tedana.gscontrol.gscontrol_mmix

gscontrol_mmix(optcom_ts, mmix, mask, comptable, ref_img)[source]

Perform global signal regression.

Parameters:
  • optcom_ts ((S x T) array_like) – Optimally combined time series data
  • mmix ((T x C) array_like) – Mixing matrix for converting input data to component space, where C is components and T is the same as in optcom_ts
  • mask ((S,) array_like) – Boolean mask array
  • comptable ((C x X) pandas.DataFrame) – Component metric table. One row for each component, with a column for each metric. The index should be the component number.
  • ref_img (str or img_like) – Reference image to dictate how outputs are saved to disk

Notes

This function writes out several files:

Filename Content
sphis_hik.nii T1-like effect
hik_ts_OC_T1c.nii T1-corrected BOLD (high-Kappa) time series
dn_ts_OC_T1c.nii Denoised version of T1-corrected time series
betas_hik_OC_T1c.nii T1 global signal-corrected components
meica_mix_T1c.1D T1 global signal-corrected mixing matrix