diff --git a/docs/pipeline.md b/docs/pipeline.md
index 29f67aa..aaf4b2b 100644
--- a/docs/pipeline.md
+++ b/docs/pipeline.md
@@ -80,7 +80,7 @@ In working with ABCD data, we have found that a respiratory artifact is produced
 
 #### 3. DBP Motion censoring
 
-Our motion censoring procedure is used for performing the standard pre-processing and for the final construction of parcellated timeseries.  For standard pre-processing, data are labeled as "bad" frames if they exceed an FD threshold of 0.3 mm.  Such "bad" frames are removed when demeaning and detrending, and betas for the denoising are calculated using only the "good" frames. For band-pass filtering, interpolation is used initially to replace the "bad" frames and the residuals are extracted from the denoising GLM.  In such a way, standard pre-processing of the timeseries only uses the "good" data but avoids potential aliasing due to missing timepoints.  After motion censoring, timepoints are further censored using an outlier detection approach. Both a mask including outlier detection and a mask without outlier detection are created. [These masks](https://collection3165.readthedocs.io/en/stable/derivatives/#7-motion-mat-file) are HDF5 compatible .MAT files, which contain temporal masks from 0 ("No censoring") to 0.5 FD thresholds in steps of 0.01. 
+Our motion censoring procedure is used for performing the standard pre-processing and for the final construction of parcellated timeseries.  For standard pre-processing, data are labeled as "bad" frames if they exceed an FD threshold of 0.3 mm.  Such "bad" frames are removed when demeaning and detrending, and betas for the denoising are calculated using only the "good" frames. For band-pass filtering, interpolation is used initially to replace the "bad" frames and the residuals are extracted from the denoising GLM.  In such a way, standard pre-processing of the timeseries only uses the "good" data but avoids potential aliasing due to missing timepoints.  After motion censoring, timepoints are further censored using an outlier detection approach. Both a mask including outlier detection and a mask without outlier detection are created. [These masks](https://collection3165.readthedocs.io/en/stable/derivatives/#7-motion-mat-file) are HDF5 compatible .MAT files, which contain temporal masks from 0 ("No censoring") to 0.5 mm FD thresholds in steps of 0.01 mm. 
 
 #### 4. DBP Generation of parcellated timeseries for specific atlases
 
diff --git a/docs/release_notes.md b/docs/release_notes.md
index f9cba96..427e4ff 100644
--- a/docs/release_notes.md
+++ b/docs/release_notes.md
@@ -8,7 +8,7 @@ Note: Clicking any link within the readthedocs site will not open a new web brow
 
 The ABCC houses a community-shared and continually updated ABCD neuroimaging dataset available under Brain Imaging Data Structure (BIDS) standards. Source data are converted to BIDS from the [NIMH Data Archive (NDA) share of ABCD fast-track data](https://nda.nih.gov/edit_collection.html?id=2573). Only data that passed the Data Analysis Imaging Center (DAIC) quality control are included. 
 
-Currently, the ABCD-BIDS Community Collection (ABCC) from the Developmental Cognition and Neuroimaging (DCAN) Labs contains a regularly updated dataset of ABCD Brain Imaging Data Structure (BIDS) version 1.2.0 pipeline inputs and derivatives. Source data are currently comprised of all the ABCD Study participants baseline year 1 arm 1 DICOM imaging data that passed initial acquisition quality control from the ABCD Data Analysis and Informatics Center (DAIC) and were processed by DCAN Labs.
+Currently, the ABCD-BIDS Community Collection (ABCC) from the Developmental Cognition and Neuroimaging (DCAN) Labs contains a regularly updated dataset of ABCD Brain Imaging Data Structure (BIDS) version 1.2.0 pipeline inputs and derivatives. Source data are currently comprised of all the ABCD Study participants baseline year 1 arm 1 DICOM imaging data that passed initial acquisition quality control from the ABCD Data Analysis and Informatics Center (DAIC) and were processed by DCAN Labs. Per task, the first two bold runs that passed QC were pulled and converted to BIDS.
 
 The version 1.0.0 release focuses on anatomical and resting-state fMRI derivative data. Version 2.0.0 will add new derivatives including diffusion and task fMRI deriative data.