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_time_derivative#

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

Implementation of the SPM time derivative hrf (dhrf) model

Parameters
trfloat

Scan repeat time, in seconds.

oversamplingint, optional

Temporal oversampling factor. Default=50.

time_lengthfloat, optional

hrf kernel length, in seconds. Default=32.

onsetfloat, optional

Onset of the response in seconds. Default=0.

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

dhrf sampling on the provided grid