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Overview for Dummies

Overview for Dummies. Outline . Getting started with an experiment Things you need to know for scanning SPM & your data Acronyms. Getting started. Cogent scripts….

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Overview for Dummies

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  1. Overview for Dummies

  2. Outline • Getting started with an experiment • Things you need to know for scanning • SPM & your data • Acronyms

  3. Getting started • Cogent scripts…. • Allow you to present scanner-synchronized visual stimuli, auditory stimuli, mechanical stimuli, and taste and smell stimuli. Details at: http://www.vislab.ucl.ac.uk/Cogent/ • It is also used in monitoring key presses and other physiological recordings from the subject, as well as logging stimulus and 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… • …and if you need to use any special equipment then Peter Aston is the man to see

  4. Getting started…scanning decisions to be made • What are your scanning parameters • how many conditions/sessions/blocks? • how much brain coverage do you need • what ISI do you want • how many measurements & at what angle

  5. TRs • It takes 44 horizontal slices to get whole brain coverage. • Each slice takes about 90s to acquire, with a standard slice thickness of 3mm • So, acquiring the whole brain may take too long… • Factors you need to take into account are: • TR length • ISI length • TR should not equal the ISI… • And if you want to do a DCM (dynamic causal model) then you need a TR ideally of less than 3s

  6. TR decisions – an example • I needed to present stimuli for 1s and also give the subject time to respond • I wanted 6 stimulus presentations per block • Interleaved between blocks I needed a fixation time for the baseline, and ideally I want to use DCM too • Also, having the TR & ISI both divisible by the number of stimuli in a block, stimuli are evenly presented throughout the block • So the choices were… • TR of 30 slices (2.7s) with an ISI of 36 slices (3.24s), or a TR of 36 slices (3.24s) with an ISI of 30 slices (2.7s) • Fixation between trails was equivalent to 5*TR • The first choice gave plenty of time for the subject to respond and also allows me to carry out a DCM analysis

  7. Summary for scanning • 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… • Provide the radiographers with tea, biscuits, chocolate etc.

  8. Hurrah! I have brain data! • SO WHAT DO I DO WITH IT NOW? • This is where we get into SPM & preprocessing… • …and more decision-making! • It can take a long time to process at this stage, so make sure you have decided in advance!

  9. Preprocessing Possiblities… • These steps basically get your imaging data to a state where you can start your analysis • Slice timing • Realignment • Coregistration • Normalisation • Smoothing • Segmentation • Once you have carried out your pre-processing you can specify your design and data

  10. Contrasts, inference & basis functions • Contrasts allow us to test hypotheses about our data, using t & f tests • Our fMRI data is a time series based on the haemodynamic response. The basis functions used in SPM are curves used to ‘describe’ or fit the haemodynamic response in relation to our model.

  11. Linear hierarchical models • 1st level analysis: activation over scans (within subject) • 2nd level analysis: activation over subjects • Hierarchical models are central to: • random effects analyses • Bayseian modelling • DCM

  12. Connectivity • Functional segregation – responses to an input giving a regionally specific effect • 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 DCM)

  13. Voxel-based Morphometry • Contrasts differences in structural data on a voxel-by-voxel basis • Used to compare size or shape of brain region, for instance • Comparing brain-damaged patients with a control group • mapping changes in grey (or white) matter within subjects over time

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

  15. Good Luck!

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