multiGLM: multiGLM for CIFTI

In hrf: Hemodynamic Response Function

multiGLM for CIFTI

Description

Performs classical Bayesian GLM for task fMRI activation with CIFTI-format data, evaluating multiple design matrices. Includes the pre-processing steps of nuisance regression. Supports single-session analysis only.

Usage

multiGLM(
  BOLD,
  design,
  brainstructures = c("left", "right"),
  TR = NULL,
  resamp_res = 10000,
  hpf = NULL,
  nuisance = NULL,
  design_canonical = NULL,
  verbose = 1,
  meanTol = 1e-06,
  varTol = 1e-06
)

Arguments

BOLD	fMRI timeseries data in CIFTI format ("*.dtseries.nii"). For single-session analysis this can be a file path to a CIFTI file or a "xifti" object from the ciftiTools package. For multi-session analysis this can be a vector of file paths or a list of "xifti" objects. If BOLD is a "xifti" object(s), the surfaces, if any, will be used for the spatial model. However, if surfL and surfR are provided, they will override any surfaces in BOLD.
design	A 3D numeric array that is locations by fields by designs.
brainstructures	Character vector indicating which brain structure(s) of BOLD to analyze: "left" cortex; "right" cortex; and/or "subcortical" structures. Or "all" to model all three. Default: c("left","right") (cortex only).
TR	Temporal resolution of the data, in seconds.
resamp_res	For cortex spatial model. The number of vertices to which each cortical surface should be resampled, or NULL to not resample. For computational feasibility, a value of 10000 (default) or lower is recommended for Bayesian spatial modeling. If Bayes=FALSE, resamp_res can be set to NULL for full-resolution classical modeling.
hpf	Add DCT bases to nuisance to apply a temporal high-pass filter to the data, for detrending? hpf is the filter frequency. Use NULL to skip detrending. Detrending is strongly recommended for fMRI data, to help reduce the autocorrelation in the residuals, so NULL will induce a warning. Use "already" to disable the warning while skipping highpass filtering. Using at least two DCT bases is as sufficient for detrending as using linear and quadratic drift terms in the nuisance matrix. So if DCT detrending is being used here, there is no need to add linear and quadratic drift terms to nuisance.
nuisance	(Optional) A T \times N_{nuis} matrix of nuisance signals, where T is the number of timepoints and N is the number of nuisance signals, or a list of these for multi-session analysis. Nuisance signals are regressed from the fMRI data and design matrix prior to GLM computation. Nuisance signals can include motion regressors, HRF derivatives not being modeled as tasks, and other sources of noise. Detrending/high-pass filtering is accomplished by adding DCT bases to the nuisance matrix; see the parameters hpf and DCT. Do not add spike regressors for scrubbing to the nuisance matrix. Rather, provide these in scrub so that their corresponding timepoints are also removed from the BOLD data after nuisance regression.
design_canonical	TO DO
verbose	1 (default) to print occasional updates during model computation; 2 for occasional updates as well as running INLA in verbose mode (if Bayes), or 0 for no printed updates.
meanTol, varTol	Tolerance for mean and variance of each data location. Locations which do not meet these thresholds are masked out of the analysis. Default: 1e-6 for both.

Value

An object of class "mGLM": a list with elements

brainstructures

data.frame summarizing the spatial features of each brain structure modeled.

fields

data.frame with the name, related task, and HRF_order of each field.

Connectome Workbench Requirement

This function uses a system wrapper for the 'wb_command' executable. The user must first download and install the Connectome Workbench, available from https://www.humanconnectome.org/software/get-connectome-workbench .

hrf documentation built on April 3, 2025, 10:36 p.m.