The diffusion signal provides unique, but indirect information about tissue microstructure. In this course, we will examine two main avenues for diffusion analysis: signal representations and tissue models. The former render the signal behavior without any assumptions about the tissue structure and thus produce sensitive but unspecific metrics (e.g. fractional anisotropy from DTI). For models, a theoretical expression of the diffusion signal in a given geometry (assumed to describe the tissue well) is fit to the data and characteristic parameters of the geometry are extracted. This approach should yield more specific metrics but is also more challenging to implement correctly.