Focal epilepsy is a chronic condition characterized by hyper-activity and abnormal synchronization of a specific brain region. For pharmacoresistant patients, the surgical resection of the critical area is considered a valid clinical solution, therefore, an accurate localization is crucial to minimize neurological damage. In current clinical routine the characterization of the Epileptogenic Zone (EZ) is performed using invasive methods, such as Stereo-ElectroEncephaloGraphy (SEEG). Medical experts perform the tag of neural electrophysiological recordings by visually inspecting the acquired data, a highly time consuming and subjective procedure. Here we show the results of an automatic multi-modal classification method for the evaluation of critical areas in focal epileptic patients. The proposed method represents an attempt in the characterization of brain areas which integrates the anatomical information on neural tissue, inferred using Magnetic Resonance Imaging (MRI) in combination with spectral features extracted from SEEG recordings.

Classification of Epileptic Activity Through Temporal and Spatial Characterization of Intracranial Recordings

D'Amario V.;Arnulfo G.;Nobili L.;Barla A.
2020-01-01

Abstract

Focal epilepsy is a chronic condition characterized by hyper-activity and abnormal synchronization of a specific brain region. For pharmacoresistant patients, the surgical resection of the critical area is considered a valid clinical solution, therefore, an accurate localization is crucial to minimize neurological damage. In current clinical routine the characterization of the Epileptogenic Zone (EZ) is performed using invasive methods, such as Stereo-ElectroEncephaloGraphy (SEEG). Medical experts perform the tag of neural electrophysiological recordings by visually inspecting the acquired data, a highly time consuming and subjective procedure. Here we show the results of an automatic multi-modal classification method for the evaluation of critical areas in focal epileptic patients. The proposed method represents an attempt in the characterization of brain areas which integrates the anatomical information on neural tissue, inferred using Magnetic Resonance Imaging (MRI) in combination with spectral features extracted from SEEG recordings.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1007648
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