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Slepi/Code/Utilities/spm12/spm_design_contrasts.m
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spm_design_contrasts.m
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function con = spm_design_contrasts(SPM)
% Make contrasts for one, two or three-way ANOVAs
% FORMAT con = spm_design_contrasts(SPM)
% SPM - SPM structure
%
% con - structure array of contrasts with fields
% con(i).c - Contrast matrix
% con(i).name - Name
%__________________________________________________________________________
%
% This function generates contrasts on the basis of the current SPM
% design. This is specified in SPM.factor (how the factors relate to the
% conditions) and SPM.xBF.order (how many basis functions per condition).
%
% This function generates (transposed) contrast matrices to test
% for the average effect of condition, main effects of factors and
% interactions.
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Will Penny
% $Id: spm_design_contrasts.m 3528 2009-11-03 16:33:00Z guillaume $
% Only relevant if factorial design has been specified
%--------------------------------------------------------------------------
if isempty(SPM.factor), con = []; return; end
% Compute contrasts for a generic k(1)-by-k(2)-by-k(3) design
%--------------------------------------------------------------------------
nf = length(SPM.factor);
kf = [SPM.factor.levels];
icon = spm_make_contrasts(kf);
ncon = length(icon);
if ~ncon, con = []; return; end
% Get number of basis functions per condition and 'expand' contrasts
%--------------------------------------------------------------------------
try
nbases = SPM.xBF.order;
catch
nbases = 1; % for 2nd level designs
end
for c=1:ncon
con(c).c = kron(icon(c).c,eye(nbases));
end
% Handle parametric modulations/multi-sessions for 1st level designs
%--------------------------------------------------------------------------
if isfield(SPM,'Sess')
nsess = length(SPM.Sess);
conds = length(SPM.Sess(1).U);
% Pad out parametric modulation columns with zeros
%----------------------------------------------------------------------
for c=1:ncon
nr = size(con(c).c,1);
col = 1;
block = [];
for cc=1:conds
block = [block,con(c).c(:,col:col+nbases-1)];
block = [block,zeros(nr,SPM.Sess(1).U(cc).P.h)];
col = col + nbases;
end
con(c).c = block;
end
% If there are multiple sessions, replicate each contrast matrix over
% sessions - this assumes the conditions are identical in each session
%----------------------------------------------------------------------
if nsess > 1
covs = zeros(1,nsess);
for s=1:nsess
nconds = length(SPM.Sess(s).U);
if nconds ~= conds
error('Number of conditions must be same in all sessions');
end
covs(s) = size(SPM.Sess(s).C.C,2);
end
for c=1:ncon
nr = size(con(c).c,1);
c1 = [con(c).c zeros(nr,covs(1))];
for s=2:nsess
c1 = [c1 con(c).c zeros(nr,covs(s))];
end
con(c).c = c1;
end
end
% Pad contrasts out - add columns for session effects
%----------------------------------------------------------------------
k = size(SPM.xX.X,2);
for c=1:ncon
con(c).c(:,end+1:k) = 0;
end
end
% Rename contrasts (see spm_make_contrasts)
%--------------------------------------------------------------------------
con(1).name = 'Average effect of condition';
con(2).name = ['Main effect of ',SPM.factor(1).name];
if nf>1
con(3).name = ['Main effect of ',SPM.factor(2).name];
con(4).name = ['Interaction: ',SPM.factor(1).name,' x ',SPM.factor(2).name];
end
if nf>2
con(5).name = ['Main effect of ',SPM.factor(3).name];
con(6).name = ['Interaction: ',SPM.factor(1).name,' x ',SPM.factor(3).name];
con(7).name = ['Interaction: ',SPM.factor(2).name,' x ',SPM.factor(3).name];
con(8).name = ['Interaction: ',SPM.factor(1).name,' x ',SPM.factor(2).name,' x ',SPM.factor(3).name];
end
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