Dear Maxwell:

I hope my answers are helpful.

Quoting Maxwell Boakye <[log in to unmask]>:

> Darren
>
> Can you help me with this
>
> What is the best way to compare activation areas common between two tasks.
>
> I have 8 subjects doing an active finger movement, 2 runs- analyzed and
> have con files (8 from each run)
> I have same 8 subjects doing passive finger movement, 2 runs-analyzed and
> have con files (8 from each run)

I'm not quite sure I understand the task organization. Is this a block or
event-related design in which you either have 1) subjects moving a finger or
resting or 2) having the finger moved for them or resting? If so then further
answers below. If not then I'll modify my responses based on your reply.


> I need to know differences in brain activation between 2 tasks-
> in normals and compare them to same tasks in
> spinal cord patients. I currently have done only 1 spinal cord patient.
> what is the best way to compare that to the data I have collected in
> normals -for a grant. ie can I do conjuction analysis b/n 1 SCI patient and
> 8 normals with respect to each task?

Comparing 8 subjects vs. 1 subject does violate assumptions of the general
linear model. However, my understanding is that t-tests are generally fairly
robust to such violations (although less robust for VBM). There can also be
issues if the error variances are different between groups (random effects
analyses assume these are close). The variance I believe is pooled across all
subjects by SPM.

Here are some SPM list citations about this issue.
http://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind01&L=SPM&P=R319845&I=-3
http://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind04&L=SPM&P=R160144&I=-3
http://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind01&L=SPM&P=R122309&I=-3

If you want to know the differences between groups then using a 2 sample t-test
you would compare the active con images from your normal group vs. the active
con image for the SCI subject, and similarly for the passive images. If you
want to examine group x condition interactions you would create for each
subject (both control and SCI) an image from the contrast of the difference
between active and passive runs. You could then put this into a similar 2
sample t-test as above.

If you want to look at common activations you would take the same sets of
con-images to the second level but you would have to use an ANOVA model with no
constant term. You would then set up two contrasts [1 0] for the control
subjects and [0 1] for the SCI subject. Selecting both contrasts would give you
the conjunction. Particularly given the potential problems noted above you
should use a conjunction null in order to say that both controls AND the SCI
subject showed significant effects.

How about after collecting SCI data in
> 8 patients

Same as above but now you have equal subjects so better designed. If you think
the control and SCI groups have different underlying variances I believe you
should choose non-sphericity correction, replications over subjects, error not
correlated.

>
> What is the best way to make the following comparisons
> Within group comparison-common areas of activation b/n passive and active
> task- is RFX better thsn conjunction analysis for this if I have enough
> subjects

for common activations within subjects- you again would use a conjunction at the
second level as above. However, as there are two images per subject they are
necessarily correlated so again the conjunction null would be recommended.

>
> difference in activation between passive task vs active task (?with 16 files
> from both runs). can I use 2-sample t-test here?

Within subject groups you should try to end up with a single image per subject.
So within each subject you would generate a contrast image of active-passive
and forward this to the second level. Do a one-sample t-test and the contrast
is either [1] = active-passive or [-1] which gives you passive-active.

>
> Between Group analyses b/n normals and patients:
> 8 normals vs 8 SCI (active movement con files, ? 16 from both runs)
> 8 normals vs 8 SCI (passive movement con files) or
> 8 normals (run1) vs 8 SCI (run 1) etc

see above.

> How does this change if I have only 1 or 2 SCI patients and I need the
> preliminary analysis for grant

as above, this isn't the best statistical design but seems reasonable to use for
preliminary data with the above caveats.
>
> Finally last question:
> What is the easiest way to do conjunction analysis for large samples-
> find the common areas activated by 8 subjects in each task in both runs

Conjunctions aren't really done this way- i.e., looking for common activations
across subject groups with each group having only 1 subject in it. i.e., you
couldn't take 8 subjects and do a conjunction of 8 single image contrasts. In
this case what you want is a one-sample t-test. If you use the con images
(these are the parameter estimates) what you are essentially saying is at each
voxel is the effect size different than 0.

>
> my understanding is that there is a way to do this using the confiles?

see above. you use the con images for analyses at the second level.


Hope this was helpful. I've fowarded the message to the SPM group as well so
that if I've made an error someone will hopefully point it out.

Regards,
Darren