Short Introduction to the General Linear Model for Neuroimaging (Oxford Neuroimaging Primer Appendices)

The General Linear Model, or GLM, is used for modelling and statistical hypothesis testing in nearly all areas of neuroimaging. This is due to its great flexibility - it can be used to analyse within- subject timeseries or between-subject data, and to remove components from the data identified as noise; all of which will be discussed briefly in this short introduction. It is very important to obtain a practical understanding of how to use the GLM well if you are going to do neuroimaging analyses.This text is one of a number of appendices to the Oxford Neuroimaging Primers, designed to provide extra details and information that someone reading one of the primers might find helpful, but where it is not crucial to the understanding of the main material. This appendix specifically addresses the General Linear Model (GLM), as it is used in neuroimaging. In it we seek to go into more detail than we might in one of the primers, such as the Introduction to Neuroimaging Analysis, for those who want to understand more about how the GLM works and how to use it.