fix typos diffusion-tractography.md

docs/tutorial/diffusion-tractography.md

@@ -3,15 +3,13 @@
 
 ## Diffusion-weighted MRI preprocessing.
 
-This page demonstrates common steps used to perform diffusion tractography analyses on brainlife.io. The goal of this tutorial is to show you how to process anatomical and diffusion data to generate **tractograms**, **segment major white matter tracts**, and **map microstructural measures** to the major white matter tracks. This tutorial will use a variety of brainlife.io applications to [generate tractograms](https://brainlife.io/app/5aac2437f0b5260027e24ae1), [segment white matter tracts](https://brainlife.io/app/5cc73ef44ed9df00317f6288), and [map microstructural measures](https://brainlife.io/app/5cc210ce4ed9df00317f61cf) to these tracts.
+This page demonstrates common steps used to perform diffusion tractography analyses on brainlife.io. The goal of this tutorial is to show you how to process anatomical and diffusion data to [generate tractograms](https://brainlife.io/app/5aac2437f0b5260027e24ae1), [segment white matter tracts](https://brainlife.io/app/5cc73ef44ed9df00317f6288), and [map microstructural measures](https://brainlife.io/app/5cc210ce4ed9df00317f61cf) for the major white matter tracks.
 
 This tutorial will use a combination of skills developed in the [Introduction tutorial](https://brainlife.io/docs/tutorial/introduction-to-brainlife/), the [Anatomical Preprocessing tutorial](https://brainlife.io/docs/tutorial/t1w-preprocessing/), and the [Diffusion MRI Preprocessing tutorial](https://brainlife.io/docs/tutorial/diffusion-preprocessing/) you recently completed. If you haven't read our introduction to brainlife, or if you're not comfortable staging, processing, archiving, and viewing data on brainlife.io, please go back through that tutorial before beginning this one.
 
 ### 1. Anatomical preprocessing.
 
-The first step of diffusion tractography often involves processing the anatomical images. In order to track in a biologically-informed manner and to extract major white matter tracts, we must have both of our anatomical (T1w or T2w) images and our diffusion MRI images **aligned**. One way we can make this easier for [QSIPrep](https://brainlife.io/app/5dc1c2e57f55b85a93bd3021) is by aligning the anatomical images in such a way that the center of the brain is centered in the image. We refer to this as **ACPC-aligned**, as we are aligning the data to the **anterior commissure-posterior comissure plane**. This is the first step in dMRI preprocessing, and it is typically done with the [FSL Anat (T1w)](https://brainlife.io/app/5e3c87ae9362b7166cf9c7f4) app. We will then need to generate cortical and white matter surfaces and brain region parcellations using [Freesurfer](https://brainlife.io/app/5fe1056057aacd480f2f8e48). These will be used for segmenting the major white matter tracts following tractography. Once we've processed our anatomical image, we can move on to diffusion MRI preprocessing.
-
-The first step of diffusion preprocessing often involves processing the anatomical images. In order to guarantee that any generalizations regarding location made from the preprocessed diffusion data is anatomically-informed, we must have both of our anatomical (T1w or T2w) images and our diffusion MRI images **aligned**. One way we can make this easier for [QSIPrep](https://brainlife.io/app/5dc1c2e57f55b85a93bd3021) is by aligning the anatomical images in such a way that the center of the brain is centered in the image. We refer to this as **ACPC-aligned**, as we are aligning the data to the **anterior commissure-posterior comissure plane**. This is the first step in dMRI preprocessing, and it is typically done with the [FSL Anat (T1w)](https://brainlife.io/app/5e3c87ae9362b7166cf9c7f4) app. Once we've centered our anatomical image, we can move onto diffusion MRI preprocessing.
+The first step of diffusion tractography often involves processing the anatomical images. To track in a biologically-informed manner, and to extract major white matter tracts, we must have both anatomical (T1w or T2w) images and diffusion MRI images **aligned**. One way we can make this easier for [QSIPrep](https://brainlife.io/app/5dc1c2e57f55b85a93bd3021) is by aligning the anatomical images so that the center of the brain is centered in the image. We refer to this as **ACPC-aligned**, as we are aligning the data to the **anterior commissure-posterior comissure plane**. This is the first step in dMRI preprocessing, and it is typically done with the [FSL Anat (T1)](https://brainlife.io/app/5e3c87ae9362b7166cf9c7f4) app. We will then need to generate cortical and white matter surfaces and brain region parcellations using [Freesurfer](https://brainlife.io/app/5fe1056057aacd480f2f8e48). These will be used for segmenting the major white matter tracts following tractography. Once we've processed our anatomical image, we can move on to diffusion MRI preprocessing.
 
 ### 2. Diffusion preprocessing
 
@@ -23,7 +21,7 @@ On top of these issues, dMRI data is sensitive to other artifacts and non-regula
 
 Finally, once the dMRI data is preprocessed and cleaned, [QSIPrep](https://brainlife.io/app/5dc1c2e57f55b85a93bd3021) will align the dMRI data to the anatomical data. This will ensure that any analyses we do with the dMRI data will be anatomically-informed and biologically-relevant.
 
-Useful information about the preprocessing pipeline that [QSIPrep](https://brainlife.io/app/5dc1c2e57f55b85a93bd3021) is designed to run -- QSIPrep -- can be found in this [original Nature Methods paper](https://www.nature.com/articles/s41592-021-01185-5).
+Useful information about the [QSIPrep](https://brainlife.io/app/5dc1c2e57f55b85a93bd3021) preprocessing pipeline can be found in this [original Nature Methods paper](https://www.nature.com/articles/s41592-021-01185-5).
 
 ### 3. Diffusion modeling & anatomically-informed tractography.
 
@@ -33,7 +31,7 @@ The first step is to fit models of diffusion at each location in the dMRI image
 
 Once we know the direction of water movement using the CSD model, we can then perform **diffusion tractography** to map the underlying organized white matter. Diffusion tractography *sews* together regions with common directions of water movement into streamlines that provide evidence for organized, myelinated white matter. These operations can be done millions of times across the entire brain to form **tractograms**. There are many algorithms for doing this that fall into two main categories: **deterministic** and **probabilistic**. **Deterministic** algorithms work by strictly following the directions of water movement, while **probabilistic** algorithms infer a probability of different directions of water movement at any given location. Deterministic tractography tends to be an overly conservative representation of the white matter, as modeling is never perfectly accurate. Probabilistic tractography tends to provide *hairy* streamline representations, as the model allows for a probability of different directions of water movement at any given location. Recently, it was discovered that combining both algorithms, or **ensembling** them, provides the most anatomically-accurate tractograms.
 
-On brainlife.io, we have many options for performing tractography! For this tutorial, we will focus on anatomically-constrained tractography, using the [mrtrix3 - WMC Anatomically Constrained Tractography (ACT) ](https://brainlife.io/app/5e9dced9f1745d6994f692c0) app, which restricts streamline representations to those that are biologically-plausible (i.e. not crossing CSF or gray matter)! Within this app, both the CSD and DTI models will be fit to the diffusion data and returned as outputs!
+On brainlife.io, we have many options for performing tractography! For this tutorial, we will focus on anatomically-constrained tractography, using the [mrtrix3 - WMC Anatomically Constrained Tractography (ACT)](https://brainlife.io/app/5e9dced9f1745d6994f692c0) app, which restricts streamline representations to those that are biologically-plausible (i.e. not crossing CSF or gray matter)! Within this app, both the CSD and DTI models will be fit to the diffusion data and returned as outputs!
 
 More information on ensemble tractography can be found in this [PLOS Computational Biology article](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004692) paper. More information on **ACT** can be found in this [Neuroimage publication](https://www.ncbi.nlm.nih.gov/pubmed/22705374).
 
@@ -78,7 +76,7 @@ Now, let's get to work! The following steps of this tutorial will show you how t
 
 Your data should now be staged for processing and archived in your projects page! You're now ready to move onto the first step: preprocessing of the anatomical (T1w) image!
 
-### ### Preprocess anatomical (T1w) data using FSL.
+### Preprocess anatomical (T1w) data using FSL.
 
 1. On the 'Process' tab, click 'Submit App' to submit a new application.
     * In the search bar, type 'FSL Anat (T1)'