Be able to define the principles and basic concepts of functional Magnetic Resonance Imaging (fMRI) and Voxel-Based Morphometry (VBM) in neuroimaging research.
Gain proficiency in preprocessing fMRI data using SPM, including motion correction, slice timing correction, and spatial normalisation.
Learn how to perform first-level analysis of fMRI data using SPM, including modelling experimental designs, specifying contrasts, and conducting statistical inference.
Understand the steps involved in VBM analysis, including preprocessing such as segmentation, bias correction, and spatial normalisation of structural MRI data.
Be able to describe theoretical basis and practical applications of statistical methods used in fMRI and VBM analyses, including cluster-based thresholding and correction for multiple comparisons.
Gain hands-on experience in conducting fMRI and VBM analyses, as well as interpreting and visualising results.
Be able to outline the challenges and considerations in neuroimaging research, such as data quality assurance, artifact correction, and experimental design optimisation.
Be able to evaluate and interpret research findings in the context of fMRI and VBM analyses.