1. Computational Modeling of Epileptic Activity: From Cortical Sources to EEG Signals
- Author
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D. Cosandier-Rimele, Isabelle Merlet, Jean-Michel Badier, Fabrice Wendling, Fabrice Bartolomei, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen (UMG), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epilepsies, Lesions Cerebrales et Systemes Neuraux de la Cognition, Université de la Méditerranée - Aix-Marseille 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Neurophysiologie Clinique, Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
Physiology ,Computer science ,Cortical source ,MESH: Neurons ,Action Potentials ,Context (language use) ,Electroencephalography ,MESH: Signal Processing, Computer-Assisted ,EEG-fMRI ,Brain mapping ,Synchronization ,03 medical and health sciences ,0302 clinical medicine ,MESH: Computer Simulation ,Physiology (medical) ,MESH: Electroencephalography ,medicine ,Humans ,Premovement neuronal activity ,Computer Simulation ,MESH: Action Potentials ,MESH: Brain Mapping ,030304 developmental biology ,Cerebral Cortex ,Neurons ,Brain Mapping ,0303 health sciences ,Signal processing ,MESH: Humans ,Epilepsy ,medicine.diagnostic_test ,business.industry ,Computational model ,Intracerebral EEG ,Signal Processing, Computer-Assisted ,Pattern recognition ,Scalp EEG ,Forward problem ,Scalp eeg ,MESH: Cerebral Cortex ,Neurology ,MESH: Epilepsy ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Neurology (clinical) ,Artificial intelligence ,business ,030217 neurology & neurosurgery - Abstract
International audience; In epileptic patients candidate to surgery, the interpretation of EEG signals recorded either within (depth EEG) or at the surface (scalp EEG) of the head is a crucial issue to determine epileptogenic brain regions and to define subsequent surgical strategy. This task remains difficult as there is no simple relationship between the spatiotemporal features of neuronal generators (convoluted cortical dipole layers) and the electric field potentials recorded by the electrodes. Indeed, this relationship depends on the complex interaction of several factors regarding involved cortical sources: location, area, geometry, and synchronization of neuronal activity. A computational model is proposed to address this issue. It relies on a neurophysiologically relevant model of EEG signals, which combines an accurate description of both the intracerebral sources of activity and the transfer function between dipole layers and recorded field potentials. The model is used, on the one hand, to quantitatively study the influence of source-related parameters on the properties of simulated signals, and on the other hand, to jointly analyze depth EEG and scalp EEG signals. In this article, the authors review some of the results obtained from the model with respect to the literature on the interpretation of EEG signals in the context of epilepsy.
- Published
- 2010
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