Earlier quoted context omitted.
It's fascinating that none of the comments mention neural network applications. Seems like these people came a bit too early to the party.
We've left biomimicry in the dust a fair time ago - neurons do not work like relus after all (nor do they work like memristors), but relus are great at solving problems. None of our current NN applications would even want something that behaves like a neuron. You'd essentially have to start from scratch. It's not even clear if behaves-like-a-neuron is better or not to be worth the effort. (And that's disregarding the…
The ReLU was originally introduced by computational neuroscientists as a more biologically accurate approximation compared to the other activation functions. E.g. https://www.nature.com/articles/35016072
I would expect similar history behind convolutional neural networks, given how the early stages of the vision system have been understood to operate.