Jafarian, A;
Freestone, DR;
Nešić, D;
Grayden, DB;
(2019)
Identification of A Neural Mass Model of Burst Suppression.
In:
Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
(pp. pp. 2905-2908).
IEEE: Berlin, Germany.
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Abstract
Burst suppression includes alternating patterns of silent and fast spike activities in neuronal activities observable (in micro or macro scale) electro-physiological recordings. Biological models of burst suppression are given as dynamical systems with slow and fast states. The aim of this paper is to give a method to identify parameters of a mesoscopic model of burst suppression that can provide insights into study underlying generators of intracranial electroencephalogram (iEEG) data. An optimisation technique based upon a genetic algorithm (GA) is employed to find feasible model parameters to replicate burst patterns in the iEEG data with paroxysmal transitions. Then, a continuous-discrete unscented Kalman filter (CD-UKF) is used to infer hidden states of the model and to enhance the identification results from the GA. The results show promise in finding the model parameters of a partially observed mesoscopic model of burst suppression.
| Type: | Proceedings paper |
|---|---|
| Title: | Identification of A Neural Mass Model of Burst Suppression |
| Event: | 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) |
| Dates: | 23 July 2019 - 27 July 2019 |
| ISBN-13: | 978-1-5386-1311-5 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/embc.2019.8856998 |
| Publisher version: | https://doi.org/10.1109/embc.2019.8856998 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Brain modeling, Mathematical model, Data models, Sociology, Statistics, Genetic algorithms, Biological system modeling |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10083147 |
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