In recent years, Magnetic Resonance Imaging and functional MRI have played an increasingly important role in the investigation of brain structure, function, development and pathologies. The increasing flexibility and power of MRI and FMRI to answer scientifically interesting and clinically relevant questions has led to a demand for analysis techniques which allow investigators to interrogate their data in as flexible, scientifically informative and convenient a manner as is possible. This paper presents an overview of research carried out with this aim, in the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB).
The broadest distinction which can be drawn between MRI experiments in the brain is between structural experiments, which are sensitive to biophysical properties of local brain tissue, and functional experiments, which are sensitive to temporally changing neural activity. The two types of MRI data require very different analysis techniques and are grouped into separate sections in this paper, but the relationship between structure and function is fundamental to brain organisation. The data analysis techniques and tools described in sections 2 (functional analysis) and 3 (structural analysis) allow investigators not only to learn from each source of information, but also to combine data from functional and structural experiments to better inform neuropsychological inference. Section 4 is an example of this interdependence between structure and function, investigating the influence of structural connectivity on brain function. Fundamental to the ability to draw inference from data is a thorough understanding of the processes involved in the data's creation. The research outlined in section 5 gives examples of how to improve this understanding via direct modelling of the MR image acquisition process. Crucially, this allows investigators to increase the sensitivity of their MRI experiments through both improved experimental design and the reduction of acquisition-related image artefacts. Finally, section 6 describes briefly the freely available FSL software package, within which most of the research covered in this paper has been implemented.