Dear Tommy,
Talairach and MNI are the same coordinate system in terms of their
origin and definition of the axes. The difference between them is that
different brain atlases are used to interpret the coordinates in terms
of Brodmann areas. Again, I don't think that with spatial precision of
MEG beamformers the distinction between the two systems makes any
difference. If you want to be very strict you can just use the
Talairach atlas to interpret the coordinates that you get from your
SPM analysis.
Best,
Vladimir
On Thu, Apr 8, 2010 at 9:45 AM, Karsten Hoechstetter
<[log in to unmask]> wrote:
> Dear Tommy,
>
> Since, the exported SAM images are in Talairach
> dimension, when I entered them into SPM for 2nd level analysis, are
>
> the output coordinates of activations in Talairach or MNI? Do I need
>
> to make any conversion?
>
> I forward this question to Vladimir Litvak, since I am not sure how SPM
> behaves when it receives Talairach input. Since SPM does not "know" the
> input is Talairach, I don't think it applies any intrinsic conversion.
> Vladimir will know.
>
> Best,
> Karsten
>
> PS: The BESA beamformer is not SAM, but a time-frequency LCMV (linearly
> constrained minimum variance) beamformer.
>
> --------------------------------------
> Dr. Karsten Hoechstetter
> MEGIS Software GmbH
> Gräfelfing, Germany
> HRB München 109956
> CEO Dr. Michael Scherg
> --------------------------------------
>
> -----Original Message-----
> From: [log in to unmask] [mailto:[log in to unmask]]
> Sent: Donnerstag, 8. April 2010 00:57
> To: [log in to unmask]
> Subject: RE: MEG_Normalization
>
> Dear Dr Hoechstetter
>
> Thank you for the information. I will try on both platform and compare
> the results.
>
> One quick question. Since, the exported SAM images are in Talairach
> dimension, when I entered them into SPM for 2nd level analysis, are
> the output coordinates of activations in Talairach or MNI? Do I need
> to make any conversion?
>
> Thank you once again.
>
> Tommy
>
>
>
>
> Quoting Karsten Hoechstetter <[log in to unmask]>:
>
>> Dear Tommy,
>>
>> Just one comment on Vladimir's response: He is right, the volume images in
>> BESA are already spatially normalized, they are all in Talairach
> dimensions.
>> There's no need for additional spatial normalization prior to statistical
>> analysis.
>>
>> Note that the new BESA version (BESA Research 5.3) has a direct interface
> to
>> MATLAB, and on the BESA website www.besa.de/updates/matlab there's a
> little
>> tool that allows to statistically compare two groups of BESA-generated 3D
>> volume images, making use of the statistics functions of the 'Fieldtrip'
>> toolbox. You could compare the outcome of this script to the SPM
> statistics
>> output.
>>
>> If you encounter problems or have further questions, please let me know.
>>
>> Best wishes,
>> Karsten
>>
>> --------------------------------------
>> Dr. Karsten Hoechstetter
>> MEGIS Software GmbH
>> Gräfelfing, Germany
>> HRB München 109956
>> CEO Dr. Michael Scherg
>> --------------------------------------
>>
>> -----Original Message-----
>> From: Vladimir Litvak [mailto:[log in to unmask]]
>> Sent: Dienstag, 6. April 2010 10:47
>> To: [log in to unmask]
>> Cc: [log in to unmask]; [log in to unmask]
>> Subject: Re: MEG_Normalization
>>
>> Dear Tommy,
>>
>> On Tue, Apr 6, 2010 at 12:28 AM, <[log in to unmask]> wrote:
>>
>>> I am working on a set of MEG data on motor function and wonder if I could
>>> ask you a couple of questions?
>>>
>>> 1) I have analyzed the data in BESA using beamforming method. I exported
>>> individual's images and entered them into SPM for group analysis. So, the
>>> first question is how do I spatially normalized individual image into MNI
>>> template space. I searched spm_eeg but can't seem to find a GUI for
>>> normalization.
>>
>> This functionality is in SPM/fMRI. It is possible to normalize your
>> individual structural to the template and then apply the same
>> normalization to the functional images. However, in the case of
>> beamformer images I'm not sure it is really necessary because it is
>> quite likely that the output of BESA beamformer is normalized already
>> and even if not, the level of spatial detail in those images is not
>> such that normalization would improve things. You should just make
>> sure the images are in decent registration with each other and perhaps
>> just smooth them a little.
>>
>>>
>>> 2) Output from 2nd level analysis shows activation over broad brain
>> regions.
>>> However, when I tried to churn out the t and p values using "whole
> brain",
>>> only values of activations in one hemisphere showed up (these are the
> ones
>>> with strong t values), and weaker activations in the other hemisphere (my
>>> region of interest) did not show up. Although, when I used xjview, I
> could
>>> use the cursor to source out the t and p values, i.e. they are there but
>>> kind of drowned by the very strong hemispheric activation.
>>>
>>
>> This is not an SPM problem per se but a problem with you images. If
>> you know in advance that you are interested in a particular ROI you
>> should not do SPM of the whole brain but either use an explicit mask
>> or a small volume correction. Also, do you compare two conditions or
>> just do a single sample t-test on your images? The latter is not valid
>> because the values in the images are non-negative so it doesn't make
>> sense to compare them to zero. This has been discussed on the SPM list
>> before. Finally, there are some diagnostic tools in SPM (the 'plot'
>> button in the 'Results' interface) that make it possible to check why
>> you get high or low t-values for a particular voxel (for instance is
>> it because of a single outlier, weak effect or high inter-subject
>> variance?). Sometimes it might be useful to use grand mean scaling to
>> reduce the variance. That's what is presently done for source
>> reconstruction images generated by SPM.
>>
>> Best,
>>
>> Vladimir
>>
>>> Please advise what I should do to resolve these problems?
>>>
>>> Any help is appreciated. Thank you.
>>>
>>> Regards
>>>
>>> Tommy Ng
>>> PhD Candidate
>>> MACCS|Macquarie University
>>>
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>>>
>>>
>>
>>
>
>
>
> Tommy Ng
> PhD Candidate
> MACCS|Macquarie University
>
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>
>
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