Topic: data domains

Biological visual systems have evolved around the efficient coding of natural image statistics in order to support recognition of complex visual patterns. Recent work has shown that deep neural networks are able to learn similar representations to those measured in visual areas in animals, suggesting they may serve as models for the brain. Varying network architectures and loss functions has been shown to modulate the biological similarity learned representations, however the extent to which this results from exposure to natural image statistics during training has not been fully characterized