2009 Introduction Overview 15 th October 2009 Maria

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

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

Methods for Dummies 2009 Aim: to give a basic introduction to human brain imaging analysis methods, focusing on f. MRI and M/EEG Wednesdays / 13 h 00 – 14 h 00 / FIL Seminar Room Areas covered in Mf. D Introduction to Mf. D 2009 • Basic Statistics • f. MRI (BOLD) • EEG / MEG • Connectivity • VBM

PROGRAMME 2009 Autumn Introduction to Mf. D 2009

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 Mf. D 2009

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 Mf. D 2009

III. f. MRI 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) Continues after Christmas break… Introduction to Mf. D 2009

PROGRAMME 2009 Spring 2010 Introduction to Mf. D 2009

III. f. MRI Analysis (cont. ) 13 th Jan – 3 rd Feb • 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) Introduction to Mf. D 2009

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 Mf. D 2009

V. Connectivity 24 th Feb – 10 th March • Intro to connectivity - PPI & SEM (Melissa Stockbridge and Dean Dsouza) • DCM for f. MRI – theory & practice (Marie-Helene Boudrais and Jorge Ivan Castillo-Quan) • DCM for ERP / ERF – theory & practice (Flavia Cardini and Darren Mc. Guinness) Introduction to Mf. D 2009

VI. Structural MRI Analysis 17 th March • Voxel Based Morphometry (Nikos Gorgoraptis and one other) Introduction to Mf. D 2009

How to prepare your presentation Very important!!!: Read the Presenter’s guide (available on the website) • 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: 45 min. + 15 min. 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 Mf. D 2009

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 Mf. D 2009

Where to find help Mf. D Home Resources http: //www. fil. ion. ucl. ac. uk/mfd/page 2. html • 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 Mf. D 2009

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 Mf. D 2009 Contact the expert: discuss presentation and other issues (1 week before talk) Expert will be present in the session

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

Other helpful courses • Matlab for Cognitive Neuroscience (ICN) – – Run by Christian Ruff http: //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 Introduction to Mf. D 2009

Overview for Dummies Introduction to Mf. D 2009

Outline • SPM & your (f. MRI) data – Preprocessing – Analysis – Connectivity • Getting started with an experiment • Acronyms Introduction to Mf. D 2009

Pre-processing

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

Model specification and estimation

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’ Design matrix General Linear Model ‘visual stimulus off = 0’

Inference

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

Write up and publish…

Brain connectivity Causal interactions between brain areas, statistical dependencies • 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)

Statistical Parametric Mapping • Mf. D 2009 will focus on the use of SPM 8 • SPM software has been designed for the analysis of brain imaging data in f. MRI, 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

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 Mf. D 2009

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 Mf. D 2009

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. php Introduction to Mf. D 2009

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 Mf. D 2009

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 Mf. D 2009

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 Re. ML – 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