Well...... I would add that if you want to control the lowpass filtering with 
any decent degree of frequency-cutoff specificity I would not use the Gaussian 
lowpass filter in fslmaths, but something sharper (eg Butterworth) eg in 
matlab.  But generally we don't recommend doing lowpass.

Cheers.



> On 14 Apr 2015, at 15:08, Greg Burgess <[email protected]> wrote:
> 
> Just to comment on this, using the correct conversion factor of 2.355 is 
> critical for the low pass temporal filter sigma. The differences between low 
> pass filters using ‘2’ instead of ‘2.355’ seems to be very noticeable.
> 
> --Greg
> 
> ____________________________________________________________________
> Greg Burgess, Ph.D.
> Staff Scientist, Human Connectome Project
> Washington University School of Medicine
> Department of Anatomy and Neurobiology
> Phone: 314-362-7864
> Email: [email protected]
> 
>> On Apr 13, 2015, at 8:59 AM, Harms, Michael <[email protected]> wrote:
>> 
>> 
>> Hi,
>> Just wanted to mention, for purposes of documenting in this thread, that 
>> technically the conversion from FWHM to sigma is:
>> sigma = FWHM/2.355
>> http://en.wikipedia.org/wiki/Full_width_at_half_maximum
>> 
>> I believe the FEAT just uses "2" rather than "2.355" in the denominator for 
>> the calculation of the sigma for its high pass temporal filter because the 
>> Gaussian filter is very gradual anyway.
>> 
>> In the HCP pipelines, I believe that we use the technically correct factor 
>> of 1/2.355 for any conversion of FWHM to Sigma.
>> 
>> 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: [email protected]
>> 
>> From: Kimberly Stachenfeld <[email protected]>
>> Date: Sunday, April 12, 2015 4:22 PM
>> To: "[email protected]" <[email protected]>
>> Subject: [HCP-Users] rsfc preprocessing
>> 
>> Hi hcp-users,
>> 
>> I'm new to resting state connectivity analysis (and this list-serve), and I 
>> have a few basic questions about applying it to the HCP data. I'm using the 
>> minimally preprocessed REST1 data.
>> 
>> 1. The low-pass filtering seems "controversial", though commonly employed -- 
>> is there at this point an agreed-upon way to remove deleterious high 
>> frequency noise?
>> 
>> In addition, I'm having difficulty with temporally filtering the data in 
>> fsl. To bandpass data from .009 - .08 Hz, I'm running:
>> 
>> fslmaths nii_in -bptf 77.168.68 nii_out
>> 
>> where 77.16 = sigma_hipass = 1/(2 * TR * F_hicutoff), for TR = .72 and 
>> F_cutoff = .009
>> 
>> and  8.68 = sigma_lopass = 1/(2 * TR * F_locutoff), for TR = .72 and 
>> F_locutoff = .08
>> 
>> This seems correct (I at least confirmed with the feat gui that the 
>> conversion from cycle time to sigma is 1/(2*TR)). However, when I look at 
>> the data in the frequency domain, it looks like there is significant 
>> response left for frequencies below .009 Hz (picture attached) and very 
>> little between .01-.08. Does anyone know if I'm doing something incorrectly, 
>> or if the frequency cutoff for a Gaussian filter is just very gradual?
>> 
>> 2. Any additional preprocessing is recommended, besides temporal filter and 
>> what the minimal pre-processing has already enacted?
>> 
>> 3. What is an intelligent way to combine correlation matrices? Averaging 
>> (Power et al, 2011)? Binarizing the correlation matrix by setting the top 
>> 10% of voxels to 1 and the rest to 0, and averaging the binarized matrices 
>> (Yeo et al, 2011)? Either? Something fancier?
>> 
>> Any advice or additional resources would be enormously appreciated -- thanks 
>> very much!! 
>> 
>> Kim
>> 
>> -- 
>> Kimberly Stachenfeld, BS
>> Graduate Student
>> 236A Princeton Neuroscience Institute
>> Washington Road
>> Princeton, NJ 08544
>> 
>> [email protected]
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>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>> 
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