. SIGNIFICANCE: It may be feasible to use a closed-loop system in the thalamus to detect and modulate seizure activity for neocortical epilepsy.

Optimizing detection and deep learning-based classification of pathological high-frequency oscillations in epilepsy.

OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery. METHODS: We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for spike association and time-frequency plot characteristics. A deep learning (DL)-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method. RESULTS: The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors had the highest spike association rate. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification. CONCLUSIONS: HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs. SIGNIFICANCE: Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

Characteristics of ictal thalamic EEG in pediatric-onset neocortical focal epilepsy.

Objective: To characterize ictal EEG change in the centromedian (CM) and anterior nucleus (AN) of the thalamus, using stereoelectroencephalography (SEEG) recordings. Methods: Forty habitual seizures were analyzed in nine patients with pediatric-onset neocortical drug-resistant epilepsy who underwent SEEG (age 2-25 y) with thalamic coverage. Both visual and quantitative analysis was used to evaluate ictal EEG signal in the cortex and thalamus. The amplitude and cortico-thalamic latencies of broadband frequencies at ictal onset were measured. Results: Visual analysis demonstrated consistent detection of ictal EEG changes in both the CM nucleus and AN nucleus with latency to thalamic ictal EEG changes of less than 400ms in 95% of seizures, with low-voltage fast activity being the most common ictal pattern. Quantitative broadband amplitude analysis showed consistent power changes across the frequency bands, corresponding to ictal EEG onset, while while ictal EEG latency was variable from -18.0 seconds to 13.2 seconds. There was no significant difference between detection of CM and AN ictal activity on visual or amplitude analysis. Four patients with subsequent thalamic responsive neurostimulation (RNS) demonstrated ictal EEG changes consistent with SEEG findings. Conclusions: Ictal EEG changes were consistently seen at the CM and AN of the thalamus during neocortical seizures. Significance: It may be feasible to use a closed-loop system in the thalamus to detect and modulate seizure activity for neocortical epilepsy.

Hyaline protoplasmic astrocytopathy in epilepsy.

Hyaline protoplasmic astrocytopathy (HPA) describes a rare histologic finding of eosinophilic, hyaline cytoplasmic inclusions in astrocytes, predominantly in the cerebral cortex. It has mainly been observed in children and adults with a history of developmental delay and epilepsy, frequently with focal cortical dysplasia (FCD), but the nature and significance of these inclusions are unclear. In this study, we review the clinical and pathologic features of HPA and characterize the inclusions and brain tissue in which they are seen in surgical resection specimens from five patients with intractable epilepsy and HPA compared to five patients with intractable epilepsy without HPA using immunohistochemistry for filamin A, previously shown to label these inclusions, and a variety of astrocytic markers including aldehyde dehydrogenase 1 family member L1 (ALDH1L1), SRY-Box Transcription Factor 9 (SOX9), and glutamate transporter 1/excitatory amino acid transporter 2 (GLT-1/EAAT2) proteins. The inclusions were positive for ALDH1L1 with increased ALDH1L1 expression in areas of gliosis. SOX9 was also positive in the inclusions, although to a lesser intensity than the astrocyte nuclei. Filamin A labeled the inclusions but also labeled reactive astrocytes in a subset of patients. The immunoreactivity of the inclusions for various astrocytic markers and filamin A as well as the positivity of filamin A in reactive astrocytes raise the possibility that these astrocytic inclusions may be the result of an uncommon reactive or degenerative phenomenon.