  Cortical circuits are characterized by exquisitely complex connectivity
patterns that emerge during development from undifferentiated networks. The
development of these circuits is governed by a combination of precise molecular
cues that dictate neuronal identity and location along with activity dependent
mechanisms that help establish, refine, and maintain neuronal connectivity.
Here we ask whether simple plasticity mechanisms can lead to assembling a
cortical microcircuit with canonical inter-laminar connectivity, starting from
a network with all-to-all connectivity. The target canonical microcircuit is
based on the pattern of connections between cortical layers typically found in
multiple cortical areas in rodents, cats and monkeys. We use a computational
model as a proof-of-principle to demonstrate that classical and reverse
spike-timing dependent plasticity rules lead to a formation of networks that
resemble canonical microcircuits. The model converges to biologically
reasonable solutions provided that there is a balance between potentiation and
depression and enhanced inputs to layer 4, only for a small combination of
plasticity rules. The model makes specific testable predictions about the
learning computations operant across cortical layers and their dynamic
deployment during development.
