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Variance decomposition for single-subject task-based fMRI activity estimates across many sessions
2017
NeuroImage
A B S T R A C T Here we report an exploratory within-subject variance decomposition analysis conducted on a task-based fMRI dataset with an unusually large number of repeated measures (i.e., 500 trials in each of three different subjects) distributed across 100 functional scans and 9 to 10 different sessions. Within-subject variance was segregated into four primary components: variance across-sessions, variance across-runs within a session, variance acrossblocks within a run, and residual
doi:10.1016/j.neuroimage.2016.10.024
pmid:27773827
pmcid:PMC5398961
fatcat:k2fftthprredtfnofi5ppbhnle