event_terms: Extract event terms from a model

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

Extract event terms from a model

Description

Extract the event-related terms from a model object, separating them from baseline or nuisance terms. Event terms represent the experimental conditions and parametric modulators in an fMRI design. For example, in a model with both task events (e.g., stimulus presentations) and baseline components (e.g., drift terms, motion parameters), this function returns only the task-related terms.

Usage

event_terms(x)

Arguments

x	The model object (typically an fmri_model)

Value

A list of event_term objects. Each event_term represents a different component of the experimental design and contains:

• varname: Name of the term (e.g., "stimulus", "rt")

• events: List of event objects (factors or continuous variables)

• event_table: Data frame of event information

• onsets: Event onset times in seconds

• blockids: Run/block identifiers

• durations: Event durations in seconds

See Also

baseline_terms(), fmri_model()

Other model_components: baseline_terms(), term_indices()

Examples

# Create a model with both event and baseline terms
event_data <- data.frame(
  stimulus = factor(c("face", "house", "face", "house")),
  rt = c(0.8, 1.2, 0.9, 1.1),
  onsets = c(1, 10, 20, 30),
  run = c(1, 1, 1, 1)
)

# Create sampling frame
sframe <- sampling_frame(blocklens = 50, TR = 2)

# Create event model
evmodel <- event_model(
  onsets ~ hrf(stimulus) + hrf(rt),
  data = event_data,
  block = ~run,
  sampling_frame = sframe
)

# Create baseline model for drift
bmodel <- baseline_model(
  basis = "bs",
  degree = 3,
  sframe = sframe
)

# Combine into full model
fmodel <- fmri_model(evmodel, bmodel)

# Extract only the event terms
event_terms(fmodel)  # Returns list of stimulus and rt terms

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