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Characterisation Of Resting Brain Network Topologies Across The Human Lifespan With Magnetoencephalogram Recordings: A Phase Slope Index And Granger Causality Comparison Study

Shumbayawonda, Elizabeth, Fernández, A, Escudero, J, Hughes, Michael and Abasolo, Daniel Emilio (2017) Characterisation Of Resting Brain Network Topologies Across The Human Lifespan With Magnetoencephalogram Recordings: A Phase Slope Index And Granger Causality Comparison Study In: Biosignals 2017, 2017-02-21 - 2017-02-23, Porto, Portugal.

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Abstract

This study focuses on the resting state network analysis of the brain, as well as how these networks change both in topology and location throughout life. The magnetoencephalogram (MEG) background activity from 220 healthy volunteers (age 7-84 years), was analysed combining complex network analysis principles of graph theory with both linear and non-linear methods to evaluate the changes in the brain. Granger Causality (GC) (linear method) and Phase Slope Index (PSI) (non-linear method) were used to observe the connectivity in the brain during rest, and as a function of age by analysing the degree, clustering coefficient, efficiency, betweenness, modularity and maximised modularity of the observed complex brain networks. Our results showed that GC showed little linear causal activity in the brain at rest, with small world topology, while PSI showed little information flow in the brain, with random network topology. However, both analyses produced complementary results pertaining to the resting state of the brain.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Mechanical Engineering Sciences
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Shumbayawonda, Elizabethe.shumbayawonda@surrey.ac.ukUNSPECIFIED
Fernández, AUNSPECIFIEDUNSPECIFIED
Escudero, JUNSPECIFIEDUNSPECIFIED
Hughes, MichaelM.Hughes@surrey.ac.ukUNSPECIFIED
Abasolo, Daniel EmilioD.Abasolo@surrey.ac.ukUNSPECIFIED
Date : 2017
Uncontrolled Keywords : Granger Causality, Phase Slope Index, Graph Theory, Complex Network, Ageing, Magnetoencephalography
Depositing User : Symplectic Elements
Date Deposited : 22 Dec 2016 12:32
Last Modified : 19 Jul 2017 07:25
URI: http://epubs.surrey.ac.uk/id/eprint/813169

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