This technical report presents a review of research conducted by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the analysis of both structural and functional magnetic resonance imaging (MRI) data. The research has been implemented as freely available software tools within FMRIB's Software Library (FSL). The paper discusses advances in functional MRI (fMRI) analysis, including the development of model-based voxelwise general linear model (GLM) techniques (FILM), Bayesian methods for multi-session/subject analysis (FLAME), and a complete GUI-based tool for model-based fMRI analysis (FEAT). It also covers probabilistic independent component analysis (PICA) for fMRI data, spatial mixture modelling for inference, and the use of Bayesian inference on constrained linear basis sets for haemodynamic response function (HRF) models. The report also discusses structural MRI analysis, including brain/ non-brain segmentation (BET), tissue-type segmentation and bias field correction (FAST), and affine inter-modal image registration (FLIRT). Additionally, it covers motion correction (MCFLIRT & FORCE), brain change analysis (SIENA), diffusion and white matter connectivity analysis (FDT), and MR physics-related research, including EPI distortion correction (PRELUDE & FUGUE). The research has significantly advanced the ability to detect neural activations and investigate brain function using fMRI, while also improving the understanding of the processes involved in data creation. The software tools developed have been implemented in FSL, which is freely available and widely used in the field of neuroimaging research.This technical report presents a review of research conducted by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the analysis of both structural and functional magnetic resonance imaging (MRI) data. The research has been implemented as freely available software tools within FMRIB's Software Library (FSL). The paper discusses advances in functional MRI (fMRI) analysis, including the development of model-based voxelwise general linear model (GLM) techniques (FILM), Bayesian methods for multi-session/subject analysis (FLAME), and a complete GUI-based tool for model-based fMRI analysis (FEAT). It also covers probabilistic independent component analysis (PICA) for fMRI data, spatial mixture modelling for inference, and the use of Bayesian inference on constrained linear basis sets for haemodynamic response function (HRF) models. The report also discusses structural MRI analysis, including brain/ non-brain segmentation (BET), tissue-type segmentation and bias field correction (FAST), and affine inter-modal image registration (FLIRT). Additionally, it covers motion correction (MCFLIRT & FORCE), brain change analysis (SIENA), diffusion and white matter connectivity analysis (FDT), and MR physics-related research, including EPI distortion correction (PRELUDE & FUGUE). The research has significantly advanced the ability to detect neural activations and investigate brain function using fMRI, while also improving the understanding of the processes involved in data creation. The software tools developed have been implemented in FSL, which is freely available and widely used in the field of neuroimaging research.