Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex

Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community. [Display omitted] •Two network models of the mouse primary visual cortex are developed and released•One uses compartmental-neuron models and the other point-neuron models•The models recapitulate observations from in vivo experimental data•Simulations identify experimentally testable predictions about cortex circuitry Billeh et al. systematically integrate multi-modal data about neuron types, connectivity, and sensory innervations to create biologically realistic models of the mouse primary visual cortex at two levels of resolution, shared freely as a community resource.