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In the past decade, the cell-type specific connectivity and activity of localcortical networks have been characterized experimentally to some detail. Inparallel, modeling has been established as a tool to relate network structureto activity dynamics. While the available connectivity maps have been used invarious computational studies, prominent features of the simulated activitysuch as the spontaneous firing rates do not match the experimental findings.Here, we show that the inconsistency arises from the incompleteness of theconnectivity maps. Our comparison of the most comprehensive maps (Thomson etal., 2002; Binzegger et al., 2004) reveals their main discrepancies: thelateral sampling range and the specific selection of target cells. Taking theminto account, we compile an integrated connectivity map and analyze the unifiedmap by simulations of a full scale model of the local layered cortical network.The simulated spontaneous activity is asynchronous irregular and the cell-typespecific spontaneous firing rates are in agreement with in vivo recordings inawake animals, including the low rate of layer 2/3 excitatory cells. Similarly,the activation patterns evoked by transient thalamic inputs reproduce recent invivo measurements. The correspondence of simulation results and experimentsrests on the consideration of specific target type selection and thereby on theintegration of a large body of the available connectivity data. The cell-typespecific hierarchical input structure and the combination of feed-forward andfeedback connections reveal how the interplay of excitation and inhibitionshapes the spontaneous and evoked activity of the local cortical network.

The cell-type specific connectivity of the local cortical network explains prominent features of neuronal activity