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Status: Bibliographieeintrag

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Verfasst von:Braun, Urs [VerfasserIn]   i
 Plichta, Michael M. [VerfasserIn]   i
 Esslinger, Christine [VerfasserIn]   i
 Sauer, Carina [VerfasserIn]   i
 Haddad, Leila [VerfasserIn]   i
 Grimm, Oliver [VerfasserIn]   i
 Mier, Daniela [VerfasserIn]   i
 Mohnke, Sebastian [VerfasserIn]   i
 Heinz, Andreas [VerfasserIn]   i
 Erk, Susanne [VerfasserIn]   i
 Walter, Henrik [VerfasserIn]   i
 Seiferth, Nina [VerfasserIn]   i
 Kirsch, Peter [VerfasserIn]   i
 Meyer-Lindenberg, Andreas [VerfasserIn]   i
Titel:Test-retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures
Verf.angabe:Urs Braun, Michael M. Plichta, Christine Esslinger, Carina Sauer, Leila Haddad, Oliver Grimm, Daniela Mier, Sebastian Mohnke, Andreas Heinz, Susanne Erk, Henrik Walter, Nina Seiferth, Peter Kirsch, Andreas Meyer-Lindenberg
E-Jahr:2012
Jahr:16 January 2012
Umfang:9 S.
Fussnoten:Gesehen am 29.03.2018
Titel Quelle:Enthalten in: NeuroImage
Ort Quelle:Orlando, Fla. : Academic Press, 1992
Jahr Quelle:2012
Band/Heft Quelle:59(2012), 2, Seite 1404-1412
ISSN Quelle:1095-9572
Abstract:Characterizing the brain connectome using neuroimaging data and measures derived from graph theory emerged as a new approach that has been applied to brain maturation, cognitive function and neuropsychiatric disorders. For a broad application of this method especially for clinical populations and longitudinal studies, the reliability of this approach and its robustness to confounding factors need to be explored. Here we investigated test-retest reliability of graph metrics of functional networks derived from functional magnetic resonance imaging (fMRI) recorded in 33 healthy subjects during rest. We constructed undirected networks based on the Anatomic-Automatic-Labeling (AAL) atlas template and calculated several commonly used measures from the field of graph theory, focusing on the influence of different strategies for confound correction. For each subject, method and session we computed the following graph metrics: clustering coefficient, characteristic path length, local and global efficiency, assortativity, modularity, hierarchy and the small-worldness scalar. Reliability of each graph metric was assessed using the intraclass correlation coefficient (ICC). Overall ICCs ranged from low to high (0 to 0.763) depending on the method and metric. Methodologically, the use of a broader frequency band (0.008-0.15Hz) yielded highest reliability indices (mean ICC=0.484), followed by the use of global regression (mean ICC=0.399). In general, the second order metrics (small-worldness, hierarchy, assortativity) studied here, tended to be more robust than first order metrics. In conclusion, our study provides methodological recommendations which allow the computation of sufficiently robust markers of network organization using graph metrics derived from fMRI data at rest.
DOI:doi:10.1016/j.neuroimage.2011.08.044
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: http://dx.doi.org/10.1016/j.neuroimage.2011.08.044
 Volltext: http://www.sciencedirect.com/science/article/pii/S105381191100961X
 DOI: https://doi.org/10.1016/j.neuroimage.2011.08.044
Datenträger:Online-Ressource
Sprache:eng
Bibliogr. Hinweis:Erscheint auch als : Druck-Ausgabe: Braun, Urs, 1985 - : Test-retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures. - 2012
Sach-SW:fMRI
 Graph theory
 Network analysis
 Resting-state functional connectivity
 Test-retest reliability
K10plus-PPN:1571533885
Verknüpfungen:→ Zeitschrift

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