Estimate Voxel-wise HRF Basis Coefficients

Fits a GLM to estimate HRF basis coefficients for every voxel.

Usage

estimate_voxel_hrf(Y, events, basis, nuisance_regs = NULL)

Arguments

Y

Numeric matrix of BOLD data (time x voxels).

events

Data frame with onset, duration and condition columns.

basis

HRF object from the fmrihrf package.

nuisance_regs

Optional numeric matrix of nuisance regressors.

Value

A VoxelHRF object containing at least:

coefficients

Matrix of HRF basis coefficients.

basis

The HRF basis object used.

conditions

Character vector of modeled conditions.

Examples

if (FALSE) { # \dontrun{
set.seed(1)
Y <- matrix(rnorm(100), 50, 2)
events <- data.frame(onset = c(5, 25), duration = 1,
                     condition = "A")
basis <- fmrihrf::hrf_gamma()
sframe <- fmrihrf::sampling_frame(blocklens = nrow(Y), TR = 1)
times <- fmrihrf::samples(sframe, global = TRUE)
rset <- fmrihrf::regressor_set(onsets = events$onset,
                               fac = factor(1:nrow(events)),
                               hrf = basis, duration = events$duration,
                               span = 30)
X <- fmrihrf::evaluate(rset, grid = times, precision = 0.1, method = "conv")
coef <- matrix(rnorm(ncol(X) * ncol(Y)), ncol(X), ncol(Y))
Y <- X %*% coef + Y * 0.1
est <- estimate_voxel_hrf(Y, events, basis)
str(est)
} # }