diff --git a/docs/_static/sub-01_task-mixedgamblestask_run-01_bold_carpetplot.svg b/docs/_static/sub-01_task-mixedgamblestask_run-01_bold_carpetplot.svg
deleted file mode 100644
index 15baecf76..000000000
--- a/docs/_static/sub-01_task-mixedgamblestask_run-01_bold_carpetplot.svg
+++ /dev/null
@@ -1,2691 +0,0 @@
-
-
-
-
diff --git a/docs/_static/sub-405_ses-01_task-rest_run-01_desc-carpetplot_bold.svg b/docs/_static/sub-405_ses-01_task-rest_run-01_desc-carpetplot_bold.svg
new file mode 100644
index 000000000..9b06e755a
--- /dev/null
+++ b/docs/_static/sub-405_ses-01_task-rest_run-01_desc-carpetplot_bold.svg
@@ -0,0 +1,2406 @@
+
+
+
diff --git a/docs/outputs.rst b/docs/outputs.rst
index 4329c0ffd..a51d65d26 100644
--- a/docs/outputs.rst
+++ b/docs/outputs.rst
@@ -555,15 +555,18 @@ Some of the estimated confounds are plotted with a "carpet" visualization of the
:abbr:`BOLD (blood-oxygen level-dependent)` time series [Power2016]_.
An example of these plots follows:
-.. figure:: _static/sub-01_task-mixedgamblestask_run-01_bold_carpetplot.svg
+.. figure:: _static/sub-405_ses-01_task-rest_run-01_desc-carpetplot_bold.svg
The figure shows on top several confounds estimated for the BOLD series:
- global signals ('GlobalSignal', 'WM', 'GM'), standardized DVARS ('stdDVARS'),
- and framewise-displacement ('FramewiseDisplacement').
- At the bottom, a 'carpetplot' summarizing the BOLD series.
- The color-map on the left-side of the carpetplot denotes signals located
- in cortical gray matter regions (blue), subcortical gray matter (orange),
- cerebellum (green) and the union of white-matter and CSF compartments (red).
+ global signals ('GS', 'GSCSF', 'GSWM'), DVARS,
+ and framewise-displacement ('FD').
+ At the bottom, a 'carpetplot' summarizing the BOLD series [Power2016]_.
+ The carpet plot rows correspond to voxelwise time series,
+ and are separated into regions: cortical gray matter, deep
+ gray matter, white matter and cerebrospinal fluid, cerebellum
+ and the brain-edge or “crown” [Provins2022]_.
+ The crown corresponds to the voxels located on a
+ closed band around the brain [Patriat2015]_.
Noise components computed during each CompCor decomposition are evaluated according
to the fraction of variance that they explain across the nuisance ROI.
@@ -673,6 +676,10 @@ the following invocation::
and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage. 2018.
doi:`10.1016/j.neuroimage.2017.12.073 `_
+ .. [Patriat2015] Patriat R, EK Molloy, RM Birn, T. Guitchev, and A. Popov. ,Using Edge Voxel Information to
+ Improve Motion Regression for Rs-FMRI Connectivity Studies. Brain Connectivity. 2015.
+ doi:`10.1089/brain.2014.0321 `_.
+
.. [Patriat2017] Patriat R, Reynolds RC, Birn RM, An improved model of motion-related signal
changes in fMRI. NeuroImage. 2017.
doi:`10.1016/j.neuroimage.2016.08.051 `_.