pySPFM._solvers.debiasing.debiasing_spike

pySPFM._solvers.debiasing.debiasing_spike#

debiasing_spike(hrf, y, estimates_matrix, n_jobs=0, group=False, group_dist=3, non_negative=False)[source]#

Perform voxelwise debiasing with spike model.

Parameters:

  • hrf ((E x T) ndarray) – Matrix containing shifted HRFs in its columns. E stands for the number of volumes times the number of echo-times.

  • y ((T x S) ndarray) – Matrix with fMRI data provided to pySPFM.

  • estimates_matrix ((T x S) ndarray) – Matrix containing the non-zero coefficients selected as neuronal-related.

  • n_jobs (int, optional) – Number of jobs to run in parallel, by default 0

  • group (bool, optional) – Whether to group the spikes or not, by default False

  • group_dist (int, optional) – Minimum number of TRs in between of the peaks found, by default 3

  • non_negative (bool, optional) – Whether to perform non-negative least squares or not, by default False

Returns:

  • beta_out (ndarray) – Debiased activity-inducing signal.

  • fitts_out (ndarray) – Debiased activity-inducing signal convolved with the HRF.

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