Hi Christian,
I can't seem to get this to work (I'm not automatically getting the
tickboxes appearing at higher level), which makes me wonder whether I'm
doing things correctly at the individual subject level. At the
individual level, when I get into full model setup I put in 2 EVs (one
for event A and one for event B) and set up 2 contrasts: OC1 (event
A>rest) = 0 1, OC2 (event B>rest) = 0 1. Is this where I'm going wrong?
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 22:35
To: [log in to unmask]
Subject: Re: [FSL] event-related fMRI analysis
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
>
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____
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
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