FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2942197767> ?p ?o ?g. }

• W2942197767 endingPage "223" @default.
• W2942197767 startingPage "212" @default.
• W2942197767 abstract "Brain functional connectivity features can predict cognition and behavior at the level of the individual. Most studies measure univariate signals, correlating timecourses from the average of constituent voxels in each node. While straightforward, this approach overlooks the spatial patterns of voxel-wise signals within individual nodes. Given that multivariate spatial activity patterns across voxels can improve fMRI measures of mental representations, here we asked whether using voxel-wise timecourses can better characterize region-by-region interactions relative to univariate approaches. Using two fMRI datasets, the Human Connectome Project sample and a local test-retest sample, we measured multivariate functional connectivity with multivariate distance correlation and univariate connectivity with Pearson's correlation. We compared multivariate and univariate connectivity estimates, demonstrating that relative to univariate estimates, multivariate estimates exhibited higher reliability at both the edge-level and connectome-level, stronger prediction of individual differences, and greater sensitivity to brain states within individuals. Our findings suggest that multivariate estimates reliably provide more powerful information about an individual's functional brain organization and its relation to cognitive skills." @default.
• W2942197767 created "2019-05-03" @default.
• W2942197767 creator A5011637851 @default.
• W2942197767 creator A5031168514 @default.
• W2942197767 creator A5042339320 @default.
• W2942197767 creator A5055510275 @default.
• W2942197767 creator A5058623592 @default.
• W2942197767 creator A5079635112 @default.
• W2942197767 date "2019-08-01" @default.
• W2942197767 modified "2023-10-17" @default.
• W2942197767 title "Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors" @default.
• W2942197767 cites W1491613324 @default.
• W2942197767 cites W1524242225 @default.
• W2942197767 cites W1545909954 @default.
• W2942197767 cites W1678378662 @default.
• W2942197767 cites W1687468892 @default.
• W2942197767 cites W1760829075 @default.
• W2942197767 cites W1965212122 @default.
• W2942197767 cites W1968248619 @default.
• W2942197767 cites W1986581915 @default.
• W2942197767 cites W2002627566 @default.
• W2942197767 cites W2021947606 @default.
• W2942197767 cites W2041716195 @default.
• W2942197767 cites W2041853331 @default.
• W2942197767 cites W2045758998 @default.
• W2942197767 cites W2054924908 @default.
• W2942197767 cites W2058587070 @default.
• W2942197767 cites W2081997665 @default.
• W2942197767 cites W2083789279 @default.
• W2942197767 cites W2085561705 @default.
• W2942197767 cites W2089367740 @default.
• W2942197767 cites W2093412356 @default.
• W2942197767 cites W2101374770 @default.
• W2942197767 cites W2102863441 @default.
• W2942197767 cites W2109883003 @default.
• W2942197767 cites W2111902267 @default.
• W2942197767 cites W2129932189 @default.
• W2942197767 cites W2141403362 @default.
• W2942197767 cites W2146246269 @default.
• W2942197767 cites W2154118775 @default.
• W2942197767 cites W2174056659 @default.
• W2942197767 cites W2283729400 @default.
• W2942197767 cites W2334913343 @default.
• W2942197767 cites W2339129891 @default.
• W2942197767 cites W2403664975 @default.
• W2942197767 cites W2406493898 @default.
• W2942197767 cites W2499800833 @default.
• W2942197767 cites W2516718464 @default.
• W2942197767 cites W2519753596 @default.
• W2942197767 cites W2526529257 @default.
• W2942197767 cites W2532111145 @default.
• W2942197767 cites W2538764405 @default.
• W2942197767 cites W2571093196 @default.
• W2942197767 cites W2587272693 @default.
• W2942197767 cites W2591352631 @default.
• W2942197767 cites W2603091313 @default.
• W2942197767 cites W2617838712 @default.
• W2942197767 cites W2623800443 @default.
• W2942197767 cites W2756187761 @default.
• W2942197767 cites W2767532579 @default.
• W2942197767 cites W2782673913 @default.
• W2942197767 cites W2791304632 @default.
• W2942197767 cites W2793907959 @default.
• W2942197767 cites W2797722180 @default.
• W2942197767 cites W2802442632 @default.
• W2942197767 cites W2950512494 @default.
• W2942197767 cites W2951617899 @default.
• W2942197767 cites W2952991498 @default.
• W2942197767 cites W3106063097 @default.
• W2942197767 cites W4234180827 @default.
• W2942197767 doi "https://doi.org/10.1016/j.neuroimage.2019.04.060" @default.
• W2942197767 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6591084" @default.
• W2942197767 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31039408" @default.
• W2942197767 hasPublicationYear "2019" @default.
• W2942197767 type Work @default.
• W2942197767 sameAs 2942197767 @default.
• W2942197767 citedByCount "58" @default.
• W2942197767 countsByYear W29421977672018 @default.
• W2942197767 countsByYear W29421977672019 @default.
• W2942197767 countsByYear W29421977672020 @default.
• W2942197767 countsByYear W29421977672021 @default.
• W2942197767 countsByYear W29421977672022 @default.
• W2942197767 countsByYear W29421977672023 @default.
• W2942197767 crossrefType "journal-article" @default.
• W2942197767 hasAuthorship W2942197767A5011637851 @default.
• W2942197767 hasAuthorship W2942197767A5031168514 @default.
• W2942197767 hasAuthorship W2942197767A5042339320 @default.
• W2942197767 hasAuthorship W2942197767A5055510275 @default.
• W2942197767 hasAuthorship W2942197767A5058623592 @default.
• W2942197767 hasAuthorship W2942197767A5079635112 @default.
• W2942197767 hasBestOaLocation W29421977671 @default.
• W2942197767 hasConcept C105795698 @default.
• W2942197767 hasConcept C117220453 @default.
• W2942197767 hasConcept C119857082 @default.
• W2942197767 hasConcept C121332964 @default.
• W2942197767 hasConcept C121694360 @default.
• W2942197767 hasConcept C153180895 @default.
• W2942197767 hasConcept C154945302 @default.

• next