EMC2 (version 3.2.0)

plot_design_fmri: Plot fMRI Design Matrix

Description

This function creates a visualization of an fMRI design matrix, showing the temporal evolution of regressors over time. It can handle various input formats and provides options to customize the visualization.

Usage

plot_design_fmri(
  design_matrix,
  TRs = 100,
  events = NULL,
  remove_nuisance = TRUE,
  subject = 1,
  legend_pos = "bottomleft",
  ...
)

Value

A plot showing the design matrix regressors over time.

Arguments

design_matrix

A design matrix for fMRI analysis. Can be a data frame, matrix, list of matrices, or an object of class 'emc.design'.

TRs

The number of time points (TRs) to plot. Default is 100.

events

A character vector specifying which regressors to plot. If NULL, all non-nuisance regressors will be plotted.

remove_nuisance

Logical indicating whether to remove nuisance regressors (drift terms, polynomial terms, derivatives) from the plot. Default is TRUE.

subject

The subject number to plot. Only applies for list of design matrices. Default is 1.

legend_pos

Position of the legend. Default is "bottomleft".

...

Additional graphical parameters passed to matplot and legend.

Examples

# Example time series
ts <- data.frame(
  subjects = rep(1, 100),
  run      = rep(1, 100),
  time     = seq(0, 99),
  ROI      = rnorm(100)
)
# Create a simple events data frame
events <- data.frame(
  subjects = rep(1, 10),
  run = rep(1, 10),
  onset = seq(0, 90, by = 10),
  condition = rep(c("A", "B"), 5),
  rt = runif(10, 0.5, 1.5),
  accuracy = sample(0:1, 10, replace = TRUE)
)
# Reshape with custom duration for each event_type
reshaped <- reshape_events(events,
                           event_types = c("condition", "accuracy", "rt"),
                           duration = list(condition = 0.5,
                                          accuracy = 0.2,
                                          rt = function(x) x$rt))
design_matrices <-  convolve_design_matrix(
                    timeseries = ts,
                    events = reshaped,
                    covariates = c('accuracy', 'rt'),
                    factors = list(cond = c("condition_A", "condition_B")),
                    contrasts = list(cond = matrix(c(-1, 1))))

# Plot the design matrix
plot_design_fmri(design_matrices)