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Compute DVARS (Temporal Derivative of Timecourses)

Source: R/volume_quality.R
compute_dvars.Rd

DVARS measures the root mean square of the temporal derivative across all voxels, providing a single quality metric per volume. High DVARS indicates rapid signal changes, often associated with motion artifacts.

Usage

compute_dvars(Y, normalize = TRUE)

Arguments

Y

Numeric matrix of fMRI data (time x voxels).

normalize

Logical. If TRUE, normalize by median DVARS. Default TRUE.

Value

Numeric vector of length nrow(Y) with DVARS values. The first timepoint is set to the median of subsequent values.

Examples

# Simulate fMRI data with a motion spike
set.seed(123)
Y <- matrix(rnorm(100 * 50), nrow = 100, ncol = 50)
Y[50, ] <- Y[50, ] + 5  # Add spike at volume 50
dvars <- compute_dvars(Y)
#> Error in compute_dvars(Y): could not find function "compute_dvars"
# dvars[50] will be elevated compared to other volumes

# Identify suspect volumes (normalized DVARS > 1.5)
suspect <- which(dvars > 1.5)
#> Error: object 'dvars' not found
cat("Suspect volumes:", suspect, "\n")
#> Error: object 'suspect' not found