1 / 9

Methods & models for fMRI data analysis – HS 2013

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:

Download Presentation

Methods & models for fMRI data analysis – HS 2013

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Methods & models for fMRI data analysis – HS 2013 David ColeAndrea DiaconescuJakob HeinzleSandra IglesiasSudhir Shankar RamanKlaas Enno Stephan

  2. 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)

  3. 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).

  4. 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

  5. SPM8 • the history • the program • the spirit

  6. SPM documentation SPM course notes,SPM book & SPM manual peer reviewed literature algorithm descriptions,code annotations,pseudo-code online help & function descriptions

  7. SPM online bibliography • http://www.fil.ion.ucl.ac.uk/spm/

  8. SPM web site • Introduction to SPM • SPM distribution:SPM99, SPM2, SPM5, SPM8 • Documentation & Bibliography • SPM email discussion list • SPM short course • Example data sets • SPM extensions http://www.fil.ion.ucl.ac.uk/spm/

  9. SPM email list • spm@jiscmail.ac.uk • Web home page • http://www.fil.ion.ucl.ac.uk/spm/support/ • Archives, archive searches, membership lists, instructions • Subscribe • http://www.jiscmail.ac.uk/ • email jiscmail@jiscmail.ac.uk • join spm Firstname Lastname • Participate & learn • email spm@jiscmail.ac.uk • Monitored by SPMauthors • Usage queries, theoretical discussions, bug reports, patches, techniques, &c… http://www.fil.ion.ucl.ac.uk/spm/support/ spm@jiscmail.ac.uk

More Related