1. Introduction / Overview 6th October 2010 Suz Prejawa & Chris Lambert Wellcome Trust Centre for Neuroimaging, UCL 2010

2. Overview Introduction What’s MfD Programme for 2010 How to prepare your presentation Where to find information and help Experts Overview for dummies Introduction to MfD 2010

3. Methods for Dummies 2009 Basic Statistics fMRI (BOLD) EEG / MEG Connectivity VBM & DTI (a new addition) Introduction to MfD 2010 Areas covered in MfD Wednesdays / 13h00 – 14h00 / FIL Seminar Room Aim: to give a basic introduction to human brain imaging analysis methods, focusing on fMRI and M/EEG

4. PROGRAMME 2010 Autumn Introduction to MfD 2010

5. I. Basic Statistics 20 th Oct – 17 th Nov Linear Algebra & Matrices (Philip Glass & Melanie Boly) T-tests, ANOVA’s & Regression (Jennifer Siegel & Varun Sethi) General Linear Model (Holly Rossiter & Philip Glass) Bayes for beginners (Rik Adams & Yen Yu) Random Field Theory (Rumana Chowdhury & Nagako Murase) Introduction to MfD 2010

6. II. What are we measuring? Part I: 24 th Nov Basis of the BOLD signal (Louise McDonald & Yen Yu) Introduction to MfD 2010 A nice one week break…

7. III. fMRI Analysis 8 th Dec – 15 th Dec Preprocessing: –Realigning and un-warping (Matteo Pugnaghi & Rebecca Lawson) –Co-registration & spatial normalisation (Rebecca Lawson & Matteo Pugnaghi Introduction to MfD 2010 Continues after Christmas break…

8. PROGRAMME 2009 Winter/ Spring 2010 Introduction to MfD 2010

9. Study design and efficiency (Rumana Chowdhury & Robin Carhart Harris) 1 st level analysis – Design matrix contrasts and inference (Stephane de Brito & Fiona McNab) 1 st level analysis – Basis functions, parametric modulation and correlated regressors (Klaartje Heinen & Paul Rogerson) 2 nd level analysis – between-subject analysis (Fiona McNab & Stephane de Brito) III. fMRI Analysis (cont.) 12 th Jan – 2 nd Feb

10. II. What are we measuring? Part II: 9th Feb Basis of the M/EEG signal (Rik Adams & Louise McDonald) Introduction to MfD 2010

11. IV. EEG & MEG 16 th Feb – 23 rd Feb Pre-processing and experimental design (Jennifer Siegel & Tabish Saifee) Contrasts, inference and source localisation (Tabish Saifee & Paul Rogerson) Introduction to MfD 2010

12. V. Connectivity 2 nd March – 16 th March Intro to connectivity - PPI & SEM (Nagako Murase & Klaartje Heinen) DCM for fMRI – theory & practice (Peter Zeidman & Laura Madeley) DCM for ERP / ERF – theory & practice (Niall Lally & Holly Rossiter) Introduction to MfD 2010

13. VI. Structural MRI Analysis 23 rd March- 30 th March Voxel Based Morphometry (Laura Madeley & Sabeena Chaudry) Basic DTI (Niall Lally & Sabeena Chaudry)

14. How to prepare your presentation Remember your audience are not experts… The aim of the sessions is to –introduce the concepts and explain why they are important to imaging analysis –familiarise people with the basic theory and standard methods Time: 45min. + 15min. questions – 2 presenters per session Don’t just copy last year’s slides!!!... Start preparing your talk with your co-presenter at least 2 weeks in advance Talk to the allocated expert 1 week in advance Introduction to MfD 2010 Very important!!!: Read the Presenter’s guide ( http://www.fil.ion.ucl.ac.uk/mfd/guide.pdf )

15. What if I can’t make my presentation? If you want to change / swap your topic, try and find someone else to swap with…. …if you still can’t find a solution, then get in touch with Chris, Maria or Suz as soon as possible (at least 3 weeks before the talk). Introduction to MfD 2010

16. Where to find help Key papers Previous years’ slides Human Brain Function Textbook (online) SPM course slides Cambridge CBU homepage (Rik Henson’s slides) Methods Group Experts Monday Methods Meetings (4 th floor FIL, 12.30) SPM email List Introduction to MfD 2010 MfD HomeResources http://www.fil.ion.ucl.ac.uk/mfd/page2/page2.html

17. Experts Will Penny – Head of Methods John Ashburner Dimitris Pinotsis Guillaume Flandin James Kilner Rosalyn Moran Andre Marreiros Steve Fleming Vladimir Litvak Chloe Hutton Antoine Lutti Ged Ridgeway Zoltan Nagy Marta Garrido Introduction to MfD 2010 Contact the expert: discuss presentation and other issues (1 week before talk) Expert will be present in the session

18. Website http://www.fil.ion.ucl.ac.uk/mfd/ Introduction to MfD 2010 Where you can find all the information about MfD 2010: Programme Contacts Presenter’s guide Resources (Help) Etc…

19. Other helpful courses Introduction to MfD 2010 Matlab for Cognitive Neuroscience (ICN) –Run by Klaartje Heinen Jen Marchant k.heinen@ucl.ac.uk & jennifer.marchant@ucl.ac.uk k.heinen@ucl.ac.ukjennifer.marchant@ucl.ac.uk –http://www.icn.ucl.ac.uk/courses/MATLAB- Tutorials/index.htmhttp://www.icn.ucl.ac.uk/courses/MATLAB- Tutorials/index.htm –4.30 pm, Thursday (not every week!) –17 Queen Square, basement seminar room Physics lecture series –Run by FIL physics team –Details will be announced –12 Queen Square, Seminar room

20. Overview for Dummies Introduction to MD 2010

21. Outline SPM & your (fMRI) data –Preprocessing –Analysis –Connectivity Getting started with an experiment Acronyms Introduction to MfD 2010

22. Pre-processing

23. Preprocessing Possibilities… These steps basically get your imaging data to a state where you can start your analysis –Realignment & Unwarping –Segmentation and Normalisation –Smoothing

24. Model specification and estimation

25. Analysis Once you have carried out your pre-processing you can specify your design and data –The design matrix is simply a mathematical description of your experiment E.g. ‘visual stimulus on = 1’ ‘visual stimulus off = 0’ Design matrix General Linear Model

26. Inference

27. Contrasts & inference Contrasts allow us to test hypotheses about our data, using t & f tests 1 st level analysis: activation over scans (within subject) 2 nd level analysis: activation over subjects Multiple Comparison Problem – Random Field Theory SPM

28. Write up and publish…

29. Brain connectivity Functional integration – how one region influences another…subdivided into: –Functional connectivity: correlations among brain systems (e.g. principal component analysis) –Effective connectivity: the influence of one region over another (e.g. psycho-physiological interactions, or Dynamic Causal Modelling) Causal interactions between brain areas, statistical dependencies

30. Statistical Parametric Mapping MfD 2010 will focus on the use of SPM8 SPM software has been designed for the analysis of brain imaging data in fMRI, PET, SPECT, EEG & MEG It runs in Matlab… just type SPM at the prompt and all will be revealed. There are sample data sets available on the SPM website to play with

32. Getting started – Cogent http://www.vislab.ucl.ac.uk/Cogent/ –present scanner-synchronized visual stimuli, auditory stimuli, mechanical stimuli, taste and smell stimuli –monitor key presses –physiological recordings –logging stimulus & scan onset times Try and get hold of one to modify rather than starting from scratch! People are more than happy to share scripts around. If you need help, talk to Eric Featherstone. Introduction to MfD 2010

33. Getting started - Setting up your experiment If you need… special equipment –Peter Aston –Physics team special scanning sequences –Physics team They are very happy to help, but contact them in time! Introduction to MfD 2010

34. Getting started - scanning decisions to be made What are your scanning parameters: –how many conditions/sessions/blocks –Interstimulus interval –Scanning sequence –Scanning angle –How much brain coverage do you need how many slices what slice thickness –what TR Use the physics wiki page: http://cast.fil.ion.ucl.ac.uk/pmwiki/pmwiki.php http://cast.fil.ion.ucl.ac.uk/pmwiki/pmwiki.php Introduction to MfD 2010

35. Summary Get you script ready & working with the scanner Make sure it logs all the data you need for your analysis Back up your data from the stimulus PC! You can transfer it via the network after each scanning session… Get a scanning buddy if it’s your first scanning study Provide the radiographers with tea, biscuits, chocolate etc. Introduction to MfD 2010

36. Use the project presentations! They are there to help you design a project that will get you data that can actually be analyzed in a meaningful way Introduction to MfD 2010

37. Acronyms DCM – dynamic causal model DTI – diffusion tensor imaging FDR – false discovery rate FFX – fixed effects analysis FIR – finite impulse response FWE – family wise error FWHM – full width half maximum GLM – general linear model GRF – gaussian random field theory HRF – haemodynamic response function ICA – independent component analysis ISI – interstimulus interval PCA – principal component analysis PEB – parametric empirical bayes PPI – psychophysiological interaction PPM – posterior probability map ReML – restricted maximum likelihood RFT– random field theory RFX – random effects analysis ROI – region of interest SOA – stimulus onset asynchrony SPM – statistical parametric mapping VBM – voxel-based morphometry