:orphan: .. _ahelp_3dReHo: ****** 3dReHo ****** .. contents:: :local: | .. code-block:: none REHO/Kendall W code, written by PA Taylor (July, 2012), part of FATCAT (Taylor & Saad, 2013) in AFNI. ReHo (regional homogeneity) is just a renaming of the Kendall's W (or Kendall's coefficient of concordance, KCC, (Kendall & Babington Smith, 1939)) for set of time series. Application to fMRI data was described in paper: <> by Zang, Jiang, Lu, He, and Tiana (2004, NeuroImage), where it was applied to the study of both task and resting state functional connectivity (RSFC). * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * + USAGE: This program is made to read in data from 4D time series data set and to calculate Kendall's W per voxel using neighborhood voxels. Instead of the time series values themselves, Kendall's W uses the relative rank ordering of a 'hood over all time points to evaluate a parameter W in range 0-1, with 0 reflecting no trend of agreement between time series and 1 reflecting perfect agreement. From W, one can simply get Friedman's chi-square value (with degrees of freedom equal to `the length of the time series minus one'), so this can also be calculated here and returned in the second sub-brick: chi-sq = (N_n)*(N_t - 1)*W, with N_dof = N_t - 1, where N_n is the size of neighborhood; N_t is the number of time points; W is the ReHo or concordance value; and N_dof is the number of degrees of freedom. A switch is included to have the chi-sq value output as a subbrick of the ReHo/W. (In estimating W, tied values are taken into account by averaging appropriate rankings and adjusting other factors in W appropriately, which only makes a small difference in value, but the computational time still isn't that bad). * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * + COMMAND: 3dReHo -prefix PREFIX -inset FILE {-nneigh 7|19|27} \ {-chi_sq} {-mask MASK} {-in_rois INROIS} * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * + RUNNING, need to provide: -prefix PREFIX :output file name part. -inset FILE :time series file. -chi_sq :switch to output Friedman chi-sq value per voxel as a subbrick. -mask MASK :can include a whole brain mask within which to calculate ReHo. Otherwise, data should be masked already. -nneigh NUMBER :number of voxels in neighborhood, inclusive; can be: 7 (for facewise neighbors, only), 19 (for face- and edge-wise neighbors), 27 (for face-, edge-, and node-wise neighbors). The default is: 27. -neigh_RAD R :for additional voxelwise neighborhood control, the radius R of a desired neighborhood can be put in; R is a floating point number, and must be >1. Examples of the numbers of voxels in a given radius are as follows (you can roughly approximate with the ol' 4*PI*(R^3)/3 thing): R=2.0 -> V=33, R=2.3 -> V=57, R=2.9 -> V=93, R=3.1 -> V=123, R=3.9 -> V=251, R=4.5 -> V=389, R=6.1 -> V=949, but you can choose most any value. -neigh_X A -neigh_Y B :as if *that* weren't enough freedom, you can even have -neigh_Z C ellipsoidal volumes of voxelwise neighbors. This is done by inputing the set of semi-radius lengths you want, again as floats/decimals. The 'hood is then made according to the following relation: (i/A)^2 + (j/B)^2 + (k/C)^2 <=1. which will have approx. V=4*PI*A*B*C/3. The impetus for this freedom was for use with data having anisotropic voxel edge lengths. -box_RAD BR :for additional voxelwise neighborhood control, the one can make a cubic box centered on a given voxel; BR specifies the number of voxels outward in a given cardinal direction, so the number of voxels in the volume would be as follows: BR=1 -> V=27, BR=2 -> V=125, BR=3 -> V=343, etc. In this case, BR should only be integer valued. -box_X BA -box_Y BB :as if that *still* weren't enough freedom, you can have -box_Z BC box volume neighborhoods of arbitrary dimension; these values put in get added in the +/- directions of each axis, so the volume in terms of number of voxels would be calculated: if BA = 1, BB = 2 and BC = 4, then V = (1+2*1)*(1+2*2)*(1+2*4) = 135. --> NB: you can't mix-n-match '-box_*' and '-neigh_*' settings. Mi dispiace (ma sol'un po). -in_rois INROIS :can input a set of ROIs, each labelled with distinct integers. ReHo will be calculated per ROI. The output for this info is in a file called PREFIX_ROI_reho.vals (or PREFIX_ROI_reho_000.vals, PREFIX_ROI_reho_001.vals, etc. if the INROIS has >1 subbrick); if `-chi_sq' values are being output, then those values for the ROIs will be output in an analogously formatted file called PREFIX_ROI_reho.chi (with similar zeropadded numbering for multibrick input). As of March, text format in the *.vals and *.chi files has changed: it will be 2 columns of numbers per file, with the first column being the ROI (integer) value and the second column being the ReHo or Chi-sq value. Voxelwise ReHo will still be calculated and output. + OUTPUT: [A] single file with name, e.g., PREFIX+orig.BRIK, which may have two subbricks (2nd subbrick if `-chi_sq' switch is used): [0] contains the ReHo (Kendall W) value per voxel; [1] contains Friedman chi-square of ReHo per voxel (optional); note that the number of degrees of freedom of this value is the length of time series minus 1. [B] can get list of ROI ReHo values, as well (optional). * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * + EXAMPLE: 3dReHo \ -mask MASK+orig. \ -inset REST+orig \ -prefix REST_REHO \ -neigh_RAD 2.9 \ -chi_sq * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * If you use this program, please reference the introductory/description paper for the FATCAT toolbox: Taylor PA, Saad ZS (2013). FATCAT: (An Efficient) Functional And Tractographic Connectivity Analysis Toolbox. Brain Connectivity 3(5):523-535.