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Identification of A Neural Mass Model of Burst Suppression

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. Green open access

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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 > 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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