From 72152dbf720a91347709d4696c1288b27c0d7c7f Mon Sep 17 00:00:00 2001 From: cprovins Date: Thu, 26 Jan 2023 14:30:40 +0100 Subject: [PATCH] enh : complete information about the sections about and methods --- docs/users/howto_read_fmriprep_visual_report.md | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/docs/users/howto_read_fmriprep_visual_report.md b/docs/users/howto_read_fmriprep_visual_report.md index 331b2c7..07d06b0 100644 --- a/docs/users/howto_read_fmriprep_visual_report.md +++ b/docs/users/howto_read_fmriprep_visual_report.md @@ -169,9 +169,6 @@ The brain edge (or crown) ROI (green contour) picks signals outside but close to ### Variance explained by t/a CompCor components The figure displays the cumulative variance explained by components for each of four CompCor decompositions (left to right: anatomical CSF mask, anatomical white matter mask, anatomical combined mask, temporal). Dotted lines indicate the minimum number of components necessary to explain 50%, 70%, and 90% of the variance in the nuisance mask. By default, only the components that explain the top 50% of the variance are saved. The number of components that must be included in the model in order to explain some fraction of variance in the decomposition mask can be used as a feature selection criterion for confound regression. - -* Good: -* Bad: ### BOLD summary @@ -206,11 +203,12 @@ What you’re looking at: * Link to documentation on confounds: ## About +This section is a textual summary, containing the version of fMRIPrep, which command was run and the dates when the data were preprocessed. It is good to check that all of this information is as expected. ## Methods - -## Errors +This section provides a boilerplate describing in detail the preprocessing of the images. We kindly ask to report results preprocessed with fMRIPrep using that boilerplate. The latter is available in three languages (HTML, Markdown and Latex) to faciliate integration in manuscripts. +## Errors This section tells you whether fMRIPrep encountered any problems during the preprocessing. Note that “errors” refers only to problems in running fMRIPrep, and NOT problems with the quality of the resulting images. This section won’t flag participants in which fMRIPrep was able to successfully run to completion but yielded poor results, or in which the input data was of lower-than-desirable quality. ## Things that aren’t an issue