Simulation α of EEG using brain network model

Al-Hossenat, Auhood and Wen, Paul and Li, Yan (2017) Simulation α of EEG using brain network model. In: First MoHESR and HCED Iraqi Scholars Conference in Australasia 2017 (ISCA 2017), 5-6 Dec 2017, Melbourne, Australia.

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Abstract

In this paper, we developed a large-scale brain network model comprising of four cerebral areas in the left hemisphere, and each area is modelled as an oscillator Jansen and Rit (JR) model. Our model is based on the structural connectivity of human connectome (SC) which was a hybrid from CoCoMac neuroinformatics database and diffusion spectrum imaging (DSI.) This brain network model was designed and implemented on the neuroinformatics platform using The Virtual Brain (TVB v1.5.3). The results demonstrated that incorporating the large-scale connectivity of brain regions and neural mass of JR model can generate signals similar to the α oscillation in frequency range of (7-12HZ) of EEG.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright © 2017 Swinburne University of Technology All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the written permission of the copyright holder. The authors retain the right to publish their contributions solely of their own works.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 July 2013 - 5 Sept 2019)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences (1 July 2013 - 5 Sept 2019)
Date Deposited: 06 Apr 2020 07:02
Last Modified: 07 May 2020 03:40
Uncontrolled Keywords: brain network model (BNM), neural masses model, structural connectivity, connectome, computational modelling, The Virtual Brain package
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling
URI: http://eprints.usq.edu.au/id/eprint/36860

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