This video involves precisely simulating the neurons in a worm:
https://www.youtube.com/watch?v=eYS7UIUM_SQ
Artificial neural networks (ANNs) are based on what we know about biological neural networks. Why is it that a ANN can allow a robot to learn how to catch a ball in a cup or read hand-writing or do speech recognition?
https://medium.com/@ageitgey/machin...h-recognition-with-deep-learning-28293c162f7a
Is it just a coincidence that ANNs are a very efficient way to replicate human-type skills? ANNs can explain "hunches" or "intuition". You can get an ANN to predict something based on an untrained input. When I studied ANNs in university I made a very simple ANN which learnt a form of grammar - you'd train it for some examples and it could guess unseen examples and it would initally over-apply the rule (despite exceptions in the grammar) like how kids might say "runned".
The weights that a ANN tweaks as it learns are a form of memory. Humans can also have memories linked to language. BTW in the case of ANN the memory of what catness or dogness is in a picture is smeared across many neuron weights. So memories in a ANN are similarly mysterious.
That's a huge part of the puzzle missing. It's way too early to hitch your wagons to any cart. When it comes to neurology we're where cartographers were in the 14-hundreds. There's a lot of white on the map.
You seem to think ANNs have next to nothing to do with biological brains. I think it is good to try and understand as much as we can rather than learning nothing about this.
Also.... why do you feel the need to do it? You seem to think it very important to belong to a certain camp. Why? Why not just accept when you don't know something?
ANNs have a huge number of applications including describing images, speech recognition, natural language processing, etc. This means better and better AI including better AI in games - which would approach levels that appear to be self-conscious. I'm not saying we know everything but it is interesting to see that we do know a lot.