Linear Model for FMRI Data

Description

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

Usage

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

Arguments

stimulus

matrix containing expected BOLD repsonse(s) for the linear model as columns

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 tabelow@wias-berlin.de

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

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  # 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")