make_time_weights: Build smooth time weights from motion/outlier metrics

In neuroim2: Data Structures for Brain Imaging Data

Build smooth time weights from motion/outlier metrics

Description

Creates per-time-point weights w_t \in [0, 1] by smoothly combining framewise displacement (FD), DVARS, and spike/outlier scores. Each series is transformed through a soft logistic ramp so that values beyond the specified thresholds receive progressively lower weights instead of hard 0/1 decisions.

Usage

make_time_weights(
  fd = NULL,
  dvars = NULL,
  spike = NULL,
  fd_thr = 0.5,
  dvars_z = 2.5,
  spike_z = 5,
  fd_soft = 0.1,
  dvars_soft = 0.25,
  combine = c("min", "prod")
)

Arguments

fd	Optional numeric vector of framewise displacement values.
dvars	Optional numeric vector of DVARS values.
spike	Optional numeric vector with spike/outlier magnitudes.
fd_thr	Threshold (in mm) where FD weights start to drop (default 0.5).
dvars_z	Z-threshold applied to the standardized DVARS series (default 2.5).
spike_z	Z-threshold applied to the standardized spike series (default 5).
fd_soft	Logistic softness (in mm) controlling the slope around fd_thr.
dvars_soft	Logistic softness for the DVARS z-scores.
combine	Either "min" (take the minimum weight per TR) or "prod" (multiply all weights).

Value

Numeric vector of weights in [0,1] with length equal to the provided series. At least one of fd, dvars, or spike must be supplied.

neuroim2 documentation built on April 16, 2026, 5:07 p.m.