Are convolutional neural networks inspired by the human brain? The Deep Learning book by Goodfellow et al. states

Convolutional networks stand out as an example of neuroscientiﬁc principles inﬂuencing deep learning.

Are convolutional neural networks (CNNs) really inspired by the human brain?
If so, how? In particular, what structures within the brain do CNN-like neuron groupings occur?
In the eye, the retinal ganglion cells have a receptive field that is equivalent to some types of convolution filters, most of them edge detectors.
The brain is a big unknown, nobody knows how it does to organize, memorize, create concepts, learns the language, ... . Thus, it is not possible to establish a parallelism.
In particular, brain has a capacity of handle independence in scale and rotation that CNN's are not able to reproduce.
As general remark about NN and brain: even when it is always said that &quot;neural network cells&quot; are &quot;inspired&quot; in biological neurons, there are critical differences that made this similitude only a &quot;inspiration&quot;. Thus, comparison of a CNN or any other kind of NN with brain is always a fuzzy comparison. The biggest difference is probably the learning capacity: the human brain learns by itself, while the neural network needs an external system (the back-propagation algorithm) that feeds the NN with the learned parameters.