FEAT Extras Practical

This practical contains an overview of some advanced analysis methods available in FEAT. It leads you through some of the more advanced usage and concepts in both single-session and higher-level FEAT analyses. Feel free to do the latter two sections in a different order if you are particularly interested in any of them.


Custom Waveforms
An example of the options for setting up first-level FEAT analyses with simple designs that do not require timing files.
HRF Basis Functions
Create and use basis functions to model more general / flexible HRF shapes.

Custom Waveforms

It is possible to specify EVs in FEAT using Custom Waveforms. Here, a simulated dataset has been generated with some event-related conditions to model.

cd ~/fsl_course_data/fmri_extras/custom_waveforms

Open FEAT (Feat & [or Feat_gui & on Mac]) and follow the instructions below.

HRF Basis Functions

This section shows you how basis functions can be setup and used in FEAT. The dataset we will use is a jittered single-event experiment with 200 time points. The stimulus is heat applied for 3 seconds with an average inter-stimulus interval of 70 secs. We will only analyze one slice to allow for quick processing.

cd ~/fsl_course_data/fmri_extras/flobs
Feat &

To start with we will analyze the dataset assuming a fixed Gamma HRF (no basis functions) and then compare the results with a set of the optimal linear basis functions.

We will now process the same data using FMRIB's Linear Optimal Basis Set (FLOBS) and compare the results. Kill and restart Feat, and then follow the instructions below.

The End.