It was never an accurate model (in the sense that it never modelled, eg., plasticity and many more things). It was however an attempt to actually model activati

It was never an accurate model (in the sense that it never modelled, eg., plasticity and many more things). It was however an attempt to actually model activation patterns as boolean circuits. However as soon as you make it a supervised optimisation alg it fails even to be a model. (The NN algorithm is just k-nearest-neighbours + recursive PCA.) Activation patterns in the brain aren't "trained" by backprop, and they dont form a piece-wise linear (ie., ReLU) regression function. It's better to say that the optimisation algorithm called "Neural Networks" was inspired by the "Neural Network" model of the brain which was a partially highly simplified model of one aspect of neurone behaviour. The algorithm used today has nothing homologous with anything in the brain -- and its somewhat incoherent to suppose it does. A piece-wise linear regression model of the boston house price dataset is a meaningless stand-in for anything neurological. Its aburdist marketing to say otherwise.