Complex network analysis of resting-state fMRI of the brain

  • Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usageDue to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.show moreshow less

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Metadaten
Author:Abdul Rauf Anwar, Muhammad Yousaf Hashmy, Bilal Imran, Muhammad Hussnain Riaz, Sabtain Muhammad Muntazir Mehdi, Makii Muthalib, Stephane Perrey, Gunther Deuschl, Sergiu Groppa, Muthuraman MuthuramanORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1102388
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/110238
ISBN:978-1-4577-0219-8OPAC
Parent Title (English):2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 16-20 August 2016, Orlando, FL, USA
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Bruce Wheeler, May Dongmei Wang, James Patton
Type:Conference Proceeding
Language:English
Year of first Publication:2016
Publishing Institution:Universität Augsburg
Release Date:2023/12/15
First Page:3598
Last Page:3601
DOI:https://doi.org/10.1109/embc.2016.7591506
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Informatik in der Medizintechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht