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