20.500.12556/RUL-153571 Static and dynamic fMRI-derived functional connectomes represent largely similar information Functional connectivity (FC) of blood-oxygen-level-dependent (BOLD) fMRI time series can be estimated using methods that differ in sensitivity to the temporal order of time points (static vs. dynamic) and the number of regions considered in estimating a single edge (bivariate vs. multivariate). Previous research suggests that dynamic FC explains variability in FC fluctuations and behavior beyond static FC. Our aim was to systematically compare methods on both dimensions. We compared five FC methods: Pearson’s/full correlation (static, bivariate), lagged correlation (dynamic, bivariate), partial correlation (static, multivariate) and multivariate AR model with and without self-connections (dynamic, multivariate). We compared these methods by (i) assessing similarities between FC matrices, (ii) by comparing node centrality measures, and (iii) by comparing the patterns of brain-behavior associations. Although FC estimates did not differ as a function of sensitivity to temporal order, we observed differences between the multivariate and bivariate FC methods. The dynamic FC estimates were highly correlated with the static FC estimates, especially when comparing group-level FC matrices. Similarly, there were high correlations between the patterns of brain-behavior associations obtained using the dynamic and static FC methods. We conclude that the dynamic FC estimates represent information largely similar to that of the static FC. functional connectivity autoregressive model dynamic functional connectivity brain-behavior associations measurement brain functional magnetic resonance imaging fMRI neurosciences neural networks funkcijska konektivnost merjenje možgani funkcijsko magnetnoresonančno slikanje fMRI nevroznanost nevronske mreže true false true Angleški jezik Slovenski jezik Članek v reviji 2024-01-16 12:07:37 2024-01-16 12:07:44 2024-01-17 03:43:21 0000-00-00 00:00:00 2023 0 0 Str. 1266–1301 iss. 4 Vol. 7 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 159.91:612.82 2472-1751 10.1162/netn_a_00325 157380355 Matkovic_Static_and_dynamic_fMRI-derived_functional_connectomes_represent_largely_similar_information.pdf Matkovic_Static_and_dynamic_fMRI-derived_functional_connectomes_represent_largely_similar_information.pdf 1 8FE42CC2727978FC3B060D809473961B faf12c99550a5f9dfa407381ee8ff35996144041e074658f2ca3636443a74a89 d4f6f73a-b460-11ee-9139-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=179647 https://direct.mit.edu/netn/article/doi/10.1162/netn_a_00325/116419/Static-and-dynamic-fMRI-derived-functional 1 7fd2473b-b45f-11ee-9139-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=179646 Filozofska fakulteta 0 0 0