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- W4200369500 startingPage "118792" @default.
- W4200369500 abstract "Mapping the human connectome and understanding its relationship to brain function holds tremendous clinical potential. The connectome has two fundamental components: the nodes and the sconnections between them. While much attention has been given to deriving atlases and measuring the connections between nodes, there have been no studies examining the networks within nodes. Here we demonstrate that each node contains significant connectivity information, that varies systematically across task-induced states and subjects, such that measures based on these variations can be used to classify tasks and identify subjects. The results are not specific for any particular atlas but hold across different atlas resolutions. To date, studies examining changes in connectivity have focused on edge changes and assumed there is no useful information within nodes. Our findings illustrate that for typical atlases, within-node changes can be significant and may account for a substantial fraction of the variance currently attributed to edge changes ." @default.
- W4200369500 created "2021-12-31" @default.
- W4200369500 creator A5076717135 @default.
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- W4200369500 date "2022-02-01" @default.
- W4200369500 modified "2023-10-07" @default.
- W4200369500 title "Inside information: Systematic within-node functional connectivity changes observed across tasks or groups" @default.
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- W4200369500 doi "https://doi.org/10.1016/j.neuroimage.2021.118792" @default.
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