What’s new

0.10.0 (February 01, 2022)

New feature release in the 0.10.x series.

This release implements support for BIDS Stats Models 1.0.0-rc1. While we have attempted not to break old-style models, we no longer support them.

0.9.2 (July 21, 2021)

Minor bugfix release in the 0.9.x series.

0.9.1 (April 21, 2021)

Bugfix release in the 0.9.x series. Upgrades pybids and nilearn to latest versions.

0.9.0 (February 26, 2021)

New feature release in the 0.9.x series.

This release added AFNI’s 3dREMLfit for first-level estimation, dropped nistats in favor of nilearn.stats, added test reference outputs, among other minor improvements.

0.8.0 (October 19, 2020)

New feature release in the 0.8.x series.

This release includes a change where events that are not explicitly convolved are modeled with boxcar functions instead of the nistats default.

0.7.1 (October 09, 2020)

Bug-fix release in the 0.7.x series.

This release requires PyBIDS 0.12.2 or higher, fixing various bugs that affected FitLins.

0.7.0 (August 05, 2020)

New feature release in the 0.7.x series. This is an accumulation of changes over several months.

This release requires PyBIDS 0.12 and includes some quite provisional CIFTI-2 support as well as log-likelihood and R^2 maps for assessing goodness of fit.

0.6.2 (December 13, 2019)

Hotfix release.

0.6.1 (December 12, 2019)

Hotfix release.

0.6.0 (December 11, 2019)

New feature release in the 0.6.x series.

This release respects recent changes to the BIDS-StatsModels draft specification to support fixed-effects meta-analysis (FEMA) contrasts, and renames “AutoContrasts” to “DummyContrasts”.

Provisional support for F-tests has been added.

Additional rearchitecting by Dylan Nielson provides significant speedups for large datasets by caching BIDS layout information.

0.5.1 (September 23, 2019)

Bug fix release to work with PyBIDS 0.9.4+.

0.5.0 (July 03, 2019)

This release features significant improvements to reporting and documentation, including a Jupyter notebook to demonstrate usage. Example models are now in the main branch of the repository, and annotated in the documentation.

0.4.0 (May 10, 2019)

This release produces effect, variance, statistic (t or F), Z-score, and p-value maps at every level, and enables smoothing at higher levels if preferred.

Additionally, documentation has been added at https://fitlins.readthedocs.io and versioning/packaging issues have been resolved.

0.3.0 (April 19, 2019)

This release restores reports at the second level and higher, and enables isotropic smoothing with the nistats backend. Reporting has also been refactored to reduce clutter in the outputs.

With thanks to Karolina Finc, Rastko Ciric and Mathias Goncalves for contributions.

0.2.0 (February 1, 2019)

This release marks a substantial refactoring in the wake of BIDS Derivatives RC1, fMRIPrep 1.2.x and pybids 0.7.0.

Reports at second level and higher are currently broken, but we’re at a point where neuroscout is depending on the current code base, the user base is increasing, and it’s worth having a starting point for considering new features.

With thanks to Alejandro de la Vega, Adina Wagner and Yaroslav Halchenko for contributions.

0.1.0 (August 24, 2018)

This release moves FitLins to a Nipype workflow and provides a set of Nipype interfaces for interacting with BIDS Models and the nistats statistical package.

0.0.6 (August 06, 2018)

Hotfix release.

0.0.5 (August 01, 2018)

0.0.4 (July 05, 2018)

0.0.3 (March 9, 2018)

Maintenance release

  • Update grabbit (0.1.1), pybids (0.5.0) (#11)

  • Incorporate nistats/nistats#165 (#13)

  • Update Dockerfile, versioning (#14)

0.0.2 (March 5, 2018)

Hotfix, addressing deployment issues.

0.0.1 (March 5, 2018)

Initial release of FitLins, a BIDS-model fitting BIDS app.