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NCT03893916
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.
NCT07110688
In this program, the investigators will develop novel multimodal neural-behavioral-physiological monitoring tools (software and hardware), and machine learning models for mental states within social processes and beyond. The tools consist of a multimodal skin-like wearable sensor for physiological and biochemical sensing; a conversational virtual human platform to evoke naturalistic social processes; audiovisual affect recognition software; synchronization tools; and machine learning methods to model the multimodal data. The investigators will demonstrate the tools in healthy subjects without neural recordings and in patients with drug-resistant epilepsy who already have intracranial EEG (iEEG) electrodes implanted based on clinical criteria for standard monitoring to localize seizures, which is unrelated to our study.
NCT07010445
Epilepsy is one of the most common neurological chronic conditions with a serious burden on patients, their caregivers, and society. Drug-resistant epilepsy (DRE) heightens this burden. New approaches are thus a priority. Studies in animal models and humans have shown the link between gut microbiota (GM) and the central nervous system in health, neurological conditions, and neurodevelopmental disorders. DRE has been linked to GM dysbiosis. Preliminary findings in children with DRE showed GM modifications when responding to a ketogenic diet. The mediator role of GM has not yet been studied in DRE patients undergoing surgery/vagal nerve stimulation. CARE's central hypothesis is that the GM and its metabolic profile could contribute to clinical outcomes following these different therapeutic procedures. Identifying microbial biomarkers will enable us to deepen the knowledge of the role of gut-brain axis in epilepsy and to tailor the intervention to each patient based on GM modulation.
NCT06724029
The evaluation of neurosurgical outcomes varies from center to center, and the predictive factors that determine these outcomes are not fully known or shared. This study aims to assess outcomes and their predictors using measures agreed upon by the participating centers. Standardizing the evaluation of outcomes and predictors improves the quality of research, allows for data comparison, and facilitates a "common language" in routine clinical practice. Most importantly, it influences therapeutic decisions in various neurosurgical conditions. Clinically, the identified predictors can also be used during preoperative assessments to provide more precise guidance to patients undergoing surgery.