AIMC Topic: Epilepsies, Partial

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Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

Journal of neural engineering
OBJECTIVE: An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practi...

Metrics of brain network architecture capture the impact of disease in children with epilepsy.

NeuroImage. Clinical
BACKGROUND AND OBJECTIVE: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional ...

Dynamic alterations of SEEG characteristics during peri-ictal period and localization of seizure onset zone.

Neurobiology of disease
BACKGROUND: The evolution in peri-ictal period (from pre-ictal to ictal phase) of seizures contains abundant epileptogenic information, which aids in exploring the mechanism of seizures and localizing the epileptogenic zone (EZ). This study aims to i...

Decision support system based on ensemble models in distinguishing epilepsy types.

Epilepsy & behavior : E&B
This study aimed to classify patients' focal (frontal, temporal, parietal, occipital), multifocal, and generalized epileptiform activities based on EEG findings using artificial intelligence models. The study included 575 patients followed in the Neu...

Robot-assisted stereoelectroencephalography exploration of the limbic thalamus in human focal epilepsy: implantation technique and complications in the first 24 patients.

Neurosurgical focus
OBJECTIVE: Despite numerous imaging studies highlighting the importance of the thalamus in a patient's surgical prognosis, human electrophysiological studies involving the limbic thalamic nuclei are limited. The objective of this study was to evaluat...

Unsupervised Learning of Spatiotemporal Interictal Discharges in Focal Epilepsy.

Neurosurgery
BACKGROUND: Interictal epileptiform discharges are an important biomarker for localization of focal epilepsy, especially in patients who undergo chronic intracranial monitoring. Manual detection of these pathophysiological events is cumbersome, but i...