Amherst FSL Workshop 2018
Click here to register for the workshop! Day 1 is June 1st, and Day 2 is June 8th. Customized videos and exercises will be provided during the lectures and practicals.
Below is an annotated agenda for the workshop. This page will be updated during the month of May as more instructional videos are uploaded to help attendees prepare for the course.
To prepare for the course, do the following steps:
1. Get Started with Unix
This workshop requires you to be familiar with Unix. Watch this playlist for an introduction to Unix, and go through the tutorials located here. It is also recommended that you install Xcode from the Apple Store. (This makes it easier to view and edit scripts.)
2. Install FSL
Use this link to install FSL. Follow the instructions for downloading and installing FSL on a Macintosh. A tutorial video for installing FSL and testing your installation can be found here.
3. Download the Dataset
We will be using this dataset from openneuro.org for the practicals. This dataset uses the Flanker task, a robust measure of cognitive control.
4. Download Programs and Scripts
Some of the practical sessions require downloading an application or analysis script. Here is a list of links to the relevant applications and analysis scripts, which can also be found in the agenda below.
- MRIcroGL and a sample dataset: Used for converting DICOM to NIFTI files.
- make_FSL_Timings.sh: A script for converting the timing files from openneuro into timing files that can be read by FSL.
- run_1stLevel_Analysis.sh: A script for running 1st level preprocessing and statistical analysis for each subject.
Day 1: fMRI Fundamentals and an Introduction to FSL
Agenda
(9:30am-10:00am) Unix essentials (Practical, optional)
This session will review Unix commands and concepts used in this course (download this demo script to follow along):
- The shell
- Navigating directories and files
- Environmental variables
- Commands and options (or “switches”)
- Shell scripts (in particular, loops and conditionals)
- See the Unix glossary page for a list of basic Unix terms.
- Please see this playlist for an introduction to the Unix terminal, as well as the Surrey Unix tutorial. I also recommend downloading TextWrangler for editing shell scripts.
(10:00am-11:00am) Review of fMRI Data Processing and Analysis (Lecture)
This will be a brief overview of what is done with fMRI data from start to finish in a typical pipeline. This lecture will cover:
- Hemodynamics and the BOLD signal
- The BOLD signal and linearity
- Understanding preprocessing: motion correction, registration, normalization, and smoothing
- From scanner to computer: Converting DICOM files to NIFTI with MRIcroGL (exercise dataset can be downloaded here)
(11:00am-12:00pm) Preprocessing the individual subject (Practical)
This first practical will be a guided hands-on tutorial about how to process fMRI data (Video). We will review the following topics:
- Overview of the GUI
- Brain extraction / skull stripping
- Registration of T1 and T2-weighted data
- Boundary-based registration
- User options: Slice timing correction, temporal derivatives, and smoothing size
- Troubleshooting preprocessing failures
(1:00pm-2:15pm) First-level analysis and the general linear model (Lecture & Practical)
How to set up the GLM for an individual subject and generate parameter estimates (Video).
- Overview of the GLM
- How the GLM relates to fMRI data
- Beta values, parameter estimates, and variability
- Design matrices
- Custom timing files, and how to make OpenNeuro timing files compatible with FSL. Download the timing formatting script here.
(2:15pm-3:00pm) Scripting your analysis (Practical)
Automating analyses is an indispensable skill for the neuroimaging researcher. This practical will introduce the power of loops, which will save you countless hours and reduce the probability of error (Video). The analysis script can be downloaded here.
- Review of shell scripting
- Saving the analysis script from the GUI
- Editing the .fsf file
- Looping your analysis over subjects
(3:00pm-4:00pm) General Q&A*
This is an opportunity to ask questions about any of the topics covered during the day.
*Any issues with FSL installation will also be addressed during this session. A tutorial video will be sent out ahead of the workshop about how to install FSL. If you have any issues, please let me know about them beforehand.
Day 2: Group-Level Analysis, scripting, & advanced topics
Agenda
(10:00am-11:15am) Group-level analysis (Lecture & Practical)
An overview of how to set up group-level analyses, as well as caveats to be aware of. The lecture will cover the basic mechanisms of group analysis, and correction issues unique to fMRI data. We will also briefly discuss the findings of Eklund et al. (2016).
- Second-level vs. third-level analysis
- Setting up group-level analyses
- T-tests and F-tests: How to set them up and when to use them
- Correction mechanisms: FWE, FDR, and cluster-forming thresholds
(11:15am-12:00pm) FSLeyes and viewing results (Practical)
We will tour FSL’s fsleyes data visualization tool, which is useful for understanding fMRI data conceptually – for example, the connection between the canonical HRF and beta weights. A playlist about FSLeyes can be found here for review outside of the workshop.
- Fsleyes – the FSL data visualization tool
- Overlays, underlays, and thresholds
- Atlases
- FEAT mode and cluster analysis
(1:00pm-2:00pm) Region of Interest (ROI) analysis (Lecture & Practical)
This expands upon the group-level analysis lecture by demonstrating different methods for performing inferential statistics.
- Anatomical vs. Spherical ROIs
- Testing for double dissociations
- ROI analysis with featquery and fslstats
(2:00pm-3:00pm) FSL’s Tract-Based Spatial Statistics (TBSS) (Lecture & Practical)
FSL's TBSS package allows you to do Diffusion Tensor Imaging (DTI) analysis.
- Overview of DTI
- bvals and bvecs
- Preprocessing DTI data and fitting tensors
- Post-processing of DTI data
- Group analysis of DTI data
(3:00pm-4:00pm) General Q&A
Please fill out the feedback form here at the end of the workshop!