I would use the word 'reflect' rather than 'represent' throughout, but this article nonetheless paints a fascinating picture of how a neural network organizes itself into concepts. "Asking the GAN to paint what it thought, the researchers found distinct neuron clusters that had learned to (paint) a tree, for example... In other words, it had managed to group tree pixels with tree pixels and door pixels with door pixels regardless of how these objects changed color from photo to photo in the training set." This is important because conceptualization is the basis for abstraction, which is the doorway to higher-level cognitive capacity.
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