1. Introduction / Overview 15th October 2009 Maria Joao Rosa and Antoinette Nicolle Wellcome Trust Centre for Neuroimaging, UCL 2009

2. Overview Introduction What’s MfD Programme for 2009 How to prepare your presentation Where to find information and help Experts Overview for dummies Introduction to MfD 2009

3. Methods for Dummies 2009 Basic Statistics fMRI (BOLD) EEG / MEG Connectivity VBM Introduction to MfD 2009 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 2009 Autumn Introduction to MfD 2009

5. I. Basic Statistics 21 st Oct – 18 th Nov Linear Algebra & Matrices (Elvina Chu and Flavia Mancini) T-tests, ANOVA’s & Regression (Carles Falcon and Suz Prejawa) General Linear Model (Catherine Tur and Ashawin Jha) Bayes for beginners (Raphael Kaplan and Jason Stretton) Random Field Theory (Friederike Schuur and Anne-Lise Goddings) Introduction to MfD 2009

6. II. What are we measuring? 25 th Nov – 2 nd Dec Basis of the BOLD signal (Miriam Klein and Ciara O’Mahony) Basis of the M/EEG signal (Jordi Costa Faidella and Tal Machover) Introduction to MfD 2009

7. III. fMRI Analysis 9 th Dec – 16 th Dec Preprocessing: –Realigning and un-warping (Idalmis Santusteban and Rebecca Knight) –Co-registration & spatial normalisation (Ana Csaraiva and Britt Hoffland) Introduction to MfD 2009 Continues after Christmas break…

8. PROGRAMME 2009 Spring 2010 Introduction to MfD 2009

9. Study design and efficiency (Heidi Bonnici and Sinead Mullally) 1 st level analysis – Design matrix contrasts and inference (Loreili Howard and Rumana Chowdury) 1 st level analysis – Basis functions, parametric modulation and correlated regressors (Crystal Goh and one other) 2 nd level analysis – between-subject analysis (Jennifer Marchant and Tessa Dekker) III. fMRI Analysis (cont.) 13 th Jan – 3 rd Feb

10. IV. EEG & MEG 10 th Feb – 17 th Feb Pre-processing and experimental design (Thomas Ditye and Lena Kaestner) Contrasts, inference and source localisation (Diana Omigie and Stjepana Kovac) Introduction to MfD 2009

11. V. Connectivity 24 th Feb – 10 th March Intro to connectivity - PPI & SEM (Melissa Stockbridge and Dean Dsouza) DCM for fMRI – theory & practice (Marie-Helene Boudrais and Jorge Ivan Castillo-Quan) DCM for ERP / ERF – theory & practice (Flavia Cardini and Darren McGuinness) Introduction to MfD 2009

12. VI. Structural MRI Analysis 17 th March Voxel Based Morphometry (Nikos Gorgoraptis and one other)

13. 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 2009 Very important!!!: Read the Presenter’s guide (available on the website)

14. 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 Maria or Antoinette as soon as possible (at least 3 weeks before the talk). Introduction to MfD 2009

15. 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 2009 MfD HomeResources http://www.fil.ion.ucl.ac.uk/mfd/page2/page2.html

16. Experts Will Penny – Head of Methods John Ashburner Jean Daunizeau Guillaume Flandin James Kilner Rosalyn Moran Andre Marreiros Vladimir Litvak Chloe Hutton Maria Joao Rosa Antoinette Nicolle Introduction to MfD 2009 Contact the expert: discuss presentation and other issues (1 week before talk) Expert will be present in the session

17. Website http://www.fil.ion.ucl.ac.uk/mfd/ Introduction to MfD 2009 Where you can find all the information about MfD 2009: Programme Contacts Presenter’s guide Resources (Help) Etc…

18. Other helpful courses Introduction to MfD 2009 Matlab for Cognitive Neuroscience (ICN) –Run by Christian Ruff –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

19. Overview for Dummies Introduction to MfD 2009

20. Outline SPM & your (fMRI) data –Preprocessing –Analysis –Connectivity Getting started with an experiment Acronyms Introduction to MfD 2009

21. Pre-processing

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

23. Model specification and estimation

24. 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

25. Inference

26. 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

27. Write up and publish…

28. 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

29. Statistical Parametric Mapping MfD 2009 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

31. 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 2009

32. 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 2009

33. 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 2009

34. 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 2009

35. 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 2009

36. 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