HI Jesper,
That all sounds reasonable to me.
--
Michael Harms, Ph.D.
-----------------------------------------------------------
Conte Center for the Neuroscience of Mental Disorders
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave. Tel: 314-747-6173
St. Louis, MO 63110 Email: [log in to unmask]
On 11/28/12 6:41 PM, "Jesper Andersson" <[log in to unmask]> wrote:
>Hi again,
>
>I all my reasoning I am assuming that whatever registration we are
>talking about it is unbiased.
>
>> The unknown in my mind is to what extent the derivation of the original
>> ROIs depends on the registration algorithm. My thought is that you
>>won't
>> necessarily get the same ROIs using a algorithm based on FLIRT as you
>> would with FNIRT, and that the degree of similarity or dissimilarity
>>would
>> be dependent on the precise manner in which the original ROIs were
>> obtained. For example, if the ROIs were based on significant fMRI
>> activation in a large group of subjects, it is easy to envision that
>>ROIs
>> based on FLIRTING the subjects into MNI space would be larger than those
>> obtained by FNIRTING them into MNI space, since FLIRT registration would
>> tend to spread the activation out over a larger area in MNI space.
>
>I honestly don't see how this could be done in a particularly objective
>way. Unless you actually partition the entire brain with some heroic
>battery of tasks you will always be stuck with a final decision how
>threshold the individual maps and then how to threshold the aggregate
>map.
>> On the
>> other hand, if the ROIs are based on classifying all voxels in each
>> individual subject, and then assigning the class based on maximum
>> probability after transform into MNI space, then those ensuing ROIs
>>might
>> be somewhat independent of whether the transformation used FLIRT or
>>FNIRT,
>
>I guess I would say this is the only sensible way of building ROIs in
>standard space so my assumption would be that it was done in that way.
>
>> since the ordered rankings of class probabilities within each voxel
>>might
>> not change too much, even if the probabilities themselves change (with
>> FNIRT expected to have more of the probability contained in a fewer
>>number
>> of classes).
>
>I would be surprised if the, given a reasonable sized group, fnirt or
>flirt would make much of a difference as to where the borders between the
>regions were put. I agree that you could probably get better borders from
>a smallish group with fnirt than with flirt.
>
>Regardless of that I still think that when you then have an additional
>subject that you want to use those ROIs in you would want to do the best
>possible job of the registration, and that would most likely be
>non-linear.
>
>What do you think?
>
>Jesper
>
>>
>> Does that seem like a reasonable expectation?
>>
>> cheers,
>> -MH
>>
>>
>> --
>> Michael Harms, Ph.D.
>>
>> -----------------------------------------------------------
>> Conte Center for the Neuroscience of Mental Disorders
>> Washington University School of Medicine
>> Department of Psychiatry, Box 8134
>> 660 South Euclid Ave. Tel: 314-747-6173
>> St. Louis, MO 63110 Email: [log in to unmask]
>>
>>
>>
>>
>> On 11/28/12 1:56 PM, "Jesper Andersson" <[log in to unmask]> wrote:
>>
>>> Hi Michael and Donald,
>>>
>>> I think what professor Ashburner is saying is that it is always a good
>>> idea to use the best possible registration. Let's say we have some ROI
>>> that has been defined in a bunch of subjects that have been linearly
>>> transformed (FLIRTED) into standard space and then averaged and
>>> thresholded. If the number of subjects was big enough we would expect
>>> that ROI to be a quite good standard space representation of the region
>>> in question, much better than we would expect if we just drew one ROI
>>>in
>>> one subject.
>>>
>>> Let's now say we have some subject we want to apply that ROI to. I
>>>think
>>> it would make sense to use the best possible registration (non-linear,
>>> though maybe not SPM ;-) ) to register that subject to standard space.
>>> After all, using a linear registration is likely to achieve a worse
>>> matching of that subject to standard space, and hence to the ROI in
>>> question.
>>>
>>> Does this make sense?
>>>
>>> Jesper
>>>
>>> On 28 Nov 2012, at 20:46, Michael Harms wrote:
>>>
>>>> Hi Donald,
>>>> I don't see any way to just warp the data. What you really want to
>>>>know
>>>> in your example is what the Harvard-Oxford labels would have been had
>>>> they
>>>> been derived using registrations that involved FNIRT. That seems an
>>>> empirical question to me. Ideally, one would want to use a set of
>>>>ROIs
>>>> derived using the same templates and algorithms as the study to which
>>>> those ROIs are going to be applied. But since that isn't always
>>>> possible
>>>> you have a make a decision informed by the needs/questions of your
>>>> particular study.
>>>>
>>>> cheers,
>>>> -MH
>>>>
>>>> --
>>>> Michael Harms, Ph.D.
>>>>
>>>> -----------------------------------------------------------
>>>> Conte Center for the Neuroscience of Mental Disorders
>>>> Washington University School of Medicine
>>>> Department of Psychiatry, Box 8134
>>>> 660 South Euclid Ave. Tel: 314-747-6173
>>>> St. Louis, MO 63110 Email: [log in to unmask]
>>>>
>>>>
>>>>
>>>>
>>>> On 11/28/12 1:24 PM, "MCLAREN, Donald" <[log in to unmask]>
>>>>wrote:
>>>>
>>>>> Michael,
>>>>>
>>>>> Excellent points. However, the underlying question still remains
>>>>>about
>>>>> using existing ROI with newer normalization approaches.
>>>>>
>>>>> For example, would using the Harvard-Oxford labels be bad if you use
>>>>> FSLs FNIRT as they were created with FLIRT? Or is there a way to warp
>>>>> the data?
>>>>>
>>>>> We are not using DARTEL, just SPM's regular non-linear warp.
>>>>>
>>>>> On Wed, Nov 28, 2012 at 1:50 PM, Michael Harms
>>>>><[log in to unmask]>
>>>>> wrote:
>>>>>> I would think that you might raise some eyebrows using ROIs obtained
>>>>>> using
>>>>>> FSL's FLIRT in data normalized using SPM's non-linear (Dartel?)
>>>>>>tool,
>>>>>> due
>>>>>> to the big potential difference between linear (affine) and
>>>>>>non-linear
>>>>>> approaches. Of course, it would depend on the anatomical precision
>>>>>> that
>>>>>> you want/need for your particular study and whether the ROIs involve
>>>>>> regions that are particularly sensitive to non-linear registration.
>>>>>>
>>>>>> cheers,
>>>>>> -MH
>>>>>>
>>>>>> --
>>>>>> Michael Harms, Ph.D.
>>>>>>
>>>>>> -----------------------------------------------------------
>>>>>> Conte Center for the Neuroscience of Mental Disorders
>>>>>> Washington University School of Medicine
>>>>>> Department of Psychiatry, Box 8134
>>>>>> 660 South Euclid Ave. Tel: 314-747-6173
>>>>>> St. Louis, MO 63110 Email: [log in to unmask]
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> On 11/28/12 11:43 AM, "MCLAREN, Donald" <[log in to unmask]>
>>>>>> wrote:
>>>>>>
>>>>>>> Dear SPM/FSL users,
>>>>>>>
>>>>>>> It seems that there are several templates (SPM v FSL) as well as
>>>>>>> different normalization routines that could result in slight
>>>>>>> variations of the localization of the results. Do I need to worry
>>>>>>> about these small differences between methods?
>>>>>>>
>>>>>>> In particular, I want to know if I can take regions defined in a
>>>>>>> study
>>>>>>> using FLIRT in FSL and use them in my study that has been processed
>>>>>>> with SPM's non-linear normalization tool. Can I use them as is or
>>>>>>>is
>>>>>>> there a transform that can I compute and/or apply to the ROIs to
>>>>>>>get
>>>>>>> them into the SPM normalized space.
>>>>>>>
>>>>>>> Thank you in advance for your input.
>>>>>>>
>>>>>>> Best Regards, Donald McLaren
>>>>>>> =================
>>>>>>> D.G. McLaren, Ph.D.
>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>> Hospital
>>>>>>> and
>>>>>>> Harvard Medical School
>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>> Website: http://www.martinos.org/~mclaren
>>>>>>> Office: (773) 406-2464
>>>>>>> =====================
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