DemoStat4Ci.m

% DEMOSTAT4CI illustrates the usage of the Stat2Ci toolbox on two classification images from:
%		Gosselin, F. & Schyns, P. G. (2001).  Bubbles: A technique to reveal the use of information 
% 		in recognition. Vision Research, 41, 2261-2271.
% 	The Stat4Ci toolbox allows to perform the Pixel and the Cluster tests, both based on Random Field 
% 	Theory. These tests are easy to apply, requiring a mere four pieces of information; and they 
% 	typically produce statistical thresholds (or p-values) lower than the standard Bonferroni correction.
% 
%	An excellent non-technical reference is:
% 		K. J. Worsley (1996) the geometry of random image. Chance, 9, 27-40.
% 
%	We borrowed from several sources: the STAT_THRESHOLD function was written by Keith Worsley for the fmristat toolbox
% 	(http://www.math.mcgill.ca/~keith/fmristat); and our DISPLAYCI function calls many functions from the 
%	Image Processing toolbox.
% 
% The Stat4Ci toolbox is free (http://mapageweb.umontreal.ca/gosselif/stat4ci.html); if you use 
% it in your research, please, cite us:
%	Chauvin, A., Worsley, K. J., Schyns, P. G., Arguin, M. & Gosselin, F. (2004).  A sensitive 
%	statistical test for smooth classification images.
% 
% Alan Chauvin & FrŽdŽric Gosselin (frederic.gosselin@umontreal.ca), 20/08/2004

% % Loads a classification image
SCi = double(imread('GenderFG.tiff')); % from Gosselin & Schyns, 2001, Experiment 1, GENDER, subject FG 
SCi = double(imread('exnexFG.tiff')); % from Gosselin & Schyns, 2001, Experiment 1, GENDER, subject FG 
SCi = cIm2hrCi(SCi);

sigma_b = 20;	%std of smoothing filter

% % Specifies a search space; here: the face area
S_r = double(imread('faceMask.tiff'));
S_r = (S_r - min(S_r(:))) / (max(S_r(:))-min(S_r(:)));

% % Extracts the area outside the mask; used for the estimation of expected mean and variance of the Ci
vecSCi = SCi(eq(S_r,0));

% % Z-transforms the SCi
Res = ZTransSCi(SCi,mean(vecSCi(:)),std(vecSCi(:)));
Res.ZSCi = Res.ZSCi.*S_r;

% % Performs the Pixel or Cluster test
p = .05;	%p-value
tC = 2.7; 	%threshold (for Cluster test)
Res = StatThresh(Res,p,sigma_b,tC,S_r);

% % Displays the results
background = double(imread('w1H.JPG'));  % a face used by Gosselin & Schyns, 2001, Experiment 1
tCi = DiplayRes(Res,background); 		% the results of one of the tests with a background