DP

Tutorials

  • You and Your R - Doing Statistics in Python

    In this post, I will tell you how to do statistics in Python. I’ve been trained in statistics mostly with R, but I do a lot of fMRI analyses in Python and do not really want to switch back and forth.

  • Errors in Medin & Schaffer, 1978

    Today we will simulate experiments on Context Theory of Classification Learning (Medin & Schaffer, 1978). Important differences between simulated and published results will be shown. Dr. Medin kindly confirmed the typos in the paper and asked to publish them somewhere.

  • Three-level analysis with FSL and ANTs in Nipype. Part 3.

    Today we will be setting up level 3 in a 3-level model with FSL and Nipype, using data from Part 1 and copes from Part 2

  • Three-level analysis with FSL and ANTs in Nipype. Part 2.

    Today we will be setting up levels 1 and 2 in a 3-level model with FSL and Nipype, applying transformation matrices from ANTs that we created in Part 1.

  • Three-level analysis with FSL and ANTs in Nipype. Part 1.

    In a series of posts, I plan to talk about how to run the three-level analysis with FSL and ANTs. We will use ANTs for registration, FSL for the analysis itself and nipype for putting everything together. I will be heavily utilizing a code from nipype examples, changing it’s when necessary. Again, this is not an original work, it is rather putting everything together and modifying when it’s appropriate.

  • Brain Extraction with ANTs

    Today we will be talking about how to do a brain extraction on T1 anatomical images. Good brain extraction allows better registration of an anatomical image to a standard template and thus better alignment of the functional data to the standard space. Looking for a good brain extraction tool, I’ve asked on Dr. Jeanette Mumford’s Facebook group, and Dr. Chris Gorgolewski recommended ANTs brain extraction. In this post, I will tell you how to set up and use it.