simulate_fmri_dataset: Simulate Complete fMRI Dataset

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

Simulate Complete fMRI Dataset

Description

This function simulates a complete fMRI dataset by combining task-related signals with realistic noise. It returns both the clean signals and the noisy data.

Usage

simulate_fmri_dataset(
  ncond,
  nreps = 12,
  TR = 1.5,
  snr = 0.5,
  hrf = HRF_SPMG1,
  seed = NULL
)

Arguments

ncond	Number of conditions to simulate
nreps	Number of repetitions per condition (default is 12)
TR	Repetition time in seconds (default is 1.5)
snr	Signal-to-noise ratio (default is 0.5)
hrf	Hemodynamic response function to use (default is HRF_SPMG1)
seed	Optional seed for reproducibility (default is NULL)

Value

A list containing:

• clean: The simulated signals without noise (from sim_ts)

• noisy: The signals with added noise

• noise: The simulated noise component

• onsets: Trial onset times

• conditions: Condition labels for each trial

Examples

# Simulate a dataset with 3 conditions
data <- simulate_fmri_dataset(ncond = 3, TR = 2, snr = 0.5)

# Plot clean and noisy data
par(mfrow = c(2,1))
matplot(data$clean$mat[,1], data$clean$mat[,-1], type = "l",
        main = "Clean Signal", xlab = "Time (s)", ylab = "BOLD")
matplot(data$noisy[,1], data$noisy[,-1], type = "l",
        main = "Noisy Signal", xlab = "Time (s)", ylab = "BOLD")

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