Hi
Yes, the feat pre-processing has an impact on melodic, including estimation of the model order
hth
Christian
On 10 Dec 2009, at 22:41, Kundu, Prantik (NIH/NIMH) [F] wrote:
> Related, how important are FEAT's intensity modification steps prior to the melodic process?
> ________________________________________
> From: Christian F. Beckmann [[log in to unmask]]
> Sent: Thursday, December 10, 2009 5:28 PM
> To: [log in to unmask]
> Subject: Re: Melodic Steps
>
> Hi
>
> Multiple differences:
> - You're not using any variance-normalisation - even with the vn switched off melodic does calculate some relevant quantities (but doesn;t perform the VN scaling then)
> - 2a works differently for multiple reasons, amongst others, of computational complexity
> - 2b does not remove the mean again - otherwise you might actually remove important spatial signal signatures
> hth
> Christian
>
>
> On 9 Dec 2009, at 23:48, Srinivas wrote:
>
>> Hi,
>>
>> I am implementing temporal concatentation approach of Melodic in MATLAB
>> and trying to follow the steps as mentioned in the melodic documentation.
>>
>> 1. Data - Read data for each subject and arrange in time points by voxels.
>> Time series mean is removed per voxel.
>>
>> 2. a. First PPCA - Stack data of all subjects spatially and compute eigen
>> vectors. Project data of each subject onto the common eigen space
>> (Whitening).
>>
>> b. Second PPCA - Remove mean of timeseries per voxel for each subject's
>> reduced data. Stack all subjects data temporally and compute eigen vectors.
>> Project stacked data on to the common eigen space.
>>
>> 3. PICA - Reduced data from the second PPCA step is used to compute
>> component spatial maps and time courses. Spatial maps thus obtained are
>> indepenent.
>>
>> After doing step 2b., group PCA map in my code is not matching the spatial
>> map obtained using Melodic. Please let me know if I am missing some steps.
>>
>>
>> Thanks,
>> Srinivas
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