Teaching

  • Signal processing
    • This lecture series covers univariate statistics, linear algebra, information theory, Fourier methods, stochastic processes, subspace methods, Kalman Filters and Expectation-Maximization algorithms.



  • Maths for Brain Imaging
    • This lecture series covers a number of mathematical methods that are used in the analysis of brain imaging data. Each lecture describes a different category of model and shows how it is applied to a particular aspect of brain imaging analysis. This includes the General Linear Model, Random Field Theory, Multivariate Models, Variance Components, Bayesian Methods, Model Comparison, Spectral Estimation, Approximate Bayesian Inference and Nonlinear Models. The applications cover data from functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and EEG.



  • Statistical Parametric Mapping
    • The SPM short course on using Statistical Parametric Mapping for functional neuroimaging is held each May as part of the Institute of Neurology's short course programme. Since 2008, a second SPM course is organised each October. The course presents instruction on the analysis and characterisation of functional imaging data. This includes the following modalities: Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI) and Electro-encephalography (EEG) and Magneto-encephalography (MEG).