Time-Frequency Fingerprint Analysis in SEEG Source-Space to Identify the Epileptogenic Zone.

This case study highlights the application of seizure fingerprint analysis in the source-space of stereo-EEG (SEEG) data to accurately localize the epileptogenic zone (EZ) in patients with complex cortical malformations. A 25-year-old female with extensive bilateral perisylvian polymicrogyria (PMG) presented with intractable focal seizures. The source-level analysis performed in Brainstorm using the sLORETA imaging algorithm subsequently showed EZ fingerprint analysis.

Respiratory modulation of heart rate variability after generalized convulsive seizures.

Background: Autonomic function is modulated by the respiratory network. We therefore hypothesized that in persons with epilepsy (PWE), generalized convulsive seizures (GCS) would induce greater heart rate variability (HRV) and parasympathetic activation in patients with low interictal central CO chemosensitivity (measured with the hypercapnic ventilatory response, HCVR). We further hypothesized that postictal HRV would be associated with severity of postictal hypercapnia and hypoxemia.

Leveraging GPT-4o for Automated Extraction of Neural Projections from Scientific Literature.

Sudden Unexpected Death in Epilepsy (SUDEP) is a major cause of death for epilepsy patients having uncontrolled seizures. Understanding the complex neural circuits within the central nervous system is crucial for understanding the mechanisms underlying cardiorespiratory regulation, particularly in the context of SUDEP. This study explores the potential of GPT-4o, a cutting-edge language model, to automate the extraction of neural projections from scientific literature.

A Web-based Interface for Visualizing and Documenting SEEG Strategic Planning (WISP): Development and Qualitative Evaluation.

WISP stands as an efficacious solution to the challenges associated with Stereoelectroencephalography (SEEG) strategic planning, offering lightweight and interactive web interfaces for rendering multiple brain views. These interfaces facilitate collaborative engagement among care team members across various disciplines during patient case conferences and SEEG strategic planning sessions. Moreover, WISP incorporates a collaborative electrode and electrode group library, serving as a standardized repository of knowledge.

Ontology accelerates few-shot learning capability of large language model: A study in extraction of drug efficacy in a rare pediatric epilepsy.

Objective: Dravet Syndrome (DS) is a developmental and epileptic encephalopathy that is characterized by severe, prolonged motor seizures and high resistance to multiple antiseizure medications (ASMs) with multiple comorbidities. Evaluating the efficacy of new drugs in DS preclinical models and mapping them to human phenotypes of DS through analysis of published literature is an important goal for improving outcomes in this rare pediatric epilepsy.

Materials And Methods: Large language models (LLM) have demonstrated great promise in parsing published literature; however, the performance of LLMs falls short in medical applications.

Leveraging pretrained language models for seizure frequency extraction from epilepsy evaluation reports.

Seizure frequency is essential for evaluating epilepsy treatment, ensuring patient safety, and reducing risk for Sudden Unexpected Death in Epilepsy. As this information is often described in clinical narratives, this study presents an approach to extracting structured seizure frequency details from such unstructured text. We investigated two tasks: (1) extracting phrases describing seizure frequency, and (2) extracting seizure frequency attributes.

Involved but not essential: cognitive activity in periventricular nodules and neuropsychological outcomes following their ablation.

Objective: Periventricular nodular heterotopia (PVNH) is a malformation of cortical development with high rates of epilepsy. The extent to which nodules participate in normal cerebral functions in addition to pathological processes is unclear. The authors assessed the functional utility (i.

Long-Term Seizure Reduction Associated with Vagal Nerve Stimulation in Dravet Syndrome.

variants cause a range of epilepsy syndromes, including Dravet syndrome, leading to early cognitive and functional impairment. Despite advances in medical management, drug-resistant epilepsy remains common. Vagal nerve stimulation (VNS) has been suggested reducing seizure frequency in these patients but there is a lack of long-term follow-up, quantitative analysis that corrected for confounding factors such as antiseizure medications (ASMs) and the impact of VNS settings on response.

Laser Ablation of Periventricular Nodular Heterotopia for Medically Refractory Epilepsy.

Objective: Periventricular nodular heterotopia (PVNH) is the most common neuronal heterotopia, frequently resulting in pharmaco-resistant epilepsy. Here, we characterize variables that predict good epilepsy outcomes following surgical intervention using stereo-electroencephalography (SEEG) -informed magnetic resonance-guided laser interstitial thermal therapy (MRgLITT).

Methods: A retrospective review of consecutive cases from a single high-volume epilepsy referral center identified patients who underwent SEEG evaluation for PVNH to characterize the intervention and outcomes.

Brain gray matter changes in children at risk for sudden unexpected death in epilepsy.

Background: Potential failing adult brain sites, stratified by risk, mediating Sudden Unexpected Death in Epilepsy (SUDEP) have been described, but are unknown in children.

Methods: We examined regional brain volumes using T1-weighted MRI images in 21 children with epilepsy at high SUDEP risk and 62 healthy children, together with SUDEP risk scores, calculated from focal seizure frequency. Gray matter tissue type was partitioned, maps normalized, smoothed, and compared between groups (SPM12; ANCOVA; covariates, age, sex, and BMI).

Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

Objective: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy.

Methods: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors.

Leveraging logical definitions and lexical features to detect missing IS-A relations in biomedical terminologies.

Biomedical terminologies play a vital role in managing biomedical data. Missing IS-A relations in a biomedical terminology could be detrimental to its downstream usages. In this paper, we investigate an approach combining logical definitions and lexical features to discover missing IS-A relations in two biomedical terminologies: SNOMED CT and the National Cancer Institute (NCI) thesaurus.

Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

Objective: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy.

Personalization of SUDEP risk: A survey of transient subclinical comorbid changes.

Objective: Preclinical data report within subject modifiable ailments emerge weeks prior to SUDEP, including sleep disorders and cardiorespiratory changes; findings which support anecdotal clinical data. Here, we bridge preclinical findings with future clinical/preclinical studies, and survey whether caretakers or family members of victims noticed transient changes prior to SUDEP. The aim of this pilot study is to identify potential modifiable changes that may synergistically increase SUDEP risk for future research.

Stimulation-induced respiratory enhancement in corticothalamic regions.

Objective: We aimed to identify corticothalamic areas and electrical stimulation paradigms that optimally enhance breathing.

Methods: Twenty-nine patients with medically intractable epilepsy were prospectively recruited in an epilepsy monitoring unit while undergoing stereoelectroencephalographic evaluation. Direct electrical stimulation in cortical and thalamic regions was carried out using low (<1 Hz) and high (≥10 Hz) frequencies, and low (<5 mA) and high (≥5 mA) current intensities, with pulse width of .

Volumetric and microstructural abnormalities of the amygdala in focal epilepsy with varied levels of SUDEP risk.

Although the mechanisms of sudden unexpected death in epilepsy (SUDEP) are not yet well understood, generalised- or focal-to-bilateral tonic-clonic seizures (TCS) are a major risk factor. Previous studies highlighted alterations in structures linked to cardio-respiratory regulation; one structure, the amygdala, was enlarged in people at high risk of SUDEP and those who subsequently died. We investigated volume changes and the microstructure of the amygdala in people with epilepsy at varied risk for SUDEP since that structure can play a key role in triggering apnea and mediating blood pressure.

Volumetric and microstructural abnormalities of the amygdala in focal epilepsy with varied levels of SUDEP risk.

Although the mechanisms of sudden unexpected death in epilepsy (SUDEP) are not yet well understood, generalised- or focal-to-bilateral tonic-clonic seizures (TCS) are a major risk factor. Previous studies highlighted alterations in structures linked to cardio-respiratory regulation; one structure, the amygdala, was enlarged in people at high risk of SUDEP and those who subsequently died. We investigated volume changes and the microstructure of the amygdala in people with epilepsy at varied risk for SUDEP since that structure can play a key role in triggering apnea and mediating blood pressure.

Subject-Specific Activation of Central Respiratory Centers during Breath-Holding Functional Magnetic Resonance Imaging.

Background: Voluntary breath-holding (BH) triggers responses from central neural control and respiratory centers in order to restore breathing. Such responses can be observed using functional MRI (fMRI).

Objectives: We used this paradigm in healthy volunteers with the view to develop a biomarker that could be used to investigate disorders of the central control of breathing at the individual patient level.

A hybrid unsupervised and supervised learning approach for postictal generalized EEG suppression detection.

Sudden unexpected death of epilepsy (SUDEP) is a catastrophic and fatal complication of epilepsy and is the primary cause of mortality in those who have uncontrolled seizures. While several multifactorial processes have been implicated including cardiac, respiratory, autonomic dysfunction leading to arrhythmia, hypoxia, and cessation of cerebral and brainstem function, the mechanisms underlying SUDEP are not completely understood. Postictal generalized electroencephalogram (EEG) suppression (PGES) is a potential risk marker for SUDEP, as studies have shown that prolonged PGES was significantly associated with a higher risk of SUDEP.

Safety and efficacy of bihemispheric sampling via transmidline stereoelectroencephalography.

Objective: Stereoelectroencephalography (SEEG) is designed to target distributed cortical networks responsible for electroclinical seizure syndrome and to enable localization of the site of seizure onset in patients with intractable epilepsy. When the preimplantation hypothesis invokes the bilateral mesial frontal lobes, sampling of several deep-seated cortical sites in both hemispheres is required. In this study, the authors have demonstrated the feasibility of sampling bihemispheric areas with intentional implantation of an SEEG electrode crossing the midline (SECM) for sampling the cortex on both sides of the interhemispheric fissure.

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records.

Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care.

Regional variation in brain tissue texture in patients with tonic-clonic seizures.

Patients with epilepsy, who later succumb to sudden unexpected death, show altered brain tissue volumes in selected regions. It is unclear whether the alterations in brain tissue volume represent changes in neurons or glial properties, since volumetric procedures have limited sensitivity to assess the source of volume changes (e.g.

A multimodal clinical data resource for personalized risk assessment of sudden unexpected death in epilepsy.

Epilepsy affects ~2-3 million individuals in the United States, a third of whom have uncontrolled seizures. Sudden unexpected death in epilepsy (SUDEP) is a catastrophic and fatal complication of poorly controlled epilepsy and is the primary cause of mortality in such patients. Despite its huge public health impact, with a ~1/1,000 incidence rate in persons with epilepsy, it is an uncommon enough phenomenon to require multi-center efforts for well-powered studies.