Generate Neural Input Function from Event Timing

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, ...)

# S3 method for class 'Reg'
neural_input(x, start = 0, end = NULL, resolution = 0.33, ...)

Arguments

x

A regressor object containing event timing information

...

Additional arguments passed to methods

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)

Value

A list containing:

time

Numeric vector of time points

neural_input

Numeric vector of input amplitudes at each time point

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

See also

regressor, evaluate.Reg, 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
)