Parameter and state estimation for a class of neural mass models - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Parameter and state estimation for a class of neural mass models

Résumé

We present an adaptive observer which asymptotically reconstructs the parameters and states of a model of interconnected cortical columns. Our study is motivated by the fact that the considered model is able to realistically reproduce patterns seen on (intracranial) electroencephalograms (EEG) by varying its parameters. Therefore, by estimating its parameters and states, we could gain a better understanding of the mechanisms underlying neurological phenomena such as seizures, which might lead to the prediction of the onsets of epileptic seizures. Simulations are performed to illustrate our results.
Fichier principal
Vignette du fichier
Final-version-adaptive_observer.pdf (301.52 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00753114 , version 1 (23-12-2012)

Identifiants

  • HAL Id : hal-00753114 , version 1

Citer

Romain Postoyan, Michelle Chong, Dragan Nesic, Levin Kuhlmann. Parameter and state estimation for a class of neural mass models. 51st IEEE Conference on Decision and Control, CDC 2012, Dec 2012, Maui, Hawaii, United States. pp.CDROM. ⟨hal-00753114⟩
142 Consultations
298 Téléchargements

Partager

Gmail Facebook X LinkedIn More