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.

nilearn.glm.first_level.spm_dispersion_derivative

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

Implement the SPM dispersion derivative HRF model.

Parameters:

trfloat

Repetition time, in seconds (sampling period).

oversamplingint, default=50

Temporal oversampling factor in seconds.

time_lengthfloat, default=32

HRF kernel length, in seconds.

onsetfloat, default=0

Onset of the response in seconds.

Returns:

dhrfarray of shape(length / tr * oversampling), dtype=float

dhrf sampling on the oversampled time grid