fmri.stimulus: Linear Model for FMRI Data
In neuroconductor-releases/fmri: Analysis of fMRI Experiments

Description Usage Arguments Details Value Author(s) References See Also Examples

Create the expected BOLD response for a given task indicator function.

  fmri.stimulus(scans = 1, onsets = c(1), durations = c(1), TR = 2,
                times = FALSE, sliceorder = NULL,
                type = c("canonical", "gamma", "boxcar", "user"),
                par = NULL, scale = 10, hrf = NULL, verbose = FALSE)

`scans`	number of scans
`onsets`	vector of onset times (in scans)
`durations`	vector of duration of ON stimulus in scans or seconds (if `!is.null(times)`)
`TR`	time between scans in seconds (TR)
`times`	onset times in seconds. If present `onsets` arguments is ignored.
`sliceorder`	order of slice acquisition. If provided separate expected bold responses are calculated for the slices taking slice acquisition times into account. Default: no slice timing.
`type`	One of `"canonical"`, `"gamma"`, `"boxcar"`, `"user"`
`par`	Possible parameters to the HRF.
`scale`	Temporal undersampling factor
`hrf`	If `type` is `"user"` this should be a function evaluating the hemodynamic response function
`verbose`	Report more if `TRUE`

The functions calculates the expected BOLD response for the task indicator function given by the argument as a convolution with the hemodynamic response function.

If sliceorder provides an ordering of slice acquisitions a matrix of expected Bold responses with colums corresponding to the slice number is computed.

For type is "canonical" the latter is modelled by the difference between two gamma functions as given in the reference (with the defaults for a1, a2, b1, b2, cc given therein):

(x/d1)^a1 * exp(-(x - d1)/b1) - c * (x/d2)^a2 * exp(-(x - d2)/b2)

The parameters a1, a2, b1, b2, cc of this function can be changed through the argument par in this order.

Other choices are a simple gamma function

\frac{1}{kτ_h (k-1)!} ≤ft( \frac{t}{τ_h} \right)^k \exp ≤ft( - \frac{t}{τ_h} \right)

or the "boxcar" stimulus, or a user defined function hrf.

The dimension of the function value is set to c(scans, 1).

If !is.null(times) durations are specified in seconds.

Vector with dimension c(scans, 1) or a matrix with dimension c(scans, number of slices).

Karsten Tabelow tabelow@wias-berlin.de, Joerg Polzehl polzehl@wias-berlin.de

Worsley, K.J., Liao, C., Aston, J., Petre, V., Duncan, G.H., Morales, F., Evans, A.C. (2002). A general statistical analysis for fMRI data. NeuroImage, 15:1-15.

Polzehl, J. and Tabelow, K. (2007) fmri: A Package for Analyzing fmri Data, R News, 7:13-17 .

fmri.design, fmri.lm

  # Example 1
  hrf <- fmri.stimulus(107, c(18, 48, 78), 15, 2)
  z <- fmri.design(hrf, 2)
  par(mfrow=c(2, 2))
  for (i in 1:4) plot(z[, i], type="l")