Joyce | 8 May 10:33
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SPM8

Dear MarsBaRistas,

Are there any plans to make a MarsBaR version for SPM8?
It would be very appreciated,
merci,

Joyce!

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Pablo Barttfeld | 9 May 19:19
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question on ReML estimation


Hi,
I am getting this error 

"?? Index exceeds matrix dimensions."

using the SPM ReML estimation
for fMRI designs, and I tried to use the alternative fmriStat as suggested in
the Marsbar faqs, but I still could not solve the problem.

 
The code is this:

1    des_path=spm_get('Files',filedir,'SPM.mat');
2    roi_files =
spm_get('Files',roidir,'*roi.mat');
3    des =
mardo(des_path);

4    forregion_number=1
5        roi =
maroi('load_cell', roi_files(region_number,:));
6        mY =
get_marsy(roi{:}, des, 'mean'); 
7        E =
estimate(des, mY);

8        mRes =
des_struct(E);
9        sY   = summary_data(mRes.marsY); 
(Continue reading)

Matthew Brett | 9 May 20:21
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Re: question on ReML estimation

Hi,

> "?? Index exceeds matrix dimensions."
>
> using the SPM ReML estimation
> for fMRI designs, and I tried to use the alternative fmriStat as suggested in
> the Marsbar faqs, but I still could not solve the problem.

Yes, that might be the SPM ReML failing to estimate the
autocovariance...  Or something else...

> 7        E =
> estimate(des, mY);
>
> 8        mRes =
> des_struct(E);
> 9        sY   = summary_data(mRes.marsY);

Line 8 gets the SPM structure from the estimated design, line 9 gets
the data that you have estimated on.  I can't now remember whether the
SPM structure includes a marsY, but in any case, the thing you are
trying to get with mRes.marsY is identical to to 'mY' - the data you
pass in for estimation on.

I presume that you wanted to estimate the autocovariance for each
region, then create a timecourse, with the autocovariance removed by
the estimated autocovariance filter.

For that you need to make sure that you are only extracting data for
one ROI at a time:
(Continue reading)

Yune Lee | 22 May 19:26
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discrepancy of cluster size between Marsbar and SPM

 
 Dear Marsbar users,
 
 I'm puzzled by the cluster size of an ROI that I extracted by using Marsbar's get SPM cluster function.
 So, at a particular coordinate,  the cluster size that SPM tables shows and Marsbar get is quite different although Marsbar's get SPM cluster function was at the exact threshold.
 Does anyone know why this happens and let me know which one I should trust.
 
 Thanks,
 YSL
 
 
 
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hyesuk74 | 26 May 22:27
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percent signal change for blocked-design fMRI

Hello,

I'm wondering if Marsbar allows for percent signal change to be extracted from
fMRI data collected using a blocked-design. Although I have not thoroughly
researched the Marsbar listserve, it seems that percent signal change in
Marsbar is only for event-related design. Is that correct or am I wrong?  I'd
like to confirm this before I try Marsbar with my data.
Thank you.

Sue

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Matthew Brett | 26 May 22:34
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Re: percent signal change for blocked-design fMRI

Hi,

> I'm wondering if Marsbar allows for percent signal change to be extracted from
> fMRI data collected using a blocked-design. Although I have not thoroughly
> researched the Marsbar listserve, it seems that percent signal change in
> Marsbar is only for event-related design. Is that correct or am I wrong?  I'd
> like to confirm this before I try Marsbar with my data.

It should be fine - in SPM an block design is just an event-related
design with long events.  You just need to specify the block (event)
length when calculating the signal change.

Best,

Matthew

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Annalaura Lagioia | 28 May 17:55
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Help needed

I am trying to train my self to the marsBaR working on matlab 7.2 and  
spm 5, I think I got trapped into the "uigetfile" bug as none of the  
mat.file are found even if I downloaded the latest marsbar version.
I wonder if there is out there any pious user who could follow me in  
this training as I am in real need to become able to run roi analysis  
and statistics for my fMRI doctoral research.
Any help in how to proceed ( if procedure to de-bug remained the same  
etc) is extremely Welcome.

Thank you so much,

AKhairya

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Gmane