fmri.stimulus: Convolve a regressor with a hemodynamic response function for...

In PennStateDEPENdLab/dependlab: Useful functions for the UNC Chapel Hill DEPENd Lab (Director: Michael Hallquist)

Convolve a regressor with a hemodynamic response function for fMRI analysis.

Description

Extended from fmri package to allow for continuous-valued regressor, which is passed using the values parameter.

Usage

fmri.stimulus(
  n_vols = 1,
  onsets = c(1),
  durations = c(1),
  values = c(1),
  times = NULL,
  center_values = FALSE,
  rm_zeros = TRUE,
  convolve = TRUE,
  tr = 2,
  ts_multiplier = NULL,
  demean = TRUE,
  convmax_1 = FALSE,
  a1 = 6,
  a2 = 12,
  b1 = 0.9,
  b2 = 0.9,
  cc = 0.35,
  conv_method = "r",
  microtime_resolution = 20
)

Arguments

n_vols	The number of volumes (scans) to be output in the convolved regressor
onsets	A vector of times (in scans) specifying event onsets
durations	A vector of durations (in seconds) for each event
values	A vector of parametric values used as regressor heights prior to convolution
times	A vector of times (in seconds) specifying event onsets. If times are passed in, the onsets argument (which is in scans) is ignored. That is, onsets and times are mutually exclusive.
center_values	Whether to demean values vector before convolution
rm_zeros	Whether to remove zeros from events vector prior to convolution. Generally a good idea since we typically center values prior to convolution, and retaining zeros will lead them to be non-zero after mean centering.
convolve	Whether to convolve the regressor with the HRF. If FALSE, a time series of events, durations, and heights is returned.
tr	The repetition time (sometimes called TR) in seconds
ts_multiplier	A time series of length n_vols that is multiplied against the stimulus before convolution.
demean	Whether to demean the regressor after convolution. Default: TRUE
convmax_1	Whether to rescale the convolved regressor to a maximum height of 1.
a1	The a1 parameter of the double gamma
a2	The a2 parameter of the double gamma
b1	The b1 parameter of the double gamma
b2	The b2 parameter of the double gamma
cc	The cc parameter of the double gamma
conv_method	Method for convolving HRF with stimulus. Either "r" or "cpp". The "r" method uses an FFT-based internal convolution with convolve(x, y, conj=TRUE). The "cpp" method uses an internal C++ function with a loop-based convolution over the vectors. Unfortunately, at present, the C++ approach is noticeably slower since it does not use FFT to obtain the filter.
microtime_resolution	The number of bins between TRs used for calculating regressor values in continuous time

Details

The function also supports mean centering of parametric regressor prior to convolution to dissociate it from stimulus occurrence (when event regressor also in model)

PennStateDEPENdLab/dependlab documentation built on April 10, 2024, 5:15 p.m.