
v 0.0.9 (Unreleased)
--------------------

Preproc workflow
~~~~~~~~~~~~~~~~

- Added the ability to supply fieldmap images that can be used to unwarp
  distortions caused by susceptibility regions. This uses FSL's ``topup`` and
  ``applytopup`` utilities. The images you should provide aren't actually
  traditional "fieldmaps", but rather images with normal and reversed phase
  encoding directions, from which a map of the distortions can be computed.
  See the new experiment option ``fieldmap_template``.


Model workflow
~~~~~~~~~~~~~~

- Added the ability to include additional nuisance variables in the model.
  This can now include eigenvariates of deep white matter timeseries and the
  mean signal from across the whole brain. This involves the new experiment
  options ``wm_components`` and ``confound_sources``.

- Made the inclusion of artifact indicator vectors in the design matrix optional.
  See the new experiment option ``remove_artifacts``.

- Made some changes to the model summary node to use memory more efficiently.
  The model summary code should now use a similar amount of memory as the
  ``film_gls`` model fitting process.


v 0.0.9 (Unreleased)
--------------------

Preproc workflow
~~~~~~~~~~~~~~~~

- Added the ability to supply fieldmap images that can be used to unwarp
  distortions caused by susceptibility regions. This uses FSL's ``topup`` and
  ``applytopup`` utilities. The images you should provide aren't actually
  traditional "fieldmaps", but rather images with normal and reversed phase
  encoding directions, from which a map of the distortions can be computed.
  See the new experiment option ``fieldmap_template``.


Model workflow
~~~~~~~~~~~~~~

- Added the ability to include additional nuisance variables in the model.
  This can now include eigenvariates of deep white matter timeseries and the
  mean signal from across the whole brain. This involves the new experiment
  options ``wm_components`` and ``confound_sources``. This change requires that
  you rerun the preproc workflow before running the model workflow after updating
  lyman.

- Made the inclusion of artifact indicator vectors in the design matrix optional.
  See the new experiment option ``remove_artifacts``.

- Made some changes to the model summary node to use memory more efficiently.
  The model summary code should now use a similar amount of memory as the
  ``film_gls`` model fitting process.

Add note about required rerunning
Add note about required rerunning