This lesson was developed for a short course on Validating fMRI methods at the University of Leiden. It is aimed to PhD students in biostatistics and medical imaging.
Prerequisites
The lesson should be comprehensive, and shows some core concepts of validating methods. Some prior knowledge of fMRI and R are definitely helpful.
Data
The data for this workshop are the CNP data (UCLA Consortium for Neuropsychiatric Phenomics LA5c Study) - revision 1.0.5, available on openfmri with a PPDL license.
Overview of the lessons:
| Setup | Download files required for the lesson | |
| 00:00 | 1. Working with fMRI data using R |
What is fMRI?
How can I read fMRI data in R? How can I visualise fMRI data with R? |
| 00:20 | 2. Computing functional connectivity. |
What is functional connectivity?
How can I compute functional connectivity between regions with R? |
| 01:00 | 3. Using real data to validate task fMRI. |
What’s with that Eklund paper?
How do we usually assess whether a part in the brain is active during task fMRI? How do we create a random regressor? |
| 01:40 | 4. Simulating connectivity. |
What’s with that paper from Steve Smith?
How can I simulate functional connectivity between regions with R? |
| 02:10 | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.