Christian,
I'm not sure I understand correctly your answer. So may be I was not
clear enough.
For SICA, I have an observation matrix (xij) of size TxV (T=time, V=voxels).
I calculate the mean for each row (i) and remove it to xij for centering
the data.
This corresponds to a referential (with T axis) shift and is commonly
used in PCA.
BUT, generally we do not do the same for the column (j).
If I read the Melodic code the data centering is performed for each i
and each j.
and I do not understand why.
Thanks for your answer
Best
Pierre Lafaye de Michaux.
> Hi,
>
> You're partly right, in melodic the temporal mean is first removed and
> re-introduced after the decomposition as outlined in the technical
> report (see first few lines in section 'Maximum Likelihood estimation'
> of the technical report available at our website for the technical
> treatment).
> The mean time course in effect corresponds to a spatial map where all
> voxels contribute equally, i.e. it is a signal which does not contain
> any spatial specificity - as such, the mean time course itself carries
> no useful information wrt the final (spatially specific, i.e. not
> everywhere the same) maps, particularly not during the estimation
> stage. The part which lies in the space of the modelled time courses
> is only useful in that it re-sahpes the corresponding time courses
> while leaving the spatial maps in tact.
> hope this helps
> best
> christian
>
> On 6 Jun 2007, at 15:35, Pierre Lafaye de Micheaux wrote:
>
>> Dear members,
>>
>> When i do a PCA in melodic, i get the following message:
>>
>>> Excluding voxels with constant value
>>> Data size : 120 x 158227
>>> Removing mean image ... done
>>> Estimating data covariance ... done
>>> Removing mean time course ... done
>>> Starting PCA ... done
>>
>> So, it seems that you center the data BOTH for the lines and the
>> columns.
>> I thought that if you make a spatial PCA, you should center the data
>> only for the variables (time) and not for the statistical units
>> (space): removing mean tim course only.
>> In a temporal PCA i thought you should also center only for the
>> variables (space in this case): removing mean image only.
>>
>> Am i right? Do you have a theoretical justification for the procedure
>> used in Melodic?
>>
>> Best regards,
>>
>> Pierre Lafaye de Micheaux, Ph.D.
>>
>> --Pierre Lafaye de Micheaux
>> Bureau 210, bâtiment BSHM
>> 1251 avenue centrale BP 47
>> 38040 GRENOBLE Cedex 09
>> FRANCE
>>
>> Tél.: 04.76.82.58.73 / Fax: 04.76.82.56.65
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>> http://www.biostatisticien.eu
>
> ____
> Christian F. Beckmann
> University Research Lecturer
> Oxford University Centre for Functional MRI of the Brain (FMRIB)
> John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK.
> [log in to unmask] http://www.fmrib.ox.ac.uk/~beckmann
> tel: +44 1865 222551 fax: +44 1865 222717
--
Michel Dojat
Grenoble Institut des Neurosciences (GIN)
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