Spreading dynamics on spatially constrained complex brain networks

The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics, and has been widely undertaken. Typically, however, networks employed in theoretical studies bear little relation to the spatial embedding or connec...

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Main Authors: O'Dea, Reuben D., Crofts, Jonathan J., Kaiser, Marcus
Format: Article
Published: Royal Society 2013
Online Access:https://eprints.nottingham.ac.uk/28504/
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author O'Dea, Reuben D.
Crofts, Jonathan J.
Kaiser, Marcus
author_facet O'Dea, Reuben D.
Crofts, Jonathan J.
Kaiser, Marcus
author_sort O'Dea, Reuben D.
building Nottingham Research Data Repository
collection Online Access
description The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics, and has been widely undertaken. Typically, however, networks employed in theoretical studies bear little relation to the spatial embedding or connectivity of the neural networks that they attempt to replicate. Here, we employ detailed neuroimaging data to define a network whose spatial embedding represents accurately the folded structure of the cortical surface of a rat and investigate the propagation of activity over this network under simple spreading and connectivity rules. By comparison with standard network models with the same coarse statistics, we show that the cortical geometry influences profoundly the speed propagation of activation through the network. Our conclusions are of high relevance to the theoretical modelling of epileptic seizure events, and indicate that such studies which omit physiological network structure risk simplifying the dynamics in a potentially significant way.
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spelling nottingham-285042020-05-04T16:36:33Z https://eprints.nottingham.ac.uk/28504/ Spreading dynamics on spatially constrained complex brain networks O'Dea, Reuben D. Crofts, Jonathan J. Kaiser, Marcus The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics, and has been widely undertaken. Typically, however, networks employed in theoretical studies bear little relation to the spatial embedding or connectivity of the neural networks that they attempt to replicate. Here, we employ detailed neuroimaging data to define a network whose spatial embedding represents accurately the folded structure of the cortical surface of a rat and investigate the propagation of activity over this network under simple spreading and connectivity rules. By comparison with standard network models with the same coarse statistics, we show that the cortical geometry influences profoundly the speed propagation of activation through the network. Our conclusions are of high relevance to the theoretical modelling of epileptic seizure events, and indicate that such studies which omit physiological network structure risk simplifying the dynamics in a potentially significant way. Royal Society 2013-04-06 Article PeerReviewed O'Dea, Reuben D., Crofts, Jonathan J. and Kaiser, Marcus (2013) Spreading dynamics on spatially constrained complex brain networks. Journal of the Royal Society Interface, 10 (81). ISSN 1742-5689 http://classic.rsif.royalsocietypublishing.org/content/10/81/20130016 doi:10.1098/​rsif.2013.0016 doi:10.1098/​rsif.2013.0016
spellingShingle O'Dea, Reuben D.
Crofts, Jonathan J.
Kaiser, Marcus
Spreading dynamics on spatially constrained complex brain networks
title Spreading dynamics on spatially constrained complex brain networks
title_full Spreading dynamics on spatially constrained complex brain networks
title_fullStr Spreading dynamics on spatially constrained complex brain networks
title_full_unstemmed Spreading dynamics on spatially constrained complex brain networks
title_short Spreading dynamics on spatially constrained complex brain networks
title_sort spreading dynamics on spatially constrained complex brain networks
url https://eprints.nottingham.ac.uk/28504/
https://eprints.nottingham.ac.uk/28504/
https://eprints.nottingham.ac.uk/28504/