1. Introduction

The chapter delves into the analysis of Magnetic Resonance Imaging (MRI) data, focusing on four main modalities: functional MRI (fMRI), diffusion-weighted MRI (dMRI), Multi-Parameter Mapping (MPM), and inversion recovery MRI (IR-MRI). It begins with an introduction to the physics of MRI, explaining the image formation process and the specific imaging modalities. The chapter then guides readers through the handling of MRI data, including different data formats and the standardized BIDS format. It provides a detailed pipeline for fMRI data analysis, including preprocessing, statistical modeling with the General Linear Model, and inference methods. The chapter also discusses advanced smoothing procedures and alternative fMRI analysis methods. For dMRI, it covers noise reduction techniques, diffusion models, and fiber tracking methods. The MPM sequence is introduced, along with its estimation model and bias correction methods. Lastly, the chapter explores IR-MRI, detailing its use in inferring quantitative parameters and microstructural tissue properties. Throughout, the chapter emphasizes reproducibility and provides resources for further reading and implementation in R.