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Journal articles
Model-based measurement of epileptic tissue excitability.
Abstract : In the context of pre-surgical evaluation of epileptic patients, depth-EEG signals constitute a valuable source of information to characterize the spatiotemporal organization of paroxysmal interictal and ictal activities, prior to surgery. However, interpretation of these very complex data remains a formidable task. Indeed, interpretation is currently mostly qualitative and efforts are still to be produced in order to quantitatively assess pathophysiological information conveyed by signals. The proposed EEG model-based approach is a contribution to this effort. It introduces both a physiological parameter set which represents excitation and inhibition levels in recorded neuronal tissue and a methodology to estimate this set of parameters. It includes Sequential Monte Carlo nonlinear filtering to estimate hidden state trajectory from EEG and Particle Swarm Optimization to maximize a likelihood function deduced from Monte Carlo computations. Simulation results illustrate what it can be expected from this methodology.
Cited literature [8 references]
https://www.hal.inserm.fr/inserm-00188489
Contributor : Lotfi Senhadji <>
Submitted on : Monday, November 19, 2007 - 7:18:31 PM
Last modification on : Wednesday, May 16, 2018 - 11:23:08 AM
Long-term archiving on: : Monday, April 12, 2010 - 2:32:52 AM
Contributor : Lotfi Senhadji <>
Submitted on : Monday, November 19, 2007 - 7:18:31 PM
Last modification on : Wednesday, May 16, 2018 - 11:23:08 AM
Long-term archiving on: : Monday, April 12, 2010 - 2:32:52 AM