mne_nirs.experimental_design.make_first_level_design_matrix#
- mne_nirs.experimental_design.make_first_level_design_matrix(raw, stim_dur=1.0, hrf_model='glover', drift_model='cosine', high_pass=0.01, drift_order=1, fir_delays=[0], add_regs=None, add_reg_names=None, min_onset=-24, oversampling=50)[source]#
Generate a design matrix based on annotations and model HRF.
This is a wrapper function for the nilearn [1] function
make_first_level_design_matrix. For detailed description of the arguments see the nilearn documentation at http://nilearn.github.io- Parameters:
- rawinstance of Raw
Haemoglobin data.
- stim_durNumber
The length of your stimulus.
- hrf_model{‘glover’, ‘spm’, ‘spm + derivative’, ‘spm + derivative + dispersion’, ‘glover + derivative’, ‘glover + derivative + dispersion’, ‘fir’, None}, optional
Specifies the hemodynamic response function. Default=’glover’.
- drift_model{‘cosine’, ‘polynomial’, None}, optional
Specifies the desired drift model. Default=’cosine’.
- high_passfloat, optional
High-pass frequency in case of a cosine model (in Hz). Default=0.01.
- drift_orderint, optional
Order of the drift model (in case it is polynomial). Default=1.
- fir_delaysarray of shape(n_onsets) or list, optional
In case of FIR design, yields the array of delays used in the FIR model (in scans). Default=[0].
- add_regsarray of shape(n_frames, n_add_reg) or pandas DataFrame
Additional user-supplied regressors, e.g. data driven noise regressors or seed based regressors.
- add_reg_nameslist of (n_add_reg,) str, optional
If None, while add_regs was provided, these will be termed ‘reg_%i’, i = 0..n_add_reg - 1 If add_regs is a DataFrame, the corresponding column names are used and add_reg_names is ignored.
- min_onsetfloat, optional
Minimal onset relative to frame_times[0] (in seconds) events that start before frame_times[0] + min_onset are not considered. Default=-24.
- oversamplingint, optional
Oversampling factor used in temporal convolutions. Default=50.
- Returns:
- design_matrixDataFrame instance,
Holding the computed design matrix, the index being the frames_times and each column a regressor.
References
