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Contents

  1. Introduction

    Contents

    1. Overview - FMRIB's ICA-based Xnoiseifier - FIX v1.061 beta
  2. User Guide
  3. FAQ

Overview - FMRIB's ICA-based Xnoiseifier - FIX v1.061 beta

FIX attempts to auto-classify ICA components into "good" vs "bad" components, so that the bad components can be removed from the 4D FMRI data. FIX is intended to be run on single-session MELODIC ICA output. See example raw data movies showing the (potentially huge) effect of FIX cleanup. This beta-version of FIX is a set of R, MATLAB and shell scripts and hence requires you to have various other software than just FSL - and for now is not bundled as part of FSL. If you use FIX, please cite these papers:

1. G. Salimi-Khorshidi, G. Douaud, C.F. Beckmann, M.F. Glasser, L. Griffanti S.M. Smith. Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers. NeuroImage, 90:449-68, 2014

2. L. Griffanti, G. Salimi-Khorshidi, C.F. Beckmann, E.J. Auerbach, G. Douaud, C.E. Sexton, E. Zsoldos, K. Ebmeier, N. Filippini, C.E. Mackay, S. Moeller, J.G. Xu, E. Yacoub, G. Baselli, K. Ugurbil, K.L. Miller, and S.M. Smith. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging. NeuroImage, 95:232-47, 2014

The latest version (1.06) can now be run without MATLAB, using either the supplied precompiled-matlab binaries, or with Octave. The other change from v1.05 is a change in the top-level meta-classifier, which gives a tiny average improvement in classification accuracy. No need to rerun feature generation from v1.05 for use in v1.06, but the old trained-weights files cannot be used with v1.06 (and any custom trained-weights files will need regenerating). (Update: v1.061 has a tiny change from 1.06, in that it can work with the newest flavours of R that had started to create problems for 1.06. 1.061 can be used with features from 1.05-1.06 and training files from 1.06)

For FIX to work well, it is very important that it is run using good "training data". While a few example trained-weights files are supplied with FIX, for major studies we would strongly recommend training FIX on your own study data (see below for more details). You can find example training-input data, including our hand-labellings, here (note that you do not need this example training-input data in order to run FIX; you just need the download linked below, which includes several trained-weights files).

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