SPM Course 2016

Zurich 2016 SPM Course for fMRI

Thank you all for a wonderful 10th Zurich SPM course! The talks and tutorials offered during the course can be accessed here.

BASIC

BOLD Physiology (Jakob Heinzle) Pre-processing (Lars Kasper) The General Linear Model for fMRI analyses & Tutorial (Frederike Petzschner) Statistical inference and design efficiency (Andreea Diaconescu)

Multiple comparison correction in SPMs (Justin Chumbley) Experimental design (Sandra Iglesias) Event-related fMRI (Christian Ruff) Resting state” fMRI . . . → Read More: SPM Course 2016

SPM Course 2015

Thank you all for taking part in the SPM course! The SPM 2015 lecture slides are now available online: Basic Course SPM Overview  Preprocessing The General Linear Model for fMRI analyses Statistical inference and design efficiency Multiple comparison correction in SPMs  Experimental design Modelling of hemodynamic timeseries and 2nd-level statistics “Resting state” fMRI  Practicals Scripts  Advanced Course Group analyses Advanced issues in fMRI statistics (SnPM, power, meta-analysis) Practicals Slides & Worksheet Voxel-based morphometry Multivariate analyses Computational models for fMRI analyses Bayesian model selection . . . → Read More: SPM Course 2015

SPM Course 2014

11-14 February, 2014

An IBT Advanced Imaging Course

This four-day course, held annually since 2007, offers comprehensive coverage of all MRI-related aspects of SPM, including . . . → Read More: SPM Course 2014

SPM Course 2013 - Presentation Slides

Here are links to the presentation slides for the SPM Course 2013 (in PDF or Powerpoint format). . . . → Read More: SPM Course 2013 – Presentation Slides

Reading list

Neuroscience

Kandel, Schwartz, Jessell. Principles of Neural Science. McGraw Hill. Parts I – IV. [cell and molecular biology of the neuron, synaptic transmission, neural basis of cognition] Bear, Connors, Paradiso. Neuroscience. Exploring the Brain. LWW.

Classical statistics

Bühlmann, P. Computational Statistics. ETH lectures. Website / Script [introduction to classical multiple linear regression, hypothesis tests, nonparametric regression, classification, shrinkage]

Bayesian statistics and machine learning

Bishop, C. M. (2007). Pattern Recognition and Machine Learning. Springer. Chapters 1-4. [Bayesian linear regression and classification] Barber, D. (2012). Bayesian Reasoning and Machine Learning. Cambridge University Press.

Bayesian models of neural information processing

Kenji Doya (Editor), . . . → Read More: Reading list

SPM Course 2013

13-15 February, 2013

An IBT Advanced Imaging Course All lectures take place at the main University building (lecture hall KO2-F-180), whereas the practical sessions take place at the Gymnasium Rämibühl (Rämistrasse 58, 8001 Zurich) . . . → Read More: SPM Course 2013

SPM courses 2009-2012

SPM Course 2012 SPM Course 2011 SPM Course 2010 SPM Course 2009