tedana.workflows.tedana_workflow

tedana_workflow(data, tes, mask=None, mixm=None, ctab=None, manacc=None, strict=False, gscontrol=True, kdaw=10.0, rdaw=1.0, conv=2.5e-05, ste=-1, combmode='t2s', dne=False, cost='logcosh', stabilize=False, filecsdata=False, wvpca=False, label=None, fixed_seed=42, debug=False, quiet=False)[source]

Run the “canonical” TE-Dependent ANAlysis workflow.

Parameters:
  • data (str or list of str) – Either a single z-concatenated file (single-entry list or str) or a list of echo-specific files, in ascending order.
  • tes (list) – List of echo times associated with data in milliseconds.
  • mask (str, optional) – Binary mask of voxels to include in TE Dependent ANAlysis. Must be spatially aligned with data.
  • mixm (str, optional) – File containing mixing matrix. If not provided, ME-PCA and ME-ICA are done.
  • ctab (str, optional) – File containing component table from which to extract pre-computed classifications.
  • manacc (str, optional) – Comma separated list of manually accepted components in string form. Default is None.
  • strict (bool, optional) – Ignore low-variance ambiguous components. Default is False.
  • gscontrol (bool, optional) – Control global signal using spatial approach. Default is True.
  • kdaw (float, optional) – Dimensionality augmentation weight (Kappa). Default is 10. -1 for low-dimensional ICA.
  • rdaw (float, optional) – Dimensionality augmentation weight (Rho). Default is 1. -1 for low-dimensional ICA.
  • conv (float, optional) – Convergence limit. Default is 2.5e-5.
  • ste (int, optional) – Source TEs for models. 0 for all, -1 for optimal combination. Default is -1.
  • combmode ({'t2s', 'ste'}, optional) – Combination scheme for TEs: ‘t2s’ (Posse 1999, default), ‘ste’ (Poser).
  • dne (bool, optional) – Denoise each TE dataset separately. Default is False.
  • cost ({'logcosh', 'exp', 'cube'} str, optional) – Cost function for ICA
  • stabilize (bool, optional) – Stabilize convergence by reducing dimensionality, for low quality data. Default is False.
  • filecsdata (bool, optional) – Save component selection data to file. Default is False.
  • wvpca (bool, optional) – Whether or not to perform PCA on wavelet-transformed data. Default is False.
  • label (str or None, optional) – Label for output directory. Default is None.
Other Parameters:
 
  • fixed_seed (int, optional) – Value passed to mdp.numx_rand.seed(). Set to a positive integer value for reproducible ICA results; otherwise, set to -1 for varying results across calls.
  • debug (bool, optional) – Whether to run in debugging mode or not. Default is False.
  • quiet (bool, optional) – If True, suppresses logging/printing of messages. Default is False.

Notes

This workflow writes out several files, which are written out to a folder named TED.[ref_label].[label] if label is provided and TED.[ref_label] if not. ref_label is determined based on the name of the first data file. For a complete list of the files generated by this workflow, please visit https://tedana.readthedocs.io/en/latest/outputs.html