I'm making a model of cortex with an excitatory layer (e.g. layer 2/3 pyramidal neurons) and an inhibitory layer (e.g. gabaergic interneurons). Right now I'm refining the connection matrix. I have the option to eliminate reciprocal connections where neuron A connects to neuron B and B back to A. This would affect the extent of positive feedback in the system. I would like to base this on biology. I did a quick search for this and didn't find exactly what I was looking for. Hoping you might know answer or a relevant paper offhand.
I know that identifying a synapse between two cells can be done in various ways with various trade-offs. Serial electron microscopy would give the most detail, but serial EM reconstructions haven't even been achieved of much more than a single neuron, much less a group. Fluorescence based methods often require some interpretation. Dual patch clamp electrophysiology might be the best approach but is low yield.
Also, if this isn't known, that's good to know as well.
Thanks in advance.