Short Course on:

Statistical Parametric Mapping

Presented by the Wellcome Department of Imaging Neuroscience

in London, May 15-17, 2003

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 in to two sessions, dealing with (i) the theoretical foundations, procedural implementation and experimental design and (ii) a series of practical sessions in which SPM will be used to analyse exemplar data sets. The second session 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 Foundations

Thursday 15th May

09.30 - 09.45 Introduction & Overview, Karl Friston
09.45 - 10.45 Computational Neuroanatomy, John Ashburner ( + Movement Correction slides)
10.45 - 11.00 Coffee
11.00 - 12.00 The General Linear Model and Statistical Parametric Mapping, Stefan Kiebel
12.00 - 13.00 Contrasts and Classical Inference, Jean-Baptiste Poline
12.30 - 14.00 Lunch
14.00 - 15.00 Inference and the Theory of Gaussian Fields, Will Penny ( + False Discovery Rate slides)
15.00 - 16.00 Experimental design, Daniel Glaser
16.00 - 16.30 Tea
16.30 - 17.30 fMRI: Epoch and event-related designs, Rik Henson

Friday 16th May

9.30 - 10.15 Hierarchical models and variance components, Will Penny
10.15 - 11.00 Effective Connectivity and Dynamic Causal Modelling, Lee Harrison
11.00 - 11.30 Coffee
11.30 - 12.15 Non-parametric Inference, Tom Nichols
12.15 - 13.00 Multivariate Analysis, Jean-Baptiste Poline
13.00 - 14.00 Lunch

Practical Sessions

14.00 - 15.30 Introduction and orientation to the SPM interface and data, Daniel Glaser & Stefan Kiebel
15.30 - 16.00 Tea
16.00 - 17.30 Spatial pre-processing and voxel-based morphometry, Chris Phillips & John Ashburner

Saturday 17th May

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

An analysis of a PET time series, 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
Computational Neuroanatomy, 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.