Active clinical trials for "Epilepsy"

The researchers hope to explore the etiological distribution and influencing factors of KCNQ2-related neonatal convulsions or refractory epileptic encephalopathy, and to improve the level of assessment, identification, intervention and shunt of KCNQ2-related convulsions. To formulate countermeasures and measures for prevention, management and health education.

Drug-resistant partial epilepsies are disabling diseases for which surgical treatment may be indicated. The determination of the area to be operated (or 'epileptogenic zone') is based on a bundle of clinical arguments and neuroimaging, having a direct impact on surgical success. Epileptic patients have electrical abnormalities that can be detected with surface electrophysiological examinations such as surface EEG or MagnetoEncephalography (MEG). The intracerebral source of these abnormalities can be localized in the brain using source modeling techniques from MEG signals or EEG signals if a sufficient number of electrodes is used (> 100, so-called high EEG technique Resolution = EEG HR). EEG HR and MEG are two infrequent state-of-the-art techniques. The independent contribution of EEG HR and MEG for the localization of the epileptogenic zone has been shown in several studies. However, several modeling studies have shown that MEG and EEG HR have a different detection capacity and spatial resolution depending on the cortical generators studied. Modeling studies suggest that MEG has better localization accuracy than EEG for most cortical sources. No direct comparison of the locating value of MEG and EEG HR for the localization of the epileptogenic zone has been performed to date in a large-scale clinical study. In this prospective study, 100 patients with partial epilepsy who are candidates for epilepsy surgery, and for some of them with intracranial EEG recording, will benefit from two advanced electrophysiological examinations including magnetoencephalographic recording (MEG). ) interictal electrophysiological abnormalities and high-resolution EEG recording (128 electrodes) in addition to the usual examinations performed as part of the pre-surgical assessment, prior to cortectomy and / or intracranial EEG recording. Based on recent work conducted in humans, we postulate: that the MEG and the EEG HR make it possible to precisely determine the epileptogenic zone, by using two approaches of definition of the epileptogenic zone (zone operated in the cured patients, zone at the origin of the crises during the intracranial recordings), but that the MEG is a little more precise than the EEG HR for the determination of the epileptogenic zone (we will try to highlight a difference of about 10%) that the quantitative study of the complementarity between EEG HR and MEG for modeling sources of epileptic spikes will show an added value in the use of both methods compared to the use of only one of the two methods that it is possible to determine the epileptogenic zone by determining the MEG model zone having the highest centrality value (hub) within the intercritical network by studying networks using graph theory.

The aim of this observational single-center cohort study is to gain a deeper understanding regarding the effects of treatment adaption based on information from outcome prediction models, risk stratification, as well as treatment monitoring, detection, prevention, and management of complications on course and outcome of adult patients with status epilepticus (SE).

This proposal outlines the steps required for the creation of a pilot database of EEG recordings and de-identified medical records from patients internally referred within the UNMH Comprehensive Epilepsy Center. The UNMH EEG Corpus would be the first database of its kind. Other public databases contain either patient EEG signals or medical records, but without both kinds of information, it is impossible to relate pre-treatment neurobiomarkers with post-treatment prognosis. The database will also contain information that can improve seizure localization based off of scalp and intracranial EEG, and the requisite data for the creation of algorithms that forecast seizure activity; a development that could ultimately lead to novel responsive neural stimulation procedures that suppress seizures before they begin.

For one-third of patients with drug-resistant epilepsy alternative approaches must be investigated in order to improve the quality of their life. A possible approach is to find automatic methods to detect/predict seizures, in order to adopt interventional actions to stop or abort the seizure or to limit its side effect. The main problem in this case is to evaluate the reproducibility of such methods and to standardize them, because there is a lack of availability of long-term electroencephalography (EEG) data. In this study we want to create a large long-term EEG database, called NEED (Neuromed Epilepsy EEG Database), whos aim is to give researchers a way to test their method in a large collection of data. The database will contain long-term EEG recordings of 200 patients as well as extensive metadata and standardized annotation of the data sets and will be made freely available for the download to the research community.

This prospective observational study aims to describe the effectiveness of MC on pain, epilepsy, sleep and /or anxiety/depression in a cohorts of patients authorized to use MC, using pre-defined, validated self assessment scales.

To evaluate the efficacy, safety and tolerability of cenobamate as adjunctive treatment of refractory focal epilepsy

Atypical presentations in epilepsy may include confusion status, acute maniac or delirious condition, loss of cognitive ability such as speech, interaction skills, or other praxis. Current diagnosis of epilepsy did not address on definition of seizure. The new insights of seizure semiology and their treatment response, suggest the screen tool and diagnostic criteria of epilepsy can be revised. In this study, we have two aims. The first aim is to develop a screening questionnaire by adding new semiology of epilepsy, including abnormality in psychiatry, cognition, and sleep, and to test its accuracy. The second aim is to evaluate the benefits in cognition of anti-epileptic drug intervention in participants with positive screening results.

Language is a signature human cognitive skill, but the precise computations that support language understanding remain unknown. This study aims to combine high-quality human neural data obtained through intracranial recordings with advances in computational modeling of human cognition to shed light on the construction and understanding of speech.

The proper period of anti-seizure medication (ASM) treamtment is important for decreasing side effect of ASM and recurrence of seizure. We evaluate reliable risk factor analysis for safe withdrawal of ASM in children with epilepsy. Futhermore, we develop the scoring system for prediction of seizure recurrence to set the standard for safe withdrawal of ASM.