Interpreting a large number of neurons in deep learning is difficult. Our proposed ‘CLAssi- fier-DECoder’ architecture (ClaDec) facilitates the understanding of the output of an arbi- trary layer of neurons or subsets thereof. It uses a decoder that transforms the incompre- hensible representation of the given neurons to a representation that is more similar to the domain a human is familiar with.