Mariela,

I've pooled a list (although it might not be exhaustive and
repetitious in place). Its compiled from the help sections of
spm_spm.m, spm_fmri_spm_ui.m, and spm_spm_ui.m.

% Required fields of SPM:
%
% xY.VY - nScan x 1 struct array of image handles (see spm_vol)
%         Images must have the same orientation, voxel size and data type
%       - Any scaling should have already been applied via the image handle
%         scalefactors.
%
% xX    - Structure containing design matrix information
%       - Required fields are:
%         xX.X      - Design matrix (raw, not temporally smoothed)
%         xX.name   - cellstr of parameter names corresponding to columns
%                     of design matrix
%       - Optional fields are:
%         xX.K      - cell of session-specific structures (see spm_filter)
%                   - Design & data are pre-multiplied by K
%                     (K*Y = K*X*beta + K*e)
%                   - Note that K should not smooth across block boundaries
%                   - defaults to speye(size(xX.X,1))
%         xX.W      - Optional whitening/weighting matrix used to give
%                     weighted least squares estimates (WLS). If not specified
%                     spm_spm will set this to whiten the data and render
%                     the OLS estimates maximum likelihood
%                     i.e. W*W' = inv(xVi.V).
%
% xVi   - Structure describing intrinsic temporal non-sphericity
%       - Required fields are:
%         xVi.Vi    - array of non-sphericity components
%                   - defaults to {speye(size(xX.X,1))} - i.i.d.
%                   - specifying a cell array of constraints (Qi)
%                     These constraints invoke spm_reml to estimate
%                     hyperparameters assuming V is constant over voxels.
%                     that provide a high precise estimate of xX.V
%       - Optional fields are:
%         xX.V      - Optional non-sphericity matrix.  Cov(e) = sigma^2*V
%                     If not specified spm_spm will compute this using
%                     a 1st pass to identify significant voxels over which
%                     to estimate V.  A 2nd pass is then used to re-estimate
%                     the parameters with WLS and save the ML estimates
%                     (unless xX.W is already specified).
%
% xM    - Structure containing masking information, or a simple column vector
%         of thresholds corresponding to the images in VY [default: -Inf]
%       - If a structure, the required fields are:
%         xM.TH - nVar x nScan matrix of analysis thresholds, one per image
%         xM.I  - Implicit masking (0=>none, 1 => implicit zero/NaN mask)
%         xM.VM - struct array of explicit mask image handles
%       - (empty if no explicit masks)
%               - Explicit mask images are >0 for valid voxels to assess.
%               - Mask images can have any orientation, voxel size or data
%                 type. They are interpolated using nearest neighbour
%                 interpolation to the voxel locations of the data Y.
%       - Note that voxels with constant data (i.e. the same value across
%         scans) are also automatically masked out.
%
% swd   - Directory where the output files will be saved [default: pwd]
%         If exists, it becomes the current working directory.

% creates SPM with the following fields
%
%       xY: [1x1 struct] - data structure
%    nscan: [double]     - vector of scans per session
%      xBF: [1x1 struct] - Basis function structure   (see spm_fMRI_design)
%     Sess: [1x1 struct] - Session structure          (see spm_fMRI_design)
%       xX: [1x1 struct] - Design matrix structure    (see spm_fMRI_design)
%      xGX: [1x1 struct] - Global variate structure
%      xVi: [1x1 struct] - Non-sphericity structure
%       xM: [1x1 struct] - Masking structure
%    xsDes: [1x1 struct] - Design description structure
%
%
%     SPM.xY
%             P: [n x ? char]       - filenames
%            VY: [n x 1 struct]     - filehandles
%            RT: Repeat time
%
%    SPM.xGX
%
%       iGXcalc: {'none'|'Scaling'} - Global normalization option
%       sGXcalc: 'mean voxel value' - Calculation method
%        sGMsca: 'session specific' - Grand mean scaling
%            rg: [n x 1 double]     - Global estimate
%            GM: 100                - Grand mean
%           gSF: [n x 1 double]     - Global scaling factor
%
%    SPM.xVi
%            Vi: {[n x n sparse]..} - covariance components
%          form: {'none'|'AR(1)'}   - form of non-sphericity
%
%     SPM.xM
%             T: [n x 1 double]     - Masking index
%            TH: [n x 1 double]     - Threshold
%             I: 0
%            VM:                    - Mask filehandles
%            xs: [1x1 struct]       - cellstr description

% Variables saved in the SPM stucture
%
% xY.VY         - nScan x 1 struct array of memory mapped images
%                 (see spm_vol for definition of the map structure)
% xX            - structure describing design matrix
% xX.D          - design definition structure
%                 (See definition in main body of spm_spm_ui.m)
% xX.I          - nScan x 4 matrix of factor level indicators
%                 I(n,i) is the level of factor i corresponding to image n
% xX.sF         - 1x4 cellstr containing the names of the four factors
%                 xX.sF{i} is the name of factor i
% xX.X          - design matrix
% xX.xVi        - correlation constraints for non-spericity correction
% xX.iH         - vector of H partition (condition effects) indices,
%                 identifying columns of X correspoding to H
% xX.iC         - vector of C partition (covariates of interest) indices
% xX.iB         - vector of B partition (block effects) indices
% xX.iG         - vector of G partition (nuisance variables) indices
% xX.name     - p x 1 cellstr of effect names corresponding to columns
%                 of the design matrix
%
% xC            - structure array of covariate details
% xC(i).rc      - raw (as entered) i-th covariate
% xC(i).rcname  - name of this covariate (string)
% xC(i).c       - covariate as appears in design matrix (after any scaling,
%                 centering of interactions)
% xC(i).cname   - cellstr containing names for effects corresponding to
%                 columns of xC(i).c
% xC(i).iCC     - covariate centering option
% xC(i).iCFI    - covariate by factor interaction option
% xC(i).type    - covariate type: 1=interest, 2=nuisance, 3=global
% xC(i).cols    - columns of design matrix corresponding to xC(i).c
% xC(i).descrip - cellstr containing a description of the covariate
%
% xGX           - structure describing global options and values
% xGX.iGXcalc   - global calculation option used
% xGX.sGXcalc   - string describing global calculation used
% xGX.rg        - raw globals (before scaling and such like)
% xGX.iGMsca    - grand mean scaling option
% xGX.sGMsca    - string describing grand mean scaling
% xGX.GM        - value for grand mean (/proportional) scaling
% xGX.gSF       - global scaling factor (applied to xGX.rg)
% xGX.iGC       - global covariate centering option
% xGX.sGC       - string describing global covariate centering option
% xGX.gc        - center for global covariate
% xGX.iGloNorm  - Global normalisation option
% xGX.sGloNorm  - string describing global normalisation option
%
% xM            - structure describing masking options
% xM.T          - Threshold masking value (-Inf=>None,
%                 real=>absolute, complex=>proportional (i.e. times global) )
% xM.TH         - nScan x 1 vector of analysis thresholds, one per image
% xM.I          - Implicit masking (0=>none, 1=>implicit zero/NaN mask)
% xM.VM         - struct array of explicit mask images
%                 (empty if no explicit masks)
% xM.xs         - structure describing masking options
%                 (format is same as for xsDes described below)
%
% xsDes         - structure of strings describing the design:
%                 Fieldnames are essentially topic strings (use "_"'s for
%                 spaces), and the field values should be strings or cellstr's
%                 of information regarding that topic. spm_DesRep.m
%                 uses this structure to produce a printed description
%                 of the design, displaying the fieldnames (with "_"'s
%                 converted to spaces) in bold as topics, with
%                 the corresponding text to the right
%
% SPMid         - String identifying SPM and program versions
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Thu, Sep 13, 2012 at 10:57 AM, Mariela Hidalgo
<[log in to unmask]> wrote:
> Dear SPMers:
>
> I have a question about the variables that the SPM. mat file has integrate
> (e.g. xY, xGx, SPMid, VBeta, etc.).
> Do you have any information about each variable and what mean each one of
> them?
>
> I hope any answer from you.
> Regards,
>
> --
> Mariela Hidalgo
> Biomedical Engineering student
> Universidad de Valparaíso,
> Chile