norm_BOLD: Normalize BOLD data

In fMRItools: Routines for Common fMRI Processing Tasks

Normalize BOLD data

Description

Center the data across space and/or time, detrend, and scale, in that order. For dual regression, row centering is required and column centering is not recommended. Scaling and detrending depend on the user preference.

Usage

norm_BOLD(
  BOLD,
  center_rows = TRUE,
  center_cols = FALSE,
  scale = c("local", "global", "none"),
  scale_sm_xifti = NULL,
  scale_sm_FWHM = 2,
  scale_sm_xifti_mask = NULL,
  TR = NULL,
  hpf = 0.01,
  lpf = NULL
)

Arguments

BOLD	fMRI numeric data matrix (V \times T)
center_rows, center_cols	Center BOLD data across rows (each data location's time series) or columns (each time point's image)? Default: TRUE for row centering, and FALSE for column centering.
scale	"global" (default), "local", or "none". Global scaling will divide the entire data matrix by the mean image standard deviation (mean(sqrt(rowVars(BOLD)))). Local scaling will divide each data location's time series by its estimated standard deviation.
scale_sm_xifti, scale_sm_FWHM	Only applies if scale=="local" and BOLD represents CIFTI-format data. To smooth the standard deviation estimates used for local scaling, provide a "xifti" object with data locations in alignment with BOLD, as well as the smoothing FWHM (default: 2). If no "xifti" object is provided (default), do not smooth.
scale_sm_xifti_mask	For local scaling with smoothing, the data must be unmasked to be mapped back to the surface. So if the data are masked, provide the mask here.
TR	The temporal resolution of the data, i.e. the time between volumes, in seconds. TR is required for detrending with hpf.
hpf, lpf	The frequencies at which to apply temporal filtering to the data during pre-processing, in Hertz. Set either to NULL to disable. Default: 0.01 Hz highpass filter, and NULL for the lowpass filter (disabled). Filtering is accomplished by nuisance regression of discrete cosine transform (DCT) bases. The highpass filter serves to detrend the data, since low-frequency variance is associated with noise. The lowpass filter removes high-frequency variance, which is also thought to be from non-neuronal noise. Note the TR argument is required for temporal filtering. If TR is not provided, hpf and lpf will be ignored.

Value

Normalized BOLD data matrix (V \times T)

fMRItools documentation built on April 12, 2025, 1:32 a.m.