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Methods & models for fMRI data analysis – HS 2013. David Cole Andrea Diaconescu Jakob Heinzle Sandra Iglesias Sudhir Shankar Raman Klaas Enno Stephan. Methods & models for fMRI data analysis. Room: ETZ F91 Time: Fri, 12:00 – 13:30. Schedule:
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Methods & models for fMRI data analysis – HS 2013 David ColeAndrea DiaconescuJakob HeinzleSandra IglesiasSudhir Shankar RamanKlaas Enno Stephan
Methods & modelsforfMRIdataanalysis Room: ETZ F91 Time: Fri, 12:00 – 13:30 Schedule: 27.09.: BOLD neurophysiology (Jakob Heinzle) 04.10.: Spatial preprocessing of fMRI images (David Cole) 11.10.: The General Linear Model for fMRI analyses (K.E. Stephan) 18.10.: Classical (frequentist) inference (NN) 25.10.: Multiple comparison correction (K.E. Stephan) 01.11.: Experimental design (Sandra Iglesias) 08.11.: Event-related fMRI and design efficiency (K.E. Stephan) 15.11.:VariationalBayes & Bayesian model selection (Sudhir Shankar Raman) 22.11.: Computational Neuroimaging (Andreea Diaconescu) 29.11.: Multivariate models for fMRI (K.E. Stephan) 06.12.: Basics of Dynamic Causal Modelling (Sudhir Shankar Raman) 13.12.: Practicalsession on DCM (K.E. Stephan) 20.12.: Advanced aspects of Dynamic Causal Modelling(K.E. Stephan)
FAQs • slides on TNU website: www.translationalneuromodeling.org • 3 credit points • attendance requirements: 11/13 presentations • exam: • 10.01.2014, 12:00-13:30 • 36 multiple choice questions (18 correct answers required for passing), 90 minutes duration For all administrative issues, please contact Silvia Princz (sprincz@biomed.ee.ethz.ch).
Statistical Parametric Mapping (SPM) Design matrix Statistical parametric map (SPM) Image time-series Kernel Realignment Smoothing General linear model Gaussian field theory Statistical inference Normalisation p <0.05 Template Parameter estimates
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