Interictal functional connectivity in focal refractory epilepsies investigated by intracranial EEG

S Lagarde, CG Bénar, F Wendling, F Bartolomei - Brain connectivity, 2022 - liebertpub.com
Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic
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 …

Interictal SEEG resting‐state connectivity localizes the seizure onset zone and predicts seizure outcome

H Jiang, V Kokkinos, S Ye, A Urban, A Bagić… - Advanced …, 2022 - Wiley Online Library
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 …

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 …

Network perspectives on epilepsy using EEG/MEG source connectivity

P Van Mierlo, Y Höller, NK Focke… - Frontiers in neurology, 2019 - frontiersin.org
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 …

EEG: Current relevance and promising quantitative analyses

M Gavaret, A Iftimovici, E Pruvost-Robieux - Revue Neurologique, 2023 - Elsevier
Electroencephalography (EEG) remains an essential tool, characterized by an excellent
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

AH Shahid, MP Singh - Biocybernetics and Biomedical Engineering, 2019 - Elsevier
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 …

Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy

Y Varatharajah, B Joseph, B Brinkmann… - …, 2022 - Wiley Online Library
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 …

[HTML][HTML] Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy

SS Rajagopalan, S Bhardwaj, R Panda, VR Reddam… - Seizure, 2018 - Elsevier
Purpose Quasi-stable electrical distribution in EEG called microstates could carry useful
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

L Tait, LE Staniaszek, E Galizia, D Martin‐Lopez… - …, 2024 - Wiley Online Library
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 …