Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

8.12.15.13. nilearn.glm.first_level.spm_time_derivative

nilearn.glm.first_level.spm_time_derivative(tr, oversampling=50, time_length=32.0, onset=0.0)

Implementation of the SPM time derivative hrf (dhrf) model

Parameters:

tr: float

scan repeat time, in seconds

oversampling: int, optional

temporal oversampling factor, optional

time_length: float, optional

hrf kernel length, in seconds

onset: float, optional

onset of the response in seconds

Returns:

dhrf: array of shape(length / tr, dtype=float)

dhrf sampling on the provided grid