Overview

1) Physical and practical principles of MRI imaging, Methods for image pre-processing (e.g. image registration etc.) and basic handling of imaging data; 2)  Practicalities associated with the physiology of MRI contrast in the brain, with a focus on measures of cerebral metabolism and blood flow; 3)  Principles and practical methodologies for measurement of changes in cerebral metabolism; 5)   Practicalities of statistical analyses of functional imaging time-series; 6)   Experimental design for functional imaging; 7) The safety and ethical issues that arise in regards to neuroimaging research and how they apply to the researcher, participants and the wider community.

Learning Outcomes

• 1. Understand modern neuroimaging data formats and solid data management and hygiene practices

• 3. Use this knowledge of the GLM to design a good fMRI study

• 4. Be able to pre-process and analyze MRI and fMRI data.

• 5. Be able to report and interpret the results of fMRI studies.

• 6. A thorough understanding of MRI safety

• 7. An understanding of the ethical issues associated with handling modern neuroimaging data.

• Have a solid understanding of practical application of the general linear model (GLM) to analysis of neuroimaging data