I think we must be careful about including noisy large scale measurements as global nuisance covariates in the General Linear Model (GLM). The GLM assumes that the independent variables are measured almost without error (eg. see http://en.wikipedia.org/wiki/Errors-in-variables_models).  For instance, mean cortical thickness or mean global activity in fMRI (as the mean of many values) should not be as noisy as Intracranial Volume estimates (or the estimated volume of any neuroanatomical structure).

-Jorge




De: Anderson Winkler <andersonwinkler@hotmail.com>
Para: freesurfer@nmr.mgh.harvard.edu
Enviado: Lunes 26 de marzo de 2012 13:56
Asunto: Re: [Freesurfer] Cortical Normalization Questions

Hi Jeff and all,

For normalization (i.e., divide the measurement under study by some
global measurement), I would not argue favourably, as this procedure can
bias the results in the opposite direction if a global effect is present.

Instead, include it as a covariate is not as harmful. My suggestion is,
when there is no clear approach about using or not a global measurement
as a nuisance, the relationships between the measurement under study,
the independent variable, and the putative nuisance should be
calculated, and models with and without the nuisance should be analysed
and presented. The discussion should consider both analyses together,
and enough information should be presented so that the final
interpretation is left to the reader.

Specifically for area, I suggest analysing and presenting two models:
(1) without any global measurement and (2) with global area as nuisance.

If brain volume (whichever way it is measured) is to be considered a
potential nuisance for the disorder you are analysing, it can be
included in the model #2 above, even given that they are not orthogonal
to each other, and are related to global area. Non-orthogonality 
between the nuisance variables is not a problem as it is when effects of
interest are involved.

Hope this helps!

All the best,

Anderson


On 23/03/12 11:29, Michael Harms wrote:
> Our reply to that is here
> http://bjp.rcpsych.org/content/196/5/414.2.long
>
> which reminded me of other papers that have also used a global thickness
> measure to covary for mean cortical thickness and thereby "address whether
> any regional thickness differences were in excess of global cortical
> thickness differences between groups" -- see references [1,4] in our
> Reply.
>
> cheers,
> -MH
>
>> Hi Michael and others,
>>
>> maybe it's this one:
>>
>> http://bjp.rcpsych.org/content/196/5/414.1.long
>>
>> best,
>> -joost
>>
>>
>> On Fri, Mar 23, 2012 at 2:15 AM, Michael Harms
>> <mharms@conte.wustl.edu>wrote:
>>
>>> Hi Jeff,
>>> I personally like the idea of using average thickness as a covariate to
>>> control for a reduction in "whole brain" thickness, and have used that
>>> approach in a paper.  If the Abstract that you mentioned indicated that
>>> this is flawed, I'd be curious to know what the reason was...
>>>
>>> cheers,
>>> -MH
>>>
>>> On Thu, 2012-03-22 at 21:00 -0400, Bruce Fischl wrote:
>>>> Hi Jeff
>>>>
>>>> yes, I think this is still our recommendation for thickness, although
>>>> perhaps David Salat can verify. As far as surface area, you might get
>>>> Anderson Winkler to send you a preprint of his newly accepted paper on
>>>> surface area comparisons and how to do them properly. I would have
>>> said
>>>> normalize by the 2/3 root of ICV (maybe David can comment on this as
>>> well)
>>>> cheers
>>>> Bruce
>>>>
>>>>
>>>> On Thu, 22 Mar 2012, Jeff Sadino wrote:
>>>>
>>>>> Hello,
>>>>> For cortical thickness normalizations, Bruce said not to normalize
>>> based on a HBM
>>>>> abstract
>>>>> (
>>> http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg06646.html).
>>>  Is
>>>>> this still the consensus?
>>>>>
>>>>> For cortical volume, it is pretty standard to normalize to eTIV.
>>>>>
>>>>> For cortical surface area (jacobian), I couldn't find any
>>> information
>>> on the wiki.
>>>>>  Does anyone have any recommendations?
>>>>>
>>>>> Thank you,
>>>>> Jeff
>>>>>
>>>>>
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