Reducing higher order network structure in a neocortical microcircuit model. (A1) Neurons in the neocortical microcircuit (NMC-) model. (A2) Deriving synaptic connectivity between neocortical neurons: Connectivity in the NMC-model is based on appositions of dendrites and axons (Reimann et al., 2015). Connectivity in the control cloud-model considers overlap of average dendritic and axonal clouds (Reimann, Horlemann, et al., 2017). (B1) We computed network properties for seven statistical instantiations of the microcircuit (apposition-based connectomes AC1–7, orange diamonds and red star; Markram et al., 2015), and simulated one of them in this study (the NMC-model with connectome AC1, red star). Additionally, we studied versions of the model using the existing NMC-neurons, but synaptic connectivity derived according to the cloud-based approach (cloud-connectomes CC1–5, blue diamonds). We then implemented one of the alternative connectomes within the existing synapses of the NMC-neurons, resulting in the cloud-model that we simulated, with connectome C1* (blue star). The rewiring of the cloud-model was restricted to excitatory connections. (B2) Number of connections across connectomes. By design, the cloud-connectomes CC1–5 have the same number of connections as the NMC-model connectome AC1. However, the connectome implemented in the cloud-model CC1* has 0.12% fewer connections than CC1 because of a mismatch in new connections and available synapses (see Figure 2A). To control for this loss, we generate a copy of the NMC-model with the same fraction of excitatory connections randomly removed, the NMC*-model (green star).