UCL Institute of Neurology (D07)![]() The Institute of Neurology was established in 1950, merged with UCL in 1997, and is a key component of the Faculty of Brain Sciences at UCL. The Institute has eight academic Departments, which encompass clinical and basic research within each theme. In parallel, there are currently six Divisions representing professional affiliations. FOR ALL QUERIES PLEASE USE THE CONTACT TABS FOUND IN EACH OF THE INDIVIDUAL COURSES/CONFERENCES AND PRODUCTS, PLEASE ONLY CONTACT THE ONLINE STORE DIRECTLY IF YOU ARE EXPERIENCING PAYMENT DIFFICULTIES.
UCL Institute of Neurology (D07)D07 Final Year Electives for Medical StudentsDescriptionThe Institute of Neurology offers a limited number of undergraduate Elective placements, to final year medical students from the UK and abroad, which are booking at least 18 months in advance. These placements are not strictly structured - it is advisable to be as pro-active as possible. It is up to the individual student to choose the activities they wish to attend, within their assigned clinical group/formal teaching programme, which would most benefit them during their placement. https://www.ucl.ac.uk/ion/study/electives-medical-students
D07 Statistical Parametric Mapping For fMRI & MRI/VBM Oct 2025DescriptionThis three-day online course introduces the analysis of neuroimaging data, including Magnetic Resonance Imaging (MRI) and functional MRI (fMRI). It covers: Experimental design Pre-processing brain images Quantifying structural changes in the brain (Voxel-Based Morphometry, VBM) Quantifying brain function (using the General Linear Model, GLM) Statistics for neuroimaging (frequentist and Bayesian) Connectivity analysis (Dynamic Causal Modelling, DCM) The course will be divided into theoretical and practical sessions, in which the SPM software package will be used to analyse exemplar data sets. The SPM course is taught by an international faculty of neuroimaging experts from the Department of Imaging Neuroscience, including the Functional Imaging Laboratory, and collaborators. The course is suitable for beginners and more advanced users. More information about the content and learning objectives of the course can be found here https://www.fil.ion.ucl.ac.uk/spm/docs/courses/
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