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Interictal functional connectivity in focal refractory epilepsies investigated by intracranial EEG
Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic
networks of cortical and subcortical neural structures. These networks (“epileptogenic …
networks of cortical and subcortical neural structures. These networks (“epileptogenic …
[HTML][HTML] EEG biomarker candidates for the identification of epilepsy
S Gallotto, M Seeck - Clinical Neurophysiology Practice, 2023 - Elsevier
Electroencephalography (EEG) is one of the main pillars used for the diagnosis and study of
epilepsy, readily employed after a possible first seizure has occurred. The most established …
epilepsy, readily employed after a possible first seizure has occurred. The most established …
Interictal SEEG resting‐state connectivity localizes the seizure onset zone and predicts seizure outcome
Localization of epileptogenic zone currently requires prolonged intracranial recordings to
capture seizure, which may take days to weeks. The authors developed a novel method to …
capture seizure, which may take days to weeks. The authors developed a novel method to …
Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography
É Lemoine, D Toffa, G Pelletier-Mc Duff, AQ Xu… - Scientific Reports, 2023 - nature.com
Predicting seizure recurrence risk is critical to the diagnosis and management of epilepsy.
Routine electroencephalography (EEG) is a cornerstone of the estimation of seizure …
Routine electroencephalography (EEG) is a cornerstone of the estimation of seizure …
Network perspectives on epilepsy using EEG/MEG source connectivity
The evolution of EEG/MEG source connectivity is both, a promising, and controversial
advance in the characterization of epileptic brain activity. In this narrative review we …
advance in the characterization of epileptic brain activity. In this narrative review we …
EEG: Current relevance and promising quantitative analyses
Electroencephalography (EEG) remains an essential tool, characterized by an excellent
temporal resolution and offering a real window on cerebral functions. Surface EEG signals …
temporal resolution and offering a real window on cerebral functions. Surface EEG signals …
Computational intelligence techniques for medical diagnosis and prognosis: Problems and current developments
Diagnosis, being the first step in medical practice, is very crucial for clinical decision making.
This paper investigates state-of-the-art computational intelligence (CI) techniques applied in …
This paper investigates state-of-the-art computational intelligence (CI) techniques applied in …
Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy
Objective Anterior temporal lobectomy (ATL) is a widely performed and successful
intervention for drug‐resistant temporal lobe epilepsy (TLE). However, up to one third of …
intervention for drug‐resistant temporal lobe epilepsy (TLE). However, up to one third of …
[HTML][HTML] Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy
Purpose Quasi-stable electrical distribution in EEG called microstates could carry useful
information on the dynamics of large scale brain networks. Using machine learning …
information on the dynamics of large scale brain networks. Using machine learning …
Estimating the likelihood of epilepsy from clinically noncontributory electroencephalograms using computational analysis: A retrospective, multisite case–control study
Objective This study was undertaken to validate a set of candidate biomarkers of seizure
susceptibility in a retrospective, multisite case–control study, and to determine the …
susceptibility in a retrospective, multisite case–control study, and to determine the …