How to compute `AUC` for NN (`patternnet`)?

According to the following code of Matlab, I'm trying to get the AUC of a neural network (patternnet), so I have used the perfcurve function (see the related outputs):

(There are two different classes - labeled 0, 1).

[net, tr] = train(net, xtrain', ytrain');   % xtrain = 64x4; xtest = 7x4;
y_pred = net(xtest'); 
[~,indicesPredicted] = max(y_pred,[],1);

%  output of y_pred (2x7): 
%  [0.557, 0.557, 0.557, 0.557, 0.788,  0.574,  0.557;
%   0.442, 0.442, 0.442, 0.442, 0.212, 0.425, 0.442] 
%
% and so the output of
% indicesPredicted is [1, 1, 1, 1, 1, 1, 1];

score = y_pred'; 
[~,~,~,AUC] = perfcurve(indicesReal', score(:,2), 1);   % indicesReal = [0, 1, 1, 1, 0, 0, 0];

%  The output of AUC is 1.

While the result of AUC isn't correct because:

predicted                        Real

ans =                             ans =

    1  (class 2)                      0  (class 1)  
    1  (class 2)                      1  (class 2)  
    1  (class 2)                      1  (class 2)  
    1  (class 2)                      1  (class 2)  
    1  (class 2)                      0  (class 1)  
    1  (class 2)                      0  (class 1)  
    1  (class 2)                      0  (class 1)  

How to compute the posterior probabilities (scores) for NN (patternnet) to get AUC?

Also, I have tested the [y_pred, score] = predict(net, xtest); and an error has occurred about predict:

"Error using predict 
No valid system or dataset was specified."

I have also seen the related links such as: Link1, Link2, Link3.