\(\newcommand{L}[1]{\| #1 \|}\newcommand{VL}[1]{\L{ \vec{#1} }}\newcommand{R}[1]{\operatorname{Re}\,(#1)}\newcommand{I}[1]{\operatorname{Im}\, (#1)}\)

Exercises and homework

• Basic Python exercises;

• Numpy exercises:

  • Basic numpy exercises – solution: Basic numpy exercises;

• Arrays, images and plotting:

  • Cameraman exercise – solution: Cameraman solution;
  • Anatomical exercise – solution: Anatomical solution;
  • Find the arteries exercise – solution: Find the arteries solution;

• Vectors, projection and PCA:

  • PCA exercise, with some github practice – PCA exercise – solution: PCA solution;

• Git / github workflow, the Python path:

  • Git workflow exercises;

• Correlation, regression, statistics on brain images:

  • Pearson 1D and 2D function exercise;
  • Correlation in practice;
  • First go at brain activation exercise – solution: First go at brain activation exercise;
  • Voxel correlation exercise – solution: Voxel correlation exercise;
  • Correlation per voxel, in 2D – solution: Correlation per voxel, in 2D;

• Some git, some multiple regression:

  • git quiz;

• Exploring the general linear model:

  • Correlation in practice;
  • Correlation per voxel, in 2D;
  • GLM exercise, with some github practice – Least-squares regression exercise – solution: Least-squares regression exercise;

• Project pitch, ANOVA with the GLM:

  • Dummy coding GLM exercise – Modeling groups with dummy variables exercise – solution: Modeling groups with dummy variables exercise;

• F tests; convolution; project template:

  • Making our own hemodynamic response function – solution: Making our own hemodynamic response function;
  • Predicted neural time course exercise – solution: Predicted neural time course exercise;

• The HRF, modeling and statistical maps:

  • Multiple voxel model homework – Basic linear modeling – solution: Basic linear modeling;

• Multiple comparison correction:

  • GLM and testing exercise;

• Slice timing and motion correction:

  • Slice timing exercise – solution: Slice timing exercise.

• Affine and cross-modality registration:

  • Optimizing rotation exercise – solution: Optimizing rotation exercise;
  • Reslicing with affines exercise – solution: Reslicing with affines exercise.

• Affine transformations:

  • Extra transform exercise – solution: Extra transform exercise;
  • Affine optimization exercise – Affine optimization exercise.

• Cross-subject registration:

  • Applying deformations exercise – solution: Applying deformations exercise.

• Exploring cross-subject registration:

  • Anterior cingulate exercise.

• Scripting using nipype:

  • SPM slice timing exercise – solution: SPM slice timing solution;
  • Scripting of SPM analysis with nipype – solution: nipype_ds114_sub009_t2r1.py.

Extra exercises

• Smoothing exercise – solution: Smoothing exercise.