event_model: Construct an event model

In bbuchsbaum/fmrireg: R package for the anlysis of fmri data

Construct an event model

Description

This function creates an event-based fMRI regression model, represented as a data structure.

Usage

event_model(
  x,
  data,
  block,
  sampling_frame,
  drop_empty = TRUE,
  durations = 0,
  ...
)

Arguments

x	The model specification, typically a formula. The formula should have the following format: response ~ predictor1 + predictor2 + ... + predictorN where response is a numeric vector of fMRI signal values, and predictor1 to predictorN are predictor variables. Each predictor variable should be specified as a function of categorical variables (factors) and/or continuous variables. The functions should have the prefix "hrf", and can be defined using the hrf() function (see hrf documentation for details).
data	A data frame containing the experimental design, with one row per time point and one column per variable used in the model formula. If a categorical variable is used in the formula, it should be a factor in the data frame. The data frame should also contain a column with the fMRI signal values (the response variable).
block	A formula specifying the block structure of the design. This formula should have the format block_var1 + block_var2 + ..., where each block_var is a categorical variable (factor) used to define blocks of time points. The block structure is used to estimate the baseline fMRI signal level separately for each block.
sampling_frame	A sampling frame defining the temporal and block structure of the design. This should be an object of class sampling_frame (see sampling_frame documentation for details).
drop_empty	Logical value indicating whether to drop empty factor levels in the model. If TRUE (default), any factor levels with no observations will be dropped from the model. If FALSE, empty levels will be retained and will receive a coefficient of zero in the model.
durations	A numeric vector specifying the duration (in seconds) of each event in the model. If the model contains block variables, the duration of each block should be specified as well. The length of this vector should be equal to the number of events/blocks in the design. Default value is 0 (no duration).
...	Additional arguments to be passed to methods. Currently not used.

Value

A list containing the following elements:

formula

The formula used to create the model.

design

The design matrix for the model, with one row per time point and one column per predictor variable.

block_indices

A list of indices defining the start and end time points of each block.

baseline

A vector containing the estimated baseline fMRI signal level for each block.

dur

A vector containing the duration (in seconds) of each event or block in the design.

Examples

# Create a data frame with experimental design
event_data <- data.frame(fac=c("a", "B", "A", "B"), onsets=c(1,10,20,80), run=c(1,1,1,1))

# Create a sampling frame with 50-second blocks and a TR of 2 seconds
sframe <- sampling_frame(blocklens=50, TR=2)

# Create an event model using the `onsets` variable as a predictor, 
#  with a separate baseline for each run
evmodel <- event_model(onsets ~ hrf(onsets), data=event_data, block=~run, sampling_frame=sframe)
dmat <- design_matrix(evmodel)

bbuchsbaum/fmrireg documentation built on March 1, 2025, 11:20 a.m.