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I suggest you use AFNi or DPARSF for the fALFF Kind regards Eduardo El jueves, 30 de junio de 2016, Julian Yaoan Cheng <[log in to unmask]> escribió: > Hello Eduardo, > > > Thank you for your suggestions. > > I will review the papers on aCompCor and see how I can integrate that with > the fsl modeling. > > I do include the motion parameters via the rp_*.txt files from SPM, but > this was admittedly an inadequate description since it would not have been > obvious without familiarity with SPM. > > > Best, > > Julian > ------------------------------ > *From:* FSL - FMRIB's Software Library <[log in to unmask] > <javascript:_e(%7B%7D,'cvml',[log in to unmask]);>> on behalf of > Eduardo Garza-Villarreal <[log in to unmask] > <javascript:_e(%7B%7D,'cvml',[log in to unmask]);>> > *Sent:* Wednesday, June 29, 2016 6:44:57 PM > *To:* [log in to unmask] > <javascript:_e(%7B%7D,'cvml',[log in to unmask]);> > *Subject:* Re: [FSL] Generating ALFF and fALFF from resting state data > > Hi Julian, > > It's ok if you don't use Global Signal, but you have to use something. I > recommend aCompCor: ( > http://www.sciencedirect.com/science/article/pii/S1053811911009657) > (http://www.sciencedirect.com/science/article/pii/S105381191400175X) > > Now, if you are using FSL then you need to work on the Residual data, not > the actual GLM results. The residual 4D rsfmri nifti file is the one you > need to use to continue. I suggest you include the motion parameters, not > just WM and CSF by the way, in the GLM. > > I can't comment exactly on how to do it in FSL because I've only used AFNI > for the GLM and fALFF. > > Hope this helps. > > Kind regards > > Eduardo > > > > Eduardo A. Garza-Villarreal, M.D., Ph.D. > > - CONACYT Research Fellow, *Investigaciones Clínicas, Instituto > Nacional de Psiquiatría, Mexico.* > - Visiting Senior Researcher, *Center of Functionally Integrative > Neuroscience, University of Aarhus, Denmark.* > > > On Wed, Jun 29, 2016 at 7:22 PM, Julian C <[log in to unmask] > <javascript:_e(%7B%7D,'cvml',[log in to unmask]);>> wrote: > >> Hello experts, >> >> I've been trying to replicate the methods in this paper using FSL 5.0.9 >> but have been having trouble progressing: "Hoptman et al 2010. Amplitude of >> low-frequency oscillations in schizophrenia: A resting state fMRI study". >> The relevant section on the processing is reproduced below: >> -- >> Resting state data were preprocessed as described elsewhere in detail >> (Margulies et al., 2007; Castellanos et al., 2008; Kelly et al., 2008). >> Briefly, the first 10 volumes were discarded to eliminate T1 relaxation >> effects. Images were then motion-corrected, time shifted, and despiked >> using AFNI (Cox, 1996). Next, time series were smoothed using a 6 mm FWHM >> Gaussian kernel and spatially normalized to MNI space (2×2×2 mm 3 >> resolution) using FSL (www.fmrib.ox.ac.uk/fsl). The MPRAGE >> image was segmented using FSL's FAST software to obtain the masks used to >> extract white matter and CSF time series from the BOLD images. The white >> matter (WM) and cerebrospinal fluid (CSF) time series were then averaged >> across voxels within each mask. These time series, as well as the global >> signal intensity and >> the time series for the six motion parameters were regressed out from >> each voxel's time series. Individual participant analyses were carried out >> with the GLM >> implemented in FSL's FEAT and power spectral density toolbox. The time >> series for the nuisance covariates (time series regressors for global >> signal, WM, CSF, and six motion parameters) were entered as predictors. The >> residual data were then linearly detrended. Then, based upon detrended >> residual data, the power >> spectral density of the data was calculated using FSL's tool (fslpspec). >> Two measures were obtained: ALFF and fALFF. ALFF represents the amplitude >> in the low-frequency band, whereas fALFF is the ratio of the amplitude in a >> low-frequency band to amplitude in the total frequency band. Here, the >> low-frequency >> range was the slow-4 band (0.027–0.073 Hz; Buzsaki and Draguhn, 2004; Di >> Martino et al., 2008). The details of computation can be found in Zang et >> al. (2007) and Zou et al. (2008). The resulting amplitude measures were >> converted into Z-scores by subtracting the global mean and dividing the >> global standard deviation. >> -- >> My background is in SPM so for the preprocessing portion I elected to use >> SPM12 to do the job since I'm more familiar with that; this includes >> segmentation of the whitematter/CSF masks. I will describe what I've done >> in the following sections, and if you have time to point out any errors I >> would very much appreciate it (the part where I am actually stuck on will >> be in the last section). >> >> [time series extraction] >> Using the segmented masks from SPM I used fslmeants to extract time >> series for both WM/CSF to be used later in the GLM as regressors. This part >> was fairly straight forward. >> >> [GLM] >> I opened the FEAT GUI interface and chose "First-level analysis" and >> "Statistics", then loaded in the 4D preprocessed image and confirmed both >> the number of volumes and TR were correct (I left the high pass filter >> cutoff at the default value of 100). On the "Stats" tab I changed to "Don't >> Add Motion Parameters" and specified the rp_*.txt file generated by SPM's >> realignment module using the "Select confound EVs text file(s)" button. >> Then, in the "Full model setup" popup window I specified 2* original EVs >> using the "Custom (1 entry per volume)" setting for basic shape, and >> selected "None" for convolution. I then left "Add temporal derivative" and >> "Apply temporal filtering" options enabled by default. The model was run >> with everything else not specified left at its default state. >> *Note: I only specifed 2 because I am only supplying WM and CSF >> regressors and elected not to include the global signal due to concerns on >> co-linearity. >> >> [ALFF and fALFF] >> This is where I am stuck. First the paper noted that they linearly >> detrended the residual data, but it is not clear to me how they did this >> (or why, as most of my search seemed to suggest detrending done prior to >> modeling, not after). Furthermore I cannot figure out how to use fslpspec >> to obtain the ALFF and fALFF measures as it doesn't seem to be producing >> any output when fed with the residual image (res4D.nii.gz). >> >> Any help will be appreciated as I'm currently totally stumped. >> >> Best, >> Julian >> > > -- Eduardo A. Garza-Villarreal, M.D., Ph.D. - CONACYT Research Fellow, *Investigaciones Clínicas, Instituto Nacional de Psiquiatría, Mexico.* - Visiting Senior Researcher, *Center of Functionally Integrative Neuroscience, University of Aarhus, Denmark.*