ANN Variable Correlation
Generically speaking a neural network can automatically learn the needed feature transformation for a model to perform well.  What tends to matter more is how the features relate to your output.

If you're ever bored, you can run your original matrix, a transformed matrix that has been de-correlated via a principle axis transformation, and the original matrix combined with correlation information.  I suspect performance using the same architecture will be relatively similar.