function conn_batch(batch)
% CONN_BATCH batch functionality for connectivity toolbox
% 
% CONN_BATCH(BATCH);
% where BATCH is a structure with fields (optional) New, Setup, Preprocessing,
% Analysis, and Results, will perform the specified steps.
% 
% BATCH structure fields:
%
% filename          : conn_*.mat project file
%
% New                 PERFORMS SPATIAL PREPROCESSING (realignment/coregistration/segmentation/normalization/smoothing) AND INITIALIZES conn_* PROJECT
%   steps           : Cell array of preprocessing steps [{'Segmentation','Realignment','Coregistration','Normalization','Smoothing','Initialization'}];
%   functionals     : functionals{nsub}{nses} char array of functional volume files 
%   structurals     : structurals{nsub} char array of anatomical volume files 
%   FWHM            : Smoothing factor (mm) [8]
%   VOX             : target voxel size (mm) [2]
%   template_structural : anatomical template file for approximate coregistration [spm/template/T1.nii]
%   template_functional : functional template file for normalization [spm/template/EPI.nii]
%
% Setup               DEFINES EXPERIMENT SETUP AND PERFORMS INITIAL DATA EXTRACTION STEPS
%   isnew           : 1/0 is this a new conn project [0]
%   done            : 1/0: 0 defines fields only; 1 performs processing steps [0]
%   overwrite       : 'Yes'/'No' overwrites target files if they exist ['Yes']
%   spmfiles        : Optionally, spmfiles{nsub} is a char array pointing to the 'SPM.mat' source file to extract Setup information from for each subject
%   nsubjects       : Number of subjects
%   RT              : Repetition time (seconds) [2]
%   acquisitiontype : 1/0: Continuous acquisition of functional volumes [1] 
%   analyses        : Vector of index to analysis types (1: ROI-to-ROI; 2: Seed-to-voxel; 3: Voxel-to-voxel) [1,2] 
%   voxelmask       : Analysis mask type (voxel-level analyses): 1: Template mask (brainmask.nii); 2: Implicit mask (subject-specific) [1] 
%   voxelresolution : Voxel resolution (voxel-level analyses): 1: Same as template (2mm isotropic); 2: Same as structurals; 3: Same as functionals [1] 
%   outputfiles     : Optional output files (outputfiles(1): 1/0 creates confound beta-maps; outputfiles(2): 1/0 creates confound-corrected timeseries; outputfiles(3): 1/0 creates seed-to-voxel r-maps) [0,0,0] 
%   functionals     : functionals{nsub}{nses} char array of functional volume files 
%   structurals     : structurals{nsub} char array of structural volume files 
%   masks
%     Grey          : masks.Grey{nsub} char array of grey matter mask volume file [defaults to Grey mask extracted from structural volume] 
%     White         : masks.White{nsub} char array of white matter mask volume file [defaults to White mask extracted from structural volume] 
%     CSF           : masks.CSF{nsub} char array of CSF mask volume file [defaults to CSF mask extracted from structural volume] 
%                   : each of these fields can also be defined as a structure with fields 'files' (defined as above) and 'dimensions' (specifying the number of dimensions to extract from each mask area).
%   rois
%     names         : rois.names{nroi} char array of ROI name [defaults to ROI filename]
%     files         : rois.files{nroi}{nsub} char array of roi file (or rois.files{nroi} char array of roi file, to use the same roi for all subjects)
%     dimensions    : rois.dimensions{nroi} number of ROI dimensions - # temporal components to extract from ROI [1]
%   conditions
%     names         : conditions.names{ncondition} char array of condition name
%     onsets        : conditions.onsets{ncondition}{nsub}{nses} vector of condition onsets (in seconds)
%     durations     : conditions.durations{ncondition}{nsub}{nses} vector of condition durations (in seconds)
%   covariates
%     names         : covariates.names{ncovariate} char array of covariate name
%     files         : covariates.files{ncovariate}{nsub}{nses} char array of covariate file 
%   subjects
%     effect_names  : subjects.effect_names{neffect} char array of second-level effect name
%     effects       : subjects.effects{neffect} vector of size [nsubjects,1] defining second-level effects
%   subjects
%     group_names  : subjects.group_names{ngroup} char array of second-level group name
%     groups       : subjects.group vector of size [nsubjects,1] (with values from 1 to ngroup) defining second-level groups
%
% Preprocessing       PERFORMS PREPROCESSING STEPS (confound removal & filtering)
%   done            : 1/0: 0 defines fields only; 1 performs processing steps [0]
%   overwrite       : 'Yes'/'No' overwrites target files if they exist ['Yes']
%   filter          : vector with two elements specifying band pass filter: low-frequency & high-frequency cutoffs (Hz)
%   confounds       : Cell array of confound names (see 'confounds.names' below)
%   confounds       : alternatively confounds can be a structure with fields
%     names         : confounds.names{nconfound} char array of confound name (confound names can be: 'Grey Matter','White Matter','CSF',any ROI name, any covariate name, or 'Effect of *' where * represents any condition name])
%     dimensions    : confounds.dimensions{nconfound} number of confound dimensions [defaults to using all dimensions available for each confound variable]
%     deriv         : confounds.deriv{nconfound} numnber of derivatives for each dimension [0]
%
% Analysis            PERFORMS FIRST-LEVEL ANALYSES (ROI-to-ROI and seed-to-voxel) 
%   done            : 1/0: 0 defines fields only; 1 performs processing steps [0]
%   overwrite       : 'Yes'/'No' overwrites target files if they exist ['Yes']
%   analysis_number : sequential indexes identifying each set of independent analyses [1] 
%   measure         : connectivity measure used, 1 = 'correlation (bivariate)', 2 = 'correlation (semipartial)', 3 = 'regression (bivariate)', 4 = 'regression (multivariate)'; [1] 
%   weight          : within-condition weight, 1 = 'none', 2 = 'hrf', 3 = 'hanning'; [2] 
%   type            : analysis type, 1 = 'ROI-to-ROI', 2 = 'Seed-to-Voxel', 3 = 'all'; [3] 
%   sources         : Cell array of sources names (seeds) (source names can be: any ROI name) (if this variable does not exist the toolbox will perform the analyses for all of the existing ROIs which are not defined as confounds in the Preprocessing step) 
%   sources         : alternatively sources can be a structure with fields
%     names         : sources.names{nsource} char array of source names (seeds)
%     dimensions    : sources.dimensions{nsource} number of source dimensions [1]
%     deriv         : sources.deriv{nsource} number of derivatives for each dimension [0]
%
% Analysis            PERFORMS FIRST-LEVEL ANALYSES (voxel-to-voxel) 
%   done            : 1/0: 0 defines fields only; 1 performs processing steps [0]
%   overwrite       : 'Yes'/'No' overwrites target files if they exist ['Yes']
%   analysis_number : 0 (set this variable to 0 to identify voxel-to-voxel analyses) [0] 
%   measures        : Cell array of voxel-to-voxel measure names (type 'conn_v2v measures' for a list of default measures) (if this variable does not exist the toolbox will perform the analyses for all of the default voxel-to-voxel measures) 
%   measures        : alternatively voxel-to-voxel measures can be a structure with fields
%     names         : measures.names{nmeasure} char array of measure names 
%     type          : measures.type{nmeasure} measure type (0:local measures; 1: global measures) [1]
%     kernelsupport : measures.kernelsupport{nmeasure} local support (FWHM) of smoothing kernel [12]
%     kernelshape   : measures.kernelshape{nmeasure} kernel type (0: gaussian; 1: gradient; 2: laplacian) [1]
%     dimensions    : measures.dimensions{nmeasure} number of SVD dimensions to retain (dimensionality reduction) [16]
%
% Results             PERFORMS SECOND-LEVEL ANALYSES (ROI-to-ROI and Seed-to-Voxel analyses) 
%   done            : 1/0: 0 defines fields only; 1 performs processing steps [0]
%   overwrite       : 'Yes'/'No' overwrites target files if they exist ['Yes']
%   analysis_number : sequential indexes identifying each set of independent analysis [1]
%   foldername      : folder to store the results
%   between_subjects
%     effect_names  : cell array of second-level effect names
%     contrast      : contrast vector (same size as effect_names)
%   between_conditions [defaults to multiple analyses, one per condition]
%     effect_names  : cell array of condition names (as in Setup.conditions.names)
%     contrast      : contrast vector (same size as effect_names)
%   between_sources    [defaults to multiple analyses, one per source]
%     effect_names  : cell array of source names (as in Analysis.regressors, typically appended with _1_1; generally they are appended with _N_M -where N is an index ranging from 1 to 1+derivative order, and M is an index ranging from 1 to the number of dimensions specified for each ROI; for example ROINAME_2_3 corresponds to the first derivative of the third PCA component extracted from the roi ROINAME) 
%     contrast      : contrast vector (same size as effect_names)
%
% Results             PERFORMS SECOND-LEVEL ANALYSES (Voxel-to-Voxel analyses) 
%   done            : 1/0: 0 defines fields only; 1 performs processing steps [0]
%   overwrite       : 'Yes'/'No' overwrites target files if they exist ['Yes']
%   analysis_number : 0 (set this variable to 0 to identify voxel-to-voxel analyses) [0]
%   foldername      : folder to store the results
%   between_subjects
%     effect_names  : cell array of second-level effect names
%     contrast      : contrast vector (same size as effect_names)
%   between_conditions [defaults to multiple analyses, one per condition]
%     effect_names  : cell array of condition names (as in Setup.conditions.names)
%     contrast      : contrast vector (same size as effect_names)
%   between_measures [defaults to multiple analyses, one per measure]
%     effect_names  : cell array of measure names (as in Analysis.measures) 
%     contrast      : contrast vector (same size as effect_names)
%
% See conn_batchexample*.m files for additional information and examples of use.
%

global CONN_x;

if iscell(batch),
    for nbatch=1:numel(batch),conn_batch(batch{nbatch});end
    return;
elseif numel(batch)>1,
    for nbatch=1:numel(batch),conn_batch(batch(nbatch));end
    return;
end
%% NEW step
if isfield(batch,'New'),
    OPTIONS=struct('RT',2,'FWHM',8,'VOX',2,'CONN_DISPLAY',0,'STRUCTURAL_TEMPLATE',fullfile(fileparts(which('spm')),'templates','T1.nii'),'FUNCTIONAL_TEMPLATE',fullfile(fileparts(which('spm')),'templates','EPI.nii'),'SO',[]);
    if isfield(batch,'filename')&&~isempty(batch.filename),OPTIONS.CONN_NAME=batch.filename; end
    if isfield(batch.New,'center')&&~isempty(batch.New.cennter),OPTIONS.CENTER=batch.New.center;end
    if isfield(batch.New,'reorient')&&~isempty(batch.New.reorient),OPTIONS.REORIENT=batch.New.reorient;end
    if isfield(batch.New,'RT')&&~isempty(batch.New.RT),OPTIONS.RT=batch.New.RT;end; %obsolete
    if isfield(batch.New,'FWHM')&&~isempty(batch.New.FWHM),OPTIONS.FWHM=batch.New.FWHM;end
    if isfield(batch.New,'VOX')&&~isempty(batch.New.VOX),OPTIONS.VOX=batch.New.VOX;end
    if isfield(batch.New,'sliceorder')&&~isempty(batch.New.sliceorder),OPTIONS.SO=batch.New.sliceorder;end
    if isfield(batch.New,'steps')&&~isempty(batch.New.steps),OPTIONS.STEPS=batch.New.steps;end
    if isfield(batch.New,'template_structural')&&~isempty(batch.New.template_structural),OPTIONS.STRUCTURAL_TEMPLATE=batch.New.template_structural;end
    if isfield(batch.New,'template_functional')&&~isempty(batch.New.template_functional),OPTIONS.FUNCTIONAL_TEMPLATE=batch.New.template_functional;end
    if isfield(batch.New,'functionals')&&~isempty(batch.New.functionals),
        OPTIONS.FUNCTIONAL_FILES=batch.New.functionals;
    end
    if isfield(batch.New,'structurals')&&~isempty(batch.New.structurals),
        OPTIONS.STRUCTURAL_FILES=batch.New.structurals;
    end
    conn_setup_wizard(OPTIONS);
end

%% SETUP step
if isfield(batch,'Setup'),
    if isfield(batch,'filename'),
        if (isfield(batch.Setup,'isnew')&&batch.Setup.isnew)||isempty(dir(batch.filename)),
            conn('init');                   % initializes CONN_x structure
            CONN_x.filename=batch.filename;
        else,
            CONN_x.filename=batch.filename;
            conn load;                      % loads existing conn_* project
        end
    end
    
    if ~isfield(batch.Setup,'overwrite'),batch.Setup.overwrite='Yes';end
    if isfield(batch.Setup,'spmfiles')&&~isempty(batch.Setup.spmfiles),
        CONN_x.gui=struct('overwrite',batch.Setup.overwrite);
        conn_importspm(batch.Setup.spmfiles);
        CONN_x.gui=1;
    end
    if isfield(batch.Setup,'RT')&&~isempty(batch.Setup.RT),CONN_x.Setup.RT=batch.Setup.RT;end
    if isfield(batch.Setup,'nsubjects')&&~isempty(batch.Setup.nsubjects),
        if batch.Setup.nsubjects~=CONN_x.Setup.nsubjects, CONN_x.Setup.nsubjects=conn_merge(CONN_x.Setup.nsubjects,batch.Setup.nsubjects); end
%         CONN_x.Setup.nsubjects=batch.Setup.nsubjects;     % number of subjects
    end
    if isfield(batch.Setup,'acquisitiontype')&&~isempty(batch.Setup.acquisitiontype),
        CONN_x.Setup.acquisitiontype=batch.Setup.acquisitiontype;
    end
    if isfield(batch.Setup,'analyses'),
        CONN_x.Setup.steps=accumarray(batch.Setup.analyses(:),1,[3,1]);
    end
    if isfield(batch.Setup,'voxelmask')&&~isempty(batch.Setup.voxelmask),
        CONN_x.Setup.analysismask=batch.Setup.voxelmask;
    end
    if isfield(batch.Setup,'voxelresolution')&&~isempty(batch.Setup.voxelresolution),
        CONN_x.Setup.spatialresolution=batch.Setup.voxelresolution;
    end
    if isfield(batch.Setup,'outputfiles'),
        CONN_x.Setup.outputfiles=batch.Setup.outputfiles;
    end
    if isfield(batch.Setup,'functionals')&&~isempty(batch.Setup.functionals),
        for nsub=1:CONN_x.Setup.nsubjects,
            CONN_x.Setup.nsessions(nsub)=length(batch.Setup.functionals{nsub});
            for nses=1:CONN_x.Setup.nsessions(nsub),
                [CONN_x.Setup.functional{nsub}{nses},V]=conn_file(batch.Setup.functionals{nsub}{nses});
                CONN_x.Setup.nscans{nsub}{nses}=prod(size(V));
            end
        end
    end
    if isfield(batch.Setup,'structurals')&&~isempty(batch.Setup.structurals),
        for nsub=1:CONN_x.Setup.nsubjects,
            CONN_x.Setup.structural{nsub}=conn_file(batch.Setup.structurals{nsub});
        end
    end
    if isfield(batch.Setup,'masks'),
        masks={'Grey','White','CSF'};
        for nmask=1:length(masks),
            if isfield(batch.Setup.masks,masks{nmask})&&~isempty(batch.Setup.masks.(masks{nmask})),
                if ~isstruct(batch.Setup.masks.(masks{nmask})),
                    for nsub=1:CONN_x.Setup.nsubjects,
                        CONN_x.Setup.rois.files{nsub}{nmask}=conn_file(batch.Setup.masks.(masks{nmask}){nsub});
                    end
                else,
                    for nsub=1:CONN_x.Setup.nsubjects,
                        CONN_x.Setup.rois.files{nsub}{nmask}=conn_file(batch.Setup.masks.(masks{nmask}).files{nsub});
                    end
                    if isfield(batch.Setup.masks.(masks{nmask}),'dimensions'), CONN_x.Setup.rois.dimensions{nmask}=batch.Setup.masks.(masks{nmask}).dimensions; end
                end;
            end
        end
    end
%     if isfield(batch.Setup,'masks')&&isfield(batch.Setup.masks,'Grey')&&~isempty(batch.Setup.masks.Grey),for nsub=1:CONN_x.Setup.nsubjects,CONN_x.Setup.rois.files{nsub}{1}=conn_file(batch.Setup.masks.Grey{nsub});end; end
%     if isfield(batch.Setup,'masks')&&isfield(batch.Setup.masks,'White')&&~isempty(batch.Setup.masks.White),for nsub=1:CONN_x.Setup.nsubjects,CONN_x.Setup.rois.files{nsub}{2}=conn_file(batch.Setup.masks.White{nsub});end; end
%     if isfield(batch.Setup,'masks')&&isfield(batch.Setup.masks,'CSF')&&~isempty(batch.Setup.masks.CSF),for nsub=1:CONN_x.Setup.nsubjects,CONN_x.Setup.rois.files{nsub}{3}=conn_file(batch.Setup.masks.CSF{nsub});end; end
    if isfield(batch.Setup,'rois')&&~isempty(batch.Setup.rois),
        if ~isstruct(batch.Setup.rois), temp=batch.Setup.rois;batch.Setup.rois=struct;batch.Setup.rois.files=temp;for n1=1:length(temp),[nill,name,nameext]=fileparts(temp{n1}); batch.Setup.rois.names{n1}=name;end; end
        n0=3;%length(CONN_x.Setup.rois.names)-1; % disregards existing rois
        for n1=1:length(batch.Setup.rois.files),
            if ~iscell(batch.Setup.rois.files{n1}), batch.Setup.rois.files{n1}=repmat({batch.Setup.rois.files{n1}},[1,CONN_x.Setup.nsubjects]); end
            for nsub=1:CONN_x.Setup.nsubjects, 
                [nill,name,nameext]=fileparts(batch.Setup.rois.files{n1}{nsub});
                [V,str,icon]=conn_getinfo(batch.Setup.rois.files{n1}{nsub});
                CONN_x.Setup.rois.files{nsub}{n0+n1}={batch.Setup.rois.files{n1}{nsub},str,icon}; 
            end
            if ~isfield(batch.Setup.rois,'names')||length(batch.Setup.rois.names)<n1||isempty(batch.Setup.rois.names{n1}), batch.Setup.rois.names{n1}=name; end
            if ~isfield(batch.Setup.rois,'dimensions')||length(batch.Setup.rois.dimensions)<n1||isempty(batch.Setup.rois.dimensions{n1}), batch.Setup.rois.dimensions{n1}=1; end
            CONN_x.Setup.rois.names{n0+n1}=batch.Setup.rois.names{n1}; CONN_x.Setup.rois.names{n0+n1+1}=' ';
            CONN_x.Setup.rois.dimensions{n0+n1}=batch.Setup.rois.dimensions{n1};
            CONN_x.Setup.rois.mask(n0+n1)=0;
            CONN_x.Setup.rois.multiplelabels(n0+n1)=(strcmp(nameext,'.img')|strcmp(nameext,'.nii'))&(~isempty(dir(conn_prepend('',batch.Setup.rois.files{n1}{1},'.txt')))|~isempty(dir(conn_prepend('',batch.Setup.rois.files{n1}{1},'.csv')))|~isempty(dir(conn_prepend('',batch.Setup.rois.files{n1}{1},'.xls'))));
            CONN_x.Setup.rois.regresscovariates(n0+n1)=double(CONN_x.Setup.rois.dimensions{n0+n1}>1);
        end
        for nsub=1:CONN_x.Setup.nsubjects,% disregards existing rois
            CONN_x.Setup.rois.files{nsub}=CONN_x.Setup.rois.files{nsub}(1:n0+length(batch.Setup.rois.files)); 
        end
        CONN_x.Setup.rois.names=CONN_x.Setup.rois.names(1:n0+length(batch.Setup.rois.files)+1);
        CONN_x.Setup.rois.dimensions=CONN_x.Setup.rois.dimensions(1:n0+length(batch.Setup.rois.files));
        CONN_x.Setup.rois.mask=CONN_x.Setup.rois.mask(1:n0+length(batch.Setup.rois.files));
        CONN_x.Setup.rois.multiplelabels=CONN_x.Setup.rois.multiplelabels(1:n0+length(batch.Setup.rois.files));
        CONN_x.Setup.rois.regresscovariates=CONN_x.Setup.rois.regresscovariates(1:n0+length(batch.Setup.rois.files));
    elseif isfield(batch.Setup,'isnew')&&batch.Setup.isnew,
        conn importrois;
    end

    if isfield(batch.Setup,'conditions')&&~isempty(batch.Setup.conditions),
        CONN_x.Setup.conditions.names={batch.Setup.conditions.names{:},' '};
        for nsub=1:CONN_x.Setup.nsubjects,
            for nconditions=1:length(batch.Setup.conditions.onsets),
                for nses=1:CONN_x.Setup.nsessions(nsub),
                    CONN_x.Setup.conditions.values{nsub}{nconditions}{nses}={batch.Setup.conditions.onsets{nconditions}{nsub}{nses},batch.Setup.conditions.durations{nconditions}{nsub}{nses}};
                end
            end
        end
    end
    if isfield(batch.Setup,'covariates')&&~isempty(batch.Setup.covariates),
        CONN_x.Setup.l1covariates.names={batch.Setup.covariates.names{:},' '};
        for nsub=1:CONN_x.Setup.nsubjects,
            for nl1covariates=1:length(batch.Setup.covariates.files),
                for nses=1:CONN_x.Setup.nsessions(nsub),
                    CONN_x.Setup.l1covariates.files{nsub}{nl1covariates}{nses}=conn_file(batch.Setup.covariates.files{nl1covariates}{nsub}{nses});
                end
            end
        end
    end
    if isfield(batch.Setup,'subjects')&&~isempty(batch.Setup.subjects),
        CONN_x.Setup.l2covariates.names={' '};
        CONN_x.Setup.l2covariates.values=repmat({{}},[CONN_x.Setup.nsubjects,1]);
        if isfield(batch.Setup.subjects,'group_names')&&~isempty(batch.Setup.subjects.group_names),
            for ngroup=1:length(batch.Setup.subjects.group_names),
                idx=strmatch(batch.Setup.subjects.group_names{ngroup},CONN_x.Setup.l2covariates.names,'exact');
                if isempty(idx),
                    nl2covariates=length(CONN_x.Setup.l2covariates.names);
                    CONN_x.Setup.l2covariates.names{nl2covariates}=batch.Setup.subjects.group_names{ngroup};
                    CONN_x.Setup.l2covariates.names{nl2covariates+1}=' ';
                else, nl2covariates=idx;end
                for nsub=1:CONN_x.Setup.nsubjects,
                    CONN_x.Setup.l2covariates.values{nsub}{nl2covariates}=(batch.Setup.subjects.groups(nsub)==ngroup);
                end
            end
        end
        if isfield(batch.Setup.subjects,'effect_names')&&~isempty(batch.Setup.subjects.effect_names),
            for neffect=1:length(batch.Setup.subjects.effect_names),
                idx=strmatch(batch.Setup.subjects.effect_names{neffect},CONN_x.Setup.l2covariates.names,'exact');
                if isempty(idx),
                    nl2covariates=length(CONN_x.Setup.l2covariates.names);
                    CONN_x.Setup.l2covariates.names{nl2covariates}=batch.Setup.subjects.effect_names{neffect};
                    CONN_x.Setup.l2covariates.names{nl2covariates+1}=' ';
                else, nl2covariates=idx;end
                for nsub=1:CONN_x.Setup.nsubjects,
                    CONN_x.Setup.l2covariates.values{nsub}{nl2covariates}=batch.Setup.subjects.effects{neffect}(nsub);
                end
            end
        end
    end
    
    if isfield(batch.Setup,'done')&&batch.Setup.done,
        conn save;
        if ~isfield(batch.Setup,'overwrite'), batch.Setup.overwrite='Yes'; end
        CONN_x.gui=struct('overwrite',batch.Setup.overwrite);
        conn_process Setup;
        CONN_x.gui=1;
        conn save;
    else,
        if isfield(batch,'filename'),
            conn save;
        end
    end
end

%% PREPROCESSING step
if isfield(batch,'Preprocessing'),
    if isfield(batch,'filename'),
        CONN_x.filename=batch.filename;
        conn load;                      % loads existing conn_* project
    end
    if isfield(batch.Preprocessing,'filter')&&~isempty(batch.Preprocessing.filter),
        CONN_x.Preproc.filter=batch.Preprocessing.filter;          % frequency filter (band-pass values, in Hz)
    end
    if isfield(batch.Preprocessing,'confounds')&&~isempty(batch.Preprocessing.confounds),
        CONN_x.Preproc.confounds.names=batch.Preprocessing.confounds.names;
        if isfield(batch.Preprocessing.confounds,'dimensions')&&~isempty(batch.Preprocessing.confounds.dimensions), CONN_x.Preproc.confounds.dimensions=batch.Preprocessing.confounds.dimensions; else, CONN_x.Preproc.confounds.dimensions={}; end
        if isfield(batch.Preprocessing.confounds,'deriv')&&~isempty(batch.Preprocessing.confounds.deriv), CONN_x.Preproc.confounds.deriv=batch.Preprocessing.confounds.deriv; else, CONN_x.Preproc.confounds.deriv={}; end
    end
    
    if isfield(batch.Preprocessing,'done')&&batch.Preprocessing.done,
        conn save;
        if ~isfield(batch.Preprocessing,'overwrite'), batch.Preprocessing.overwrite='Yes'; end
        CONN_x.gui=struct('overwrite',batch.Preprocessing.overwrite);
        conn_process Preprocessing;
        CONN_x.gui=1;
        conn save;
    else,
        if isfield(batch,'filename'),
            conn save;
        end
    end
end

%% ANALYSIS step
if isfield(batch,'Analysis'),
    if isfield(batch,'filename'),
        CONN_x.filename=batch.filename;
        conn load;                      % loads existing conn_* project
    end
    if isfield(batch.Analysis,'sources'),
        if ~isfield(batch.Analysis,'analysis_number')||isempty(batch.Analysis.analysis_number),batch.Analysis.analysis_number=1; end
        if ~isfield(batch.Analysis,'measure')||isempty(batch.Analysis.measure),batch.Analysis.measure=1; end
        if ~isfield(batch.Analysis,'weight')||isempty(batch.Analysis.weight),batch.Analysis.weight=2; end
        if ~isfield(batch.Analysis,'type')||isempty(batch.Analysis.type),batch.Analysis.type=3; end
        CONN_x.Analysis=batch.Analysis.analysis_number;
        CONN_x.Analyses(CONN_x.Analysis).measure=batch.Analysis.measure;
        CONN_x.Analyses(CONN_x.Analysis).weight=batch.Analysis.weight;
        CONN_x.Analyses(CONN_x.Analysis).type=batch.Analysis.type;
        if isempty(batch.Analysis.sources),
            CONN_x.Analyses(CONN_x.Analysis).regressors.names={};
        elseif ~isstruct(batch.Analysis.sources),
            CONN_x.Analyses(CONN_x.Analysis).regressors.names=batch.Analysis.sources;
            CONN_x.Analyses(CONN_x.Analysis).regressors.dimensions=repmat({1},size(batch.Analysis.sources));
            CONN_x.Analyses(CONN_x.Analysis).regressors.deriv=repmat({0},size(batch.Analysis.sources));
        else
            CONN_x.Analyses(CONN_x.Analysis).regressors.names=batch.Analysis.sources.names;
            CONN_x.Analyses(CONN_x.Analysis).regressors.dimensions=batch.Analysis.sources.dimensions;
            CONN_x.Analyses(CONN_x.Analysis).regressors.deriv=batch.Analysis.sources.deriv;
        end
    end
    if isfield(batch.Analysis,'measures')
        batch.Analysis.analysis_number=0;
        if isempty(batch.Analysis.measures),
            CONN_x.vvAnalyses.regressors.names={};
        elseif ~isstruct(batch.Analysis.measures),
            CONN_x.vvAnalyses.regressors.names=batch.Analysis.measures;
            CONN_x.vvAnalyses.regressors.localsupport=repmat({[]},size(batch.Analysis.measures));
            CONN_x.vvAnalyses.regressors.deriv=repmat({[]},size(batch.Analysis.measures));
            CONN_x.vvAnalyses.regressors.global=repmat({[]},size(batch.Analysis.measures));
            CONN_x.vvAnalyses.regressors.dimensions=repmat({[]},size(batch.Analysis.measures));
        else
            if ~isfield(batch.Analysis.measures,'type'),batch.Analysis.measures.type=[]; end
            if ~isfield(batch.Analysis.measures,'kernelsupport'),batch.Analysis.measures.kernelsupport=[]; end
            if ~isfield(batch.Analysis.measures,'kernelshape'),batch.Analysis.measures.kernelshape=[]; end
            if ~isfield(batch.Analysis.measures,'dimensions'),batch.Analysis.measures.dimensions=[]; end
            CONN_x.vvAnalyses.regressors.names=batch.Analysis.measures.names;
            CONN_x.vvAnalyses.regressors.global=batch.Analysis.measures.type;
            CONN_x.vvAnalyses.regressors.localsupport=batch.Analysis.measures.kernelsupport;
            CONN_x.vvAnalyses.regressors.deriv=batch.Analysis.measures.kernelshape;
            CONN_x.vvAnalyses.regressors.dimensions=batch.Analysis.measures.dimensions;
        end
    end
    
    if isfield(batch.Analysis,'done')&&batch.Analysis.done,
        conn save;
        if ~isfield(batch.Analysis,'overwrite'), batch.Analysis.overwrite='Yes'; end
        CONN_x.gui=struct('overwrite',batch.Analysis.overwrite);
        if ~isfield(batch.Analysis,'analysis_number')
            conn_process('Analyses');
        else
            conn_process('Analyses',batch.Analysis.analysis_number);
        end
        CONN_x.gui=1;
        conn save;
    else
        if isfield(batch,'filename'),
            conn save;
        end
    end
end

%% RESULTS step
if isfield(batch,'Results'),
    if isfield(batch,'filename'),
        CONN_x.filename=batch.filename;
        conn load;                      % loads existing conn_* project
    end
    if ~isfield(batch.Results,'analysis_number')||isempty(batch.Results.analysis_number),
        if isfield(batch.Results,'between_measures'), batch.Results.analysis_number=0; 
        else batch.Results.analysis_number=1; 
        end
    end
    if batch.Results.analysis_number>0, CONN_x.Analysis=batch.Results.analysis_number; end
    if isfield(batch.Results,'foldername'),CONN_x.Results.foldername=batch.Results.foldername;else CONN_x.Results.foldername=''; end

    if isfield(batch.Results,'between_subjects')&&~isempty(batch.Results.between_subjects),
        for neffect=1:length(batch.Results.between_subjects.effect_names),
            idx=strmatch(batch.Results.between_subjects.effect_names{neffect},CONN_x.Setup.l2covariates.names,'exact');
            if isempty(idx),
                nl2covariates=length(CONN_x.Setup.l2covariates.names);
                CONN_x.Setup.l2covariates.names{nl2covariates}=batch.Results.between_subjects.effect_names{neffect};
                CONN_x.Setup.l2covariates.names{nl2covariates+1}=' ';
                for nsub=1:CONN_x.Setup.nsubjects,
                    CONN_x.Setup.l2covariates.values{nsub}{nl2covariates}=batch.Results.between_subjects.effects{neffect}(nsub);
                end
            end
        end
        CONN_x.Results.xX.nsubjecteffects=zeros(1,length(batch.Results.between_subjects.effect_names));
        for neffect=1:length(batch.Results.between_subjects.effect_names),
            idx=strmatch(batch.Results.between_subjects.effect_names{neffect},CONN_x.Setup.l2covariates.names,'exact');
            if isempty(idx), error(['unknown subject effect ',batch.Results.between_subjects.effect_names{neffect}]); return;
            else, CONN_x.Results.xX.nsubjecteffects(neffect)=idx(1); end
        end
        CONN_x.Results.xX.csubjecteffects=batch.Results.between_subjects.contrast;
        
        if ~isfield(batch.Results,'between_conditions')||isempty(batch.Results.between_conditions),
            clear batchtemp;
            if isfield(batch,'filename'), batchtemp.filename=batch.filename; else, batchtemp.filename=CONN_x.filename; end
            batchtemp.Results=batch.Results;
            for ncondition=1:length(CONN_x.Setup.conditions.names)-1,
                batchtemp.Results.between_conditions.effect_names={CONN_x.Setup.conditions.names{ncondition}};
                batchtemp.Results.between_conditions.contrast=[1];
                conn_batch(batchtemp);
            end
        else
            CONN_x.Results.xX.nconditions=zeros(1,length(batch.Results.between_conditions.effect_names));
            for neffect=1:length(batch.Results.between_conditions.effect_names),
                idx=strmatch(batch.Results.between_conditions.effect_names{neffect},CONN_x.Setup.conditions.names,'exact');
                if isempty(idx), error(['unknown condition ',batch.Results.between_conditions.effect_names{neffect}]); return;
                else, CONN_x.Results.xX.nconditions(neffect)=idx(1); end
            end
            CONN_x.Results.xX.cconditions=batch.Results.between_conditions.contrast;
            
            if isfield(batch.Results,'done')&&batch.Results.done&&batch.Results.analysis_number>0&&any(CONN_x.Analyses(CONN_x.Analysis).type==[1,3]),
                CONN_x.gui=struct('overwrite','Yes');
                conn_process('results_roi');
                CONN_x.gui=1;
                CONN_x.Results.foldername=[];
                conn save;
            end
            
            if batch.Results.analysis_number>0&&any(CONN_x.Analyses(CONN_x.Analysis).type==[2,3]) && (~isfield(batch.Results,'between_sources')||isempty(batch.Results.between_sources)),
                clear batchtemp;
                if isfield(batch,'filename'), batchtemp.filename=batch.filename; else, batchtemp.filename=CONN_x.filename; end
                batchtemp.Results=batch.Results;
                for nsource=1:length(CONN_x.Analyses(CONN_x.Analysis).sources),
                    batchtemp.Results.between_sources.effect_names={CONN_x.Analyses(CONN_x.Analysis).sources{nsource}};
                    batchtemp.Results.between_sources.contrast=[1];
                    conn_batch(batchtemp);
                end
            elseif batch.Results.analysis_number==0 && (~isfield(batch.Results,'between_measures')||isempty(batch.Results.between_measures)),
                clear batchtemp;
                if isfield(batch,'filename'), batchtemp.filename=batch.filename; else, batchtemp.filename=CONN_x.filename; end
                batchtemp.Results=batch.Results;
                for nmeasure=1:length(CONN_x.vvAnalyses.regressors.names),
                    batchtemp.Results.between_measures.effect_names={CONN_x.vvAnalyses.regressors.names{nmeasure}};
                    batchtemp.Results.between_measures.contrast=[1];
                    conn_batch(batchtemp);
                end
            elseif isfield(batch.Results,'between_sources')&&batch.Results.analysis_number>0&&any(CONN_x.Analyses(CONN_x.Analysis).type==[2,3]),
                CONN_x.Results.xX.nsources=zeros(1,length(batch.Results.between_sources.effect_names));
                for neffect=1:length(batch.Results.between_sources.effect_names),
                    idx=strmatch(batch.Results.between_sources.effect_names{neffect},CONN_x.Analyses(CONN_x.Analysis).sources,'exact');
                    if isempty(idx), error(['unknown source ',batch.Results.between_sources.effect_names{neffect}]); return;
                    else, CONN_x.Results.xX.nsources(neffect)=idx(1); end
                end
                CONN_x.Results.xX.csources=batch.Results.between_sources.contrast;
                conn save;
                
                if isfield(batch.Results,'done')&&batch.Results.done,
                    CONN_x.gui=struct('overwrite','Yes');
                    conn_process('results_voxel','dosingle','seed-to-voxel');
                    CONN_x.gui=1;
                    CONN_x.Results.foldername=[];
                    conn save;
                end
            elseif isfield(batch.Results,'between_measures')&&batch.Results.analysis_number==0
                CONN_x.Results.xX.nmeasures=zeros(1,length(batch.Results.between_measures.effect_names));
                for neffect=1:length(batch.Results.between_measures.effect_names),
                    idx=strmatch(batch.Results.between_measures.effect_names{neffect},CONN_x.Analyses(CONN_x.Analysis).regressors.names,'exact');
                    if isempty(idx), error(['unknown measure ',batch.Results.between_measures.effect_names{neffect}]); return;
                    else, CONN_x.Results.xX.nmeasures(neffect)=idx(1); end
                end
                CONN_x.Results.xX.cmeasures=batch.Results.between_measures.contrast;
                conn save;
                
                if isfield(batch.Results,'done')&&batch.Results.done,
                    CONN_x.gui=struct('overwrite','Yes');
                    conn_process('results_voxel','dosingle','voxel-to-voxel');
                    CONN_x.gui=1;
                    CONN_x.Results.foldername=[];
                    conn save;
                end
            end
        end
    end
end

end