neural_input: Generate Neural Input Function from Event Timing

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

Generate Neural Input Function from Event Timing

Description

Converts event timing information into a neural input function representing the underlying neural activity before HRF convolution. This function is useful for:

Usage

neural_input(x, ...)

Arguments

x	A regressor object containing event timing information
...	Additional arguments passed to methods. Common arguments include: start Numeric; start time of the input function end Numeric; end time of the input function resolution Numeric; temporal resolution in seconds (default: 0.33)

Details

stimulus

Creating stimulus functions for fMRI analysis

modeling

Modeling sustained vs. transient neural activity

inputs

Generating inputs for HRF convolution

visualization

Visualizing the temporal structure of experimental designs

Value

A list containing:

time

Numeric vector of time points

neural_input

Numeric vector of input amplitudes at each time point

See Also

regressor, evaluate.regressor, HRF_SPMG1

Examples

# Create a regressor with multiple events
reg <- regressor(
  onsets = c(10, 30, 50),
  duration = c(2, 2, 2),
  amplitude = c(1, 1.5, 0.8),
  hrf = HRF_SPMG1
)

# Generate neural input function
input <- neural_input(reg, start = 0, end = 60, resolution = 0.5)

# Plot the neural input function
plot(input$time, input$neural_input, type = "l",
     xlab = "Time (s)", ylab = "Neural Input",
     main = "Neural Input Function")

# Create regressor with varying durations
reg_sustained <- regressor(
  onsets = c(10, 30),
  duration = c(5, 10),  # sustained activity
  amplitude = c(1, 1),
  hrf = HRF_SPMG1
)

# Generate and compare neural inputs
input_sustained <- neural_input(
  reg_sustained,
  start = 0,
  end = 60,
  resolution = 0.5
)

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