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- W1503593721 abstract "While fMRI activation studies contrasting task conditions regularly assess the whole brain, this is usually not true for studies analyzing task-dependent brain connectivity changes by psychophysiological interactions (PPI). Here we combine standard PPI (sPPI) and generalized PPI (gPPI) with a priori brain parcellation by spatially constrained normalized cut spectral clustering (NCUT) to analyze task-dependent connectivity changes in a whole brain manner, and compare the results to multiseed conventional PPI analyses over all activation peaks in an episodic memory recall task. We show that, depending on the chosen parcellation frame, the whole-brain PPI approach is able to detect a large amount of the information that is detected by the conventional approach. Over and above, whole-brain PPI allows identification of several additional task-modulated connections, particularly from seed regions without significant activation differences between conditions." @default.
- W1503593721 created "2016-06-24" @default.
- W1503593721 creator A5043322660 @default.
- W1503593721 creator A5049990277 @default.
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- W1503593721 date "2014-04-22" @default.
- W1503593721 modified "2023-10-15" @default.
- W1503593721 title "Analyzing task‐dependent brain network changes by whole‐brain psychophysiological interactions: A comparison to conventional analysis" @default.
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- W1503593721 doi "https://doi.org/10.1002/hbm.22532" @default.
- W1503593721 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6869077" @default.
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