Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm

This paper evaluates brain functional connectivity (FC) using Electroencephalography data from 18 healthy subjects using visual oddball paradigm. We have evaluated the effect of different oddball tasks in different time segments. We have also compared the brain FC between the resting state-task data...

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Main Authors: Kang Wei Thee, Humaira Nisar, Chit Siang Soh
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8502047/
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spelling doaj-71921eb023d04f5f8c3c1ff993894e602021-03-29T21:28:58ZengIEEEIEEE Access2169-35362018-01-016647086472710.1109/ACCESS.2018.28770358502047Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball ParadigmKang Wei Thee0https://orcid.org/0000-0001-7126-2583Humaira Nisar1https://orcid.org/0000-0003-2026-5666Chit Siang Soh2Department of Electronic Engineering, Universiti Tunku Abdul Rahman, Kampar, MalaysiaDepartment of Electronic Engineering, Universiti Tunku Abdul Rahman, Kampar, MalaysiaDepartment of Electronic Engineering, Universiti Tunku Abdul Rahman, Kampar, MalaysiaThis paper evaluates brain functional connectivity (FC) using Electroencephalography data from 18 healthy subjects using visual oddball paradigm. We have evaluated the effect of different oddball tasks in different time segments. We have also compared the brain FC between the resting state-task data and task-task data. The trials from oddball tasks were averaged to form grand-average event-related potential. Each epoch was divided into six segments with fixed time interval. Coherence was used to compute the pairwise connections between 10-20 electrodes and adjacency matrices were formed. The threshold of 0.9 was set to binarize the matrices and form undirected graphs. Graph parameters (node degree, network density, and betweenness centrality) were used to quantify the networks. Node degree within a brain lobe was summed to form a brain regional activation graph. Node betweenness centrality was used to study the dynamic changes of the hub nodes in different oddball tasks. Edge betweenness centrality was used to quantify the significant functional networks in different oddball tasks. Results show that 1) denser brain network was found in target with response (TR) case as compared with target with no response and no target no response cases especially over 3<sup>rd</sup>, 4<sup>th</sup>, and 5<sup>th</sup> time segments which are before and during P300 period. 2) Higher brain activity in terms of node degree is distributed over all brain regions for TR case than the other two cases. 3) It is also observed that the parietal node is significant for P300 response. 4) Interactions among parietal, central, and temporal regions are significant for motor response that is only observed for TR case. The present findings suggest that our methodology is able to identify differences in FC patterns elicited by different oddball tasks for different brain states in different time segments.https://ieeexplore.ieee.org/document/8502047/CoherenceSTFTelectroencephalographyfunctional connectivitygraph theoryoddball paradigm
collection DOAJ
language English
format Article
sources DOAJ
author Kang Wei Thee
Humaira Nisar
Chit Siang Soh
spellingShingle Kang Wei Thee
Humaira Nisar
Chit Siang Soh
Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm
IEEE Access
Coherence
STFT
electroencephalography
functional connectivity
graph theory
oddball paradigm
author_facet Kang Wei Thee
Humaira Nisar
Chit Siang Soh
author_sort Kang Wei Thee
title Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm
title_short Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm
title_full Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm
title_fullStr Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm
title_full_unstemmed Graph Theoretical Analysis of Functional Brain Networks in Healthy Subjects: Visual Oddball Paradigm
title_sort graph theoretical analysis of functional brain networks in healthy subjects: visual oddball paradigm
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description This paper evaluates brain functional connectivity (FC) using Electroencephalography data from 18 healthy subjects using visual oddball paradigm. We have evaluated the effect of different oddball tasks in different time segments. We have also compared the brain FC between the resting state-task data and task-task data. The trials from oddball tasks were averaged to form grand-average event-related potential. Each epoch was divided into six segments with fixed time interval. Coherence was used to compute the pairwise connections between 10-20 electrodes and adjacency matrices were formed. The threshold of 0.9 was set to binarize the matrices and form undirected graphs. Graph parameters (node degree, network density, and betweenness centrality) were used to quantify the networks. Node degree within a brain lobe was summed to form a brain regional activation graph. Node betweenness centrality was used to study the dynamic changes of the hub nodes in different oddball tasks. Edge betweenness centrality was used to quantify the significant functional networks in different oddball tasks. Results show that 1) denser brain network was found in target with response (TR) case as compared with target with no response and no target no response cases especially over 3<sup>rd</sup>, 4<sup>th</sup>, and 5<sup>th</sup> time segments which are before and during P300 period. 2) Higher brain activity in terms of node degree is distributed over all brain regions for TR case than the other two cases. 3) It is also observed that the parietal node is significant for P300 response. 4) Interactions among parietal, central, and temporal regions are significant for motor response that is only observed for TR case. The present findings suggest that our methodology is able to identify differences in FC patterns elicited by different oddball tasks for different brain states in different time segments.
topic Coherence
STFT
electroencephalography
functional connectivity
graph theory
oddball paradigm
url https://ieeexplore.ieee.org/document/8502047/
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