- 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.…
MetadatenAuthor: | 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 |
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URN: | urn:nbn:de:bvb:384-opus4-1102388 |
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Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/110238 |
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ISBN: | 978-1-4577-0219-8OPAC |
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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 |
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Publisher: | IEEE |
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Place of publication: | Piscataway, NJ |
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Editor: | Bruce Wheeler, May Dongmei Wang, James Patton |
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Type: | Conference Proceeding |
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Language: | English |
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Year of first Publication: | 2016 |
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Publishing Institution: | Universität Augsburg |
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Release Date: | 2023/12/15 |
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First Page: | 3598 |
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Last Page: | 3601 |
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DOI: | https://doi.org/10.1109/embc.2016.7591506 |
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Institutes: | Fakultät für Angewandte Informatik |
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| Fakultät für Angewandte Informatik / Institut für Informatik |
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| Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Informatik in der Medizintechnik |
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Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
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Licence (German): | Deutsches Urheberrecht |
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