[subroutine]

Yeah, my bad. That said, I've read the article now. Indeed, the issues I've mentioned above are, more or less, echoed in the article.

Me: "these recurrent projections would need to (1) form a 3rd party connection at every synapse and (2) know which synapses were to blame for the error. "

Article: "Although the dendritic error network makes significant steps to increase the biological realism of predictive coding models, it also introduces extra one-to-one connections (dotted arrow in Box 4) that enforce the interneurons to take on similar values to the neurons in next layer and thus help them to predict the feedback from the next level."

The takeaway for me was that this article wasn't attempting to explain how biological NN actually function, but instead took the position of "for biological NN to implement a backprop-type algorithm, this is what it would entail..." and then went on to detail several models that demonstrate just how complex the bio NN architecture would have to be considering only just a few major constraints (there are still many constraining factors of ancillary importance that would have to be explained, should any of these model make it through the initial gauntlet).