fmri.design {fmri}

Linear Model for FMRI Data

Description

Return a design matrix for a linear model with given stimuli and possible polynomial drift terms.

Usage

  fmri.design(stimulus, order = 2, cef = NULL, verbose = FALSE)

Arguments

stimulus

matrix containing expected BOLD response(s) for the linear model as columns or list of expected BOLD responses containing matrices of dimension scans, number of slices as returned by function fmri.stimulus.

order

order of the polynomial drift terms

cef

confounding effects

verbose

Report more if TRUE

Details

The stimuli given in stimulus are used as first columns in the design matrix.

The order of the polynomial drift terms is given by order, which defaults to 2.

Confounding effects can be included in a matrix cef.

The polynomials are defined orthogonal to the stimuli given in stimulus.

Value

design matrix of the linear model

Author(s)

Karsten Tabelow [e-mail], Joerg Polzehl [e-mail]

References

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

See Also

fmri.stimulus, fmri.lm

Examples

  # 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")