Hippocampal effective synchronization values are not pre-seizure indicator without considering the state of the onset channels.: Inability of synchronization values as pre-seizureReportar como inadecuado




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* Corresponding author 1 Digital Signal Processing Research Lab. 2 Payame Noor University 3 Shahid Chamran University 4 LTSI - Laboratoire Traitement du Signal et de l-Image

Abstract : In this paper, a model-based approach is presented to quantify the effective synchrony between hippocampal areas from depth-EEG signals. This approach is based on the parameter identification procedure of a realistic Multi-Source-Multi-Channel MSMC hippocampal model that simulates the function of different areas of hippocampus. In the model it is supposed that the observed signals recorded using intracranial electrodes are generated by some hidden neuronal sources, according to some parameters. An algorithm is proposed to extract the intrinsic solely relative to one hippocampal area and extrinsic coupling coefficients between two areas model parameters, simultaneously, by a Maximum Likelihood ML method. Coupling coefficients are considered as the measure of effective synchronization. This work can be considered as an application of Dynamic Causal Modeling DCM that enables us to understand effective synchronization changes during transition from inter-ictal to pre -ictal state. The algorithm is first validated by using some synthetic datasets. Then by extracting the coupling coefficients of real depth-EEG signals by the proposed approach, it is observed that the coupling values show no significant difference between ictal, pre-ictal and inter-ictal states, i.e. either the increase or decrease of coupling coefficients has been observed in all states. However, taking the value of intrinsic parameters into account, pre-seizure state can be distinguished from inter-ictal state. It is claimed that seizures start to appear when there are seizure-related physiological parameters on the onset channel, and its coupling coefficient toward other channels increases simultaneously. As a result of considering both intrinsic and extrinsic parameters as the feature vector, inter-ictal, pre-ictal and ictal activities are discriminated from each other with an accuracy of 91.33% accuracy.

Keywords : coupling effective synchronization seizure prediction model-based parameter identification





Autor: Farzaneh Shayegh - Saeed Sadri - Rassoul Amirfattahi - Karim Ansari-Asl - Jean-Jacques Bellanger - Lotfi Senhadji -

Fuente: https://hal.archives-ouvertes.fr/



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