The convolutional kernels in the first levels do converge to Gabors like the ones in V1 (and there were math works in the 90-ies, in neuro research, about optimality of such kernels) so it wouldn't be surprising if higher levels would converge to something that is similar to the higher levels of visual cortex (like hierarchical feature aggregation that is nicely illustrated by deep dreaming and also feels like it can be optimal under reasonable conditions and thus would be expected to emerge).