62013-03-07 21:24:00localhostconverted to 1.6 markup52007-05-09 22:41:27RikHenson42007-03-09 20:28:50callosum.BIC.Berkeley.EDU32007-03-09 20:28:26callosum.BIC.Berkeley.EDUMaking room for 2007 course22006-07-25 14:37:36devel03.mrc-cbu.cam.ac.uk12006-07-24 22:23:25Scripting Subsystem

Rik Henson gave a short SPM course at the CBU during February 2005. Please see below for a copy of the slides of these talks: 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