Version 1.7.1 Beta (Sep 30, 2020)¶

New Features

ACPC Alignment. Anterior and Posterior Commissure (ACPC) alignment for anatomical preprocessing is now available. This technique may be beneficial for registration quality, primarily in non-human primate data.
- https://doi.org/10.1016/j.neuroimage.2013.04.127
- https://github.com/Washington-University/HCPpipelines/blob/master/PreFreeSurfer/scripts/ACPCAlignment.sh
Low-pass Filter for Motion Estimates. The ability to run a low-pass filter instead of a notch filter for motion estimate filtering is now available. This filter is adapted from the DCAN Labs filter described in this publication.

Improvements

Speed Increase. The transformation of functional time series data to template space is now parallelizable. Assign multiple CPUs per participant to enable this speed-up.
Motion Estimate Filter Configurability. The filter design of the motion estimate notch and low-pass filters can now be directly configured, if the user wishes to design these filters manually.
Composite Transform. C-PAC now outputs the composite transform from functional (BOLD) space to template space as one warp file. Users can use this file to easily transform their native-space BOLD data to template as needed (if necessary beyond the transforms to template space C-PAC already automatically performs).

Error Fixes

An error that would prevent users from running frequency bandpass filtering without any other nuisance regression strategies has been resolved.

Coming Soon

In addition, the C-PAC Docker and Singularity images, as well as the AWS AMI, have all been updated. These provide a quick way to get started.

And as always, you can contact us here for user support and discussion: https://groups.google.com/forum/#!forum/cpax_forum