Short Course on:

Statistical Parametric Mapping

Presented by the Wellcome Department of Imaging Neuroscience

at 12 Queen Square, London, UK on May 17-18, 2002

Session I - Theoretical Foundations

Friday 17th May

09.00 - 09.15 Introduction & Overview, Karl Friston
09.15 - 10.00 Computational Neuroanatomy, John Ashburner
10.00 - 10.45 The General Linear Model and Statistical Parametric Mapping, Stefan Kiebel
10.45 - 11.00 Coffee
11.00 - 11.45 Contrasts and Classical Inference, Jean-Baptiste Poline
11.45 - 12.30 Inference and the Theory of Gaussian Fields, Andrew Holmes ( + False Discovery Rate slides)
12.30 - 14.00 Lunch

Session II - Implementation and Experimental Design

14.00 - 14.45 Effective Connectivity (toolbox), Will Penny
14.45 - 15.30 Experimental Design, Daniel Glaser
15.30 - 16.00 Tea
16.00 - 16.45 fMRI: Epoch and Event-Related Designs, Rik Henson
16.45 - 17.30 Review, Discussion and SPM `Clinic', Panel (Chair: Karl Friston)

Session III - Practical

Saturday 18th May

10.00 - 10.30 Introduction and Orientation, Andrew Holmes
10.30 - 13.00 Supervised Data Analysis (8 groups) - Session I
13.00 - 14.00 Presentation of Results and Discussion
14.00 - 15.00 Break
15.00 - 16.00 Supervised data analysis (8 groups) - Session II
16.00 - 17.00 Presentation of Results and Discussion Panel
Close

The course presented instruction on the analysis and characterisation of functional activation data using Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI). It was divided in to three sessions, dealing with (i) the theoretical foundations, (ii) procedural implementation and experimental design and (iii) a practical session in which SPM99 will be used to analyse exemplar data sets. The second session included a 'clinic' where questions and issues of concern for participants will be addressed with the lecturers.