% IMPORTANT: The following is UTF-8 encoded. This means that in the presence % of non-ASCII characters, it will not work with BibTeX 0.99 or older. % Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or % “biber”. @ARTICLE{Larabi:877882, author = {Larabi, Daouia I. and Renken, Remco J. and Cabral, Joana and Marsman, Jan-Bernard C. and Aleman, André and Ćurčić-Blake, Branislava}, title = {{T}rait self-reflectiveness relates to time-varying dynamics of resting state functional connectivity and underlying structural connectomes: {R}ole of the default mode network}, journal = {NeuroImage}, volume = {219}, issn = {1053-8119}, address = {Orlando, Fla.}, publisher = {Academic Press}, reportid = {FZJ-2020-02489}, pages = {116896 -}, year = {2020}, note = {The authors would like to thank all participants for their participation, Anita Sibeijn-Kuiper and Judith Streurman for support in scanning participants, Dr. Michelle Servaas and Dr. Leonardo Cerliani for advice on analyses, and the Center for Magnetic Resonance Research of the University of Minnesota for receipt of their multi-echo-EPI sequence. We would also like to thank the Center for Information Technology of the University of Groningen for their support and for providing access to the Peregrine high-performance computing cluster.}, abstract = {BackgroundCognitive insight is defined as the ability to reflect upon oneself (i.e. self-reflectiveness), and to not be overly confident of one's own (incorrect) beliefs (i.e. self-certainty). These abilities are impaired in several disorders, while they are essential for the evaluation and regulation of one's behavior. We hypothesized that cognitive insight is a dynamic process, and therefore examined how it relates to temporal dynamics of resting state functional connectivity (FC) and underlying structural network characteristics in 58 healthy individuals.MethodsCognitive insight was measured with the Beck Cognitive Insight Scale. FC characteristics were calculated after obtaining four FC states with leading eigenvector dynamics analysis. Gray matter (GM) and DTI connectomes were based on GM similarity and probabilistic tractography. Structural graph characteristics, such as path length, clustering coefficient, and small-world coefficient, were calculated with the Brain Connectivity Toolbox. FC and structural graph characteristics were correlated with cognitive insight.ResultsIndividuals with lower cognitive insight switched more and spent less time in a globally synchronized state. Additionally, individuals with lower self-reflectiveness spent more time in, had a higher probability of, and had a higher chance of switching to a state entailing default mode network (DMN) areas. With lower self-reflectiveness, DTI-connectomes were segregated less (i.e. lower global clustering coefficient) with lower embeddedness of the left angular gyrus specifically (i.e. lower local clustering coefficient).ConclusionsOur results suggest less stable functional and structural networks in individuals with poorer cognitive insight, specifically self-reflectiveness. An overly present DMN appears to play a key role in poorer self-reflectiveness.}, cin = {INM-7}, ddc = {610}, cid = {I:(DE-Juel1)INM-7-20090406}, pnm = {572 - (Dys-)function and Plasticity (POF3-572)}, pid = {G:(DE-HGF)POF3-572}, typ = {PUB:(DE-HGF)16}, pubmed = {pmid:32470573}, UT = {WOS:000559780400009}, doi = {10.1016/j.neuroimage.2020.116896}, url = {https://juser.fz-juelich.de/record/877882}, }