Hi, when you set up the relevant contrasts for a triple t-test at the highest level this will automagically be calculated for every lower- level contrast. That is, at the highest level you do not need to specify any of the event types - after feeding in all the lower-level feat directories in the higher-level GUI a set of tickboxes should appear which allow you to select the lower-level contrasts you want to have the higher-level comparison calculated on. The higher-level analysis is calculated using the unthresholded lower- level results. hope this helps Christian On 20 Jul 2007, at 19:16, Steward Carolyn wrote: > Hi, > > Thanks very much for your swift reply! I've had a go at inputting feat > directories of individual subjects where both event types have been > included as separate EVs but can't see how the event types are > distinguished between when you put them into higher level analysis. Is > there a particular way of setting up the EVs at the higher level so > that > the event types can be differentiated? > Also, do the post-stats thresholds set at the individual subject level > affect stats done at higher levels? > > Many thanks, > Carolyn > > > -----Original Message----- > From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On > Behalf Of Christian Beckmann > Sent: 20 July 2007 16:33 > To: [log in to unmask] > Subject: Re: [FSL] event-related fMRI analysis > > Hi > >> In my study there were 16 subjects who were scanned on 2 separate >> days. On day 1 they performed a cognitive task at baseline and again >> following the administration of a placebo or drug, and on day 2 this >> was repeated, such that each subject performed the task 4 times: at >> baseline ('BP') then placebo ('P') and at baseline ('BD') then drug >> ('D'). The task consisted of 2 event types A and B, and reaction >> times > >> (RTs) were obtained for each event. >> >> Firstly, I would like to use RT as a covariate. My questions are the >> following: >> 1. Can I combine the 2 different event types with their corresponding >> RTs in the same analysis or do they have to be analysed separately? >> i.e. will >> I need to analyse event type A for each subject and feed these feat >> directories into higher level analysis and repeat this for event type >> B? >> > > No, if your experiment involved two different event types you should > model both of these in a single lower-level design. Each event type > will > become a separate EV. RT information will also be a separate EV. > >> 2. Will I need to analyse the sessions (BP, P, BD and D) >> separately or > >> can each individual and each session be put into the same higher >> level > >> analysis with RT as a covariate? > > I guess the simplest would be to model this as a triple t-test, see > http://www.fmrib.ox.ac.uk/fsl/feat5/index.html > At an intermediate level you'd then use a fixed-effects model to > combine the two BP sessions. > >> 3. I'm unclear as to what people mean by demeaning covariates, please >> can you explain?! > > You remove the mean value from the time series of RTs - in the GLM as > applied to fMRI you use covariates to 'explain' intensity changes > in the > data.The mean image intensity is of no interest (at the first > level) and therefore is removed, i.e. the data is mean zero. > Therefore, all the covariates should be zero mean, too. > >> 4. I'm also not sure whether it would be appropriate to tick the >> orthogonalise boxes? >> > > I suggest you do not orthogonalise the RT regressor wrt any of the > other > ones - if you do and your EVs are positively correlated with RTs > you end > up boosting the EVs for A and/or B because by orthogonalising RTs any > amount of variance which could be explained either by A/B or RT > ends up > being attributed to A/B only. > >> I'd also like to look at the mean group BOLD responses in the 4 >> different conditions, and compare between them (e.g. D versus BD, D >> versus P). >> 1. Again, can I combine the 2 different event types in the same >> analysis or do they have to be analysed separately? > > see above > >> 2. Which is the best approach to do this, to put all data (each >> subject and each session) into a one factor 4 level repeated measures >> ANOVA? >> > I suggest triple t-test, , just specify the appropriate contrasts to > compare e.g. D to P hope this helps Christian > >> A couple of other things, do the post-stats set at the individual >> subject level affect stats done at higher levels? Also, I'm confused >> about what the difference is between inputting feat directories or >> cope images into higher level analysis. >> >> Many thanks! >> Carolyn > > ____ > Christian F. Beckmann > University Research Lecturer > Oxford University Centre for Functional MRI of the Brain (FMRIB) John > Radcliffe Hospital, Headington, Oxford OX3 9DU, UK. > [log in to unmask] http://www.fmrib.ox.ac.uk/~beckmann > tel: +44 1865 222551 fax: +44 1865 222717 > > This message has been checked for viruses but the contents of an > attachment > may still contain software viruses, which could damage your > computer system: > you are advised to perform your own checks. Email communications > with the > University of Nottingham may be monitored as permitted by UK > legislation. ____ Christian F. Beckmann University Research Lecturer Oxford University Centre for Functional MRI of the Brain (FMRIB) John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK. [log in to unmask] http://www.fmrib.ox.ac.uk/~beckmann tel: +44 1865 222551 fax: +44 1865 222717