This is a standalone post about real life neuroscientific intricacies that may play a part in how information is processed in the brain, mostly not respected by current models of neural networks. The list is totally speculative and not exhaustive nor accurately relevant, but it’s fun to think about them 🙂
Don’t click in, this post is a placeholder, update pending.
status: being updated.
The original title is: ‘Neuronal Dynamics, the Basics’ but now that I think of it’s too big a topic to be covered in one article, so I should probably start a series, on neuronal dynamical issues pertaining to SNNs.
This series will only cover relevant issues(that I deem them to be) about SNNs so it’s by no mean comprehensive(something you really shouldn’t expect from a amateur blogger) nor even correct/applicable.
The main ideas are extracted from a great textbook on neuronal dynamics, with some supplement information from several papers. Personal hunches and wild guesses will be marked out.
1 What’s it all about
TL;DR: A more neuroscientifically realistic model of artificial neural networks.