v0.0.2

v0.0.2 (June 18, 2014)

Anatomical normalization

• Added ANTS-based volume normalization. This provides substantial
  improvements over the FSL-based normalization that was previously
  used. However, ANTS can be difficult to install, so this is optional
  and off by default. It controled through a variable in the
  project.py file, ants_normalization, which should be either
  True or False. After enabling it, you can use the command-line
  tools as before, and ANTS will be used in run_warp.py and
  run_fmri.py -workflow reg.

Preprocessing workflow

• The artifact detection code now uses robust metrics (median and
  median absolute deviation). Previously, it used mean and standard
  deviation. Importantly, this means that the your intensity
  threshold should be adjusted by a scaling factor to provide a
  similarly stringent threshold. As a general rule of thumb, 1 SD is
  about 1.48 MADs.
• Added white noise spike detection. This is controlled through the
  spike_threshod in the experiment file. It is also in units of
  median absolute deviation. It is None by default, indicating that
  no volumes will be excluded for white noise spikes. Additionally, a
  plot that can be used to diagnose spikes has been added to the
  artifact detection report.
• Changed the derivation of the brain mask. Previously, this mask was
  intensity based (although the intensity threshold was determined
  within a mask output by BET). Now, the Freesurfer segmentation is
  used to define an anatomical brain mask, which is then transformed
  into native run space. This should avoid losing voxels in magnetic
  susceptibility areas like ventral temporal cortex.
• Otherwise updated the preproc report with better summary figures.

Subject-level modelling

• It should now be possible to run the model workflow on task-free
  data (i.e. for functional connectivity analysis) by setting
  "design_name" to None in the experiment file.
• Added computation and reporting of residual tSNR.
• Improved the colormaps used for reporting summary statistics about
  the mode (residual variance, R squared, etc.)
• Improved the plot showing correlations between confound and task
  variables
• Otherwise improved the logic and testing of the model workflow.
• Added to and improved the model report at the fixed effects stage.

Mixed effects workflow

• Updated the mixed effects model reporting and simplified the
  workflow graph.
• The boxplot of COPE effect sizes in the mixed effects report is now
  taken from a sphere (with the same size as in the activation peak
  image) centered at each peak voxel rather than just from the single
  voxel itself.

v0.0.1

Version 0.0.1

This is the first "official" release of lyman. From this point, I will try to move to a relatively-frequent incremental release system so that it is easier to install lyman and figure out what version corresponds to an analysis.