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| [attachment:C:%5CDocuments%20and%20Settings%5Cuser%5CMy%20Documents%5CTALKS%5Chenson%2DSPM%2DGrad%30%38%2D%31%2Dpreproc.ppt Spatial preprocessing (Realigment, unwarping, normalisation, smoothing, segmentation) and Computational Neuroanatomy e.g. voxel-based morphometry (VBM), deformation-based morphometry (DBM) and tensor-based morphometry (TBM)] | [attachment:henson-SPM-Grad08-1-preproc.ppt Spatial preprocessing (Realigment, unwarping, normalisation, smoothing, segmentation) and Computational Neuroanatomy e.g. voxel-based morphometry (VBM), deformation-based morphometry (DBM) and tensor-based morphometry (TBM)] |
Rik Henson gave a short SPM course at the Department of Psychology at the University during February 2008. Please see below for a copy of the slides of these talks:
[attachment:henson-SPM-Grad08-1-preproc.ppt Spatial preprocessing (Realigment, unwarping, normalisation, smoothing, segmentation) and Computational Neuroanatomy e.g. voxel-based morphometry (VBM), deformation-based morphometry (DBM) and tensor-based morphometry (TBM)]
The General Linear Model: global effects, correlation/orthogonalisation, time-series convolution models, high-pass filtering, temporal auto-correlation, maximum likelihood (ML) estimation, non-sphericity
Inference: Statistical Parametric Maps (SPMs) and Gaussian Field Theory Correction, Random Effects, Parametric Empirical Bayes and PPMs, experimental designs, effective connectivity and dynamic causal modelling (DCM)
Event-related fMRI: Rationale, temporal basis functions, slice-timing correction, latency analysis, efficiency and optimal experimental design, nonlinearities