[deet]

Somewhat off topic... but do you happen to know if the dendritic tree and its functional subunits in multi-compartment models can be treated mathematically as a multilayer network of simpler neurons?

I've been wondering if dendritic arborization means that current deep learning ANNs are hopelessly far away from biological reality, or if perhaps with deep networks simple ANNs could indeed learn to compute in a similar way to complex biological neurons, just over many layers of artificial neurons.

[buboard]

Absolutely, dendritic trees are generally considered active and can elicit dendritic spikes. This 2-layer model is well studied in hippocampal CA1 neurons for example[1]. ANNs are far from reality but they do validate connectionism as probably the correct abstract model of learning. The thing that's harder to crack is plasticity i.e. the learning rules. Plasticity in real neurons is a very complex process and there is no indication that anything like backpropagation takes place.

1 https://www.sciencedirect.com/science/article/pii/S089662730...

2 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4279447/

3 https://www.ncbi.nlm.nih.gov/pubmed/18270515