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• W2950472458 endingPage "353" @default.
• W2950472458 startingPage "340" @default.
• W2950472458 abstract "There are a growing number of neuroimaging methods that model spatio-temporal patterns of brain activity to allow more meaningful characterizations of brain networks. This paper proposes dynamic graphical models (DGMs) for dynamic, directed functional connectivity. DGMs are a multivariate graphical model with time-varying coefficients that describe instantaneous directed relationships between nodes. A further benefit of DGMs is that networks may contain loops and that large networks can be estimated. We use network simulations and human resting-state fMRI (N = 500) to investigate the validity and reliability of the estimated networks. We simulate systematic lags of the hemodynamic response at different brain regions to investigate how these lags potentially bias directionality estimates. In the presence of such lag confounds (0.4-0.8 s offset between connected nodes), our method has a sensitivity of 72%-77% to detect the true direction. Stronger lag confounds have reduced sensitivity, but do not increase false positives (i.e., directionality estimates of the opposite direction). In human resting-state fMRI, the default mode network has consistent influence on the cerebellar, the limbic and the auditory/temporal networks. We also show a consistent reciprocal relationship between the visual medial and visual lateral network. Finally, we apply the method in a small mouse fMRI sample and discover a highly plausible relationship between areas in the hippocampus feeding into the cingulate cortex. We provide a computationally efficient implementation of DGM as a free software package for R." @default.
• W2950472458 created "2019-06-27" @default.
• W2950472458 creator A5000441695 @default.
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• W2950472458 date "2018-07-01" @default.
• W2950472458 modified "2023-10-12" @default.
• W2950472458 title "Directed functional connectivity using dynamic graphical models" @default.
• W2950472458 cites W1003962816 @default.
• W2950472458 cites W1144597879 @default.
• W2950472458 cites W1552598564 @default.
• W2950472458 cites W1760829075 @default.
• W2950472458 cites W1801278145 @default.
• W2950472458 cites W1907418661 @default.
• W2950472458 cites W1967931162 @default.
• W2950472458 cites W1968248619 @default.
• W2950472458 cites W1970501449 @default.
• W2950472458 cites W1974105735 @default.
• W2950472458 cites W1975389666 @default.
• W2950472458 cites W1976623182 @default.
• W2950472458 cites W1981786093 @default.
• W2950472458 cites W1995664360 @default.
• W2950472458 cites W1996196481 @default.
• W2950472458 cites W1998175349 @default.
• W2950472458 cites W1999653836 @default.
• W2950472458 cites W2005933475 @default.
• W2950472458 cites W2006240253 @default.
• W2950472458 cites W2007894316 @default.
• W2950472458 cites W2014022174 @default.
• W2950472458 cites W2015456912 @default.
• W2950472458 cites W2015822010 @default.
• W2950472458 cites W2021653459 @default.
• W2950472458 cites W2024729467 @default.
• W2950472458 cites W2030602986 @default.
• W2950472458 cites W2030727443 @default.
• W2950472458 cites W2049609468 @default.
• W2950472458 cites W2055266204 @default.
• W2950472458 cites W2058187841 @default.
• W2950472458 cites W2061564920 @default.
• W2950472458 cites W2064109848 @default.
• W2950472458 cites W2069908974 @default.
• W2950472458 cites W2075878049 @default.
• W2950472458 cites W2079450984 @default.
• W2950472458 cites W2082906925 @default.
• W2950472458 cites W2085423000 @default.
• W2950472458 cites W2086021750 @default.
• W2950472458 cites W2087658007 @default.
• W2950472458 cites W2090017477 @default.
• W2950472458 cites W2094377986 @default.
• W2950472458 cites W2096672020 @default.
• W2950472458 cites W2106201557 @default.
• W2950472458 cites W2109198067 @default.
• W2950472458 cites W2112151839 @default.
• W2950472458 cites W2117663940 @default.
• W2950472458 cites W2123586737 @default.
• W2950472458 cites W2124698428 @default.
• W2950472458 cites W2129584734 @default.
• W2950472458 cites W2131286474 @default.
• W2950472458 cites W2135176444 @default.
• W2950472458 cites W2136435696 @default.
• W2950472458 cites W2138905229 @default.
• W2950472458 cites W2140952948 @default.
• W2950472458 cites W2142566135 @default.
• W2950472458 cites W2146141169 @default.
• W2950472458 cites W2156270499 @default.
• W2950472458 cites W2157280774 @default.
• W2950472458 cites W2159275967 @default.
• W2950472458 cites W2170702893 @default.
• W2950472458 cites W2173630155 @default.
• W2950472458 cites W2233387572 @default.
• W2950472458 cites W2235823035 @default.
• W2950472458 cites W2276520418 @default.
• W2950472458 cites W2325655614 @default.
• W2950472458 cites W2411460890 @default.
• W2950472458 cites W2413679900 @default.
• W2950472458 cites W2467643547 @default.
• W2950472458 cites W2472928215 @default.
• W2950472458 cites W2516718464 @default.
• W2950472458 cites W2526529257 @default.
• W2950472458 cites W2526989977 @default.
• W2950472458 cites W2563148661 @default.
• W2950472458 cites W2563279629 @default.
• W2950472458 cites W2594366375 @default.
• W2950472458 cites W2616940960 @default.
• W2950472458 cites W2724344943 @default.
• W2950472458 cites W2729610843 @default.
• W2950472458 cites W2733572936 @default.
• W2950472458 cites W2949321751 @default.
• W2950472458 cites W2963739582 @default.
• W2950472458 cites W3021064838 @default.
• W2950472458 cites W89053356 @default.
• W2950472458 doi "https://doi.org/10.1016/j.neuroimage.2018.03.074" @default.

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