  Cortical microcircuits are very complex networks, but they are composed of a
relatively small number of stereotypical motifs. Hence one strategy for
throwing light on the computational function of cortical microcircuits is to
analyze emergent computational properties of these stereotypical microcircuit
motifs. We are addressing here the question how spike-timing dependent
plasticity (STDP) shapes the computational properties of one motif that has
frequently been studied experimentally: interconnected populations of pyramidal
cells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental
studies suggest that these inhibitory neurons exert some form of divisive
inhibition on the pyramidal cells. We show that this data-based form of
feedback inhibition, which is softer than that of winner-take-all models that
are commonly considered in theoretical analyses, contributes to the emergence
of an important computational function through STDP: The capability to
disentangle superimposed firing patterns in upstream networks, and to represent
their information content through a sparse assembly code.
