Short Course on:

Statistical Parametric Mapping

Presented by the Wellcome Department of Imaging Neuroscience

in London, May 13-15, 2004


The course will present instruction on the analysis and characterisation of functional activation data using Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI). The course will be divided into theoretical sessions covering experimental design and statistical inference and practical sessions in which SPM will be used to analyse exemplar data sets. The practical sessions will focus on important but specific issues in experimental design and analysis that will be addressed with the participation of the registrants.


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Theoretical Sessions

Thursday 13th May

09.30 - 09.45 Introduction & Overview, Karl Friston
09.45 - 10.45 Image Registration, John Ashburner
10.45 - 11.00 Coffee
11.00 - 11.45 The General Linear Model, Stefan Kiebel
11.45 - 12.30 Contrasts and Classical Inference, Jean-Baptiste Poline
12.30 - 13.00 Random Effects Analysis, Will Penny
13.00 - 14.00 Lunch
14.00 - 14.45 Random Field Theory, Tom Nichols
14.45 - 15.15 Non-parametric Inference, Tom Nichols
15.15 - 15.45 Tea

Practical Sessions

15.45 - 16.45 Introduction to Spatial Processing , John Ashburner & Chris Phillips
16.45 - 17.15 Introduction to Experimental Design , Daniel Glaser & Stefan Kiebel
17.15 - 18.00 Clinic, Karl Friston

Friday 14th May

09.30 - 10.15 Segmentation and Voxel-Based Morphometry, John Ashburner
10.15 - 11.00 Experimental design, Daniel Glaser
11.00 - 11.15 Coffee
11.15 - 12.00 Event-related fMRI, Rik Henson
12.00 - 12.30 Variance components, Stefan Kiebel
12.30 - 13.00 Bayesian Inference, Will Penny
13.00 - 14.00 Lunch
14.00 - 15.00 Effective Connectivity and Dynamic Causal Modelling, Lee Harrison

Practical Sessions

15.00 - 16.00 Analysis of Functional Data , Daniel Glaser & Stefan Kiebel
16.00 - 16.30 Tea
16.30 - 17.00 Dynamic Causal Modelling , Klaas Stephan and Lee Harrison
17.00 - 18.00 Clinic , Karl Friston

Saturday 15th May

The last day consists of a number of parallel sessions covering (approx.) the following topics:

An analysis of a PET time series, Andrea Mechelli, Daniel Glaser
Basic analysis of fMRI time series, Stefan Kiebel
Advanced analysis of fMRI time series, Rik Henson, Will Penny
Random Effects Analysis and Nonparametrics, Tom Nichols
Multivariate analysis and other toolboxes J.-B. Poline
Dynamic Causal Modelling, Lee Harrison, Klaas Stephan
Voxel-based Morphometry John Ashburner, Chris Phillips

These topics will be adapted to the requirements of students. Each session will run all day and will be broken up into mini-sessions from 9.00-10.30, 11.00-12.30, 14.00-15.30 and 16.00-17.00 with coffee served at 10.30 and 15.30.