Multi-area spiking network models of macaque and humancortices

Understanding the wiring of the brain at the micro-, meso- and macroscale and its influence onneuronal activity is a fundamental problem in neuroscience. Here we present a multi-scale spikingnetwork model of all vision related areas of macaque cortex [1] using the NEST simulator andoutline how we aim to simulate human visual cortex.The connectivity map in our model of the macaque visual cortex integrates data on corticalarchitecture and axonal tracing data into a consistent multi-scale framework and predicts theconnection probability between any two neurons based on their types and locations within areas andlayers [1]. Simulations using this connectivity map reveal a stable asynchronous irregular groundstate with heterogeneous activity across areas, layers and populations [2]. The model of humanvisual cortex will make use of this framework, replacing neuron densities, laminar thicknesses, andcortico-cortical connectivity by estimates for the human brain. To set up the framework, we willfirst model a full cortical hemisphere using published data on cortical architecture [3]. Human-macaque homologies and DTI data will provide reference values for comparison of the cortico-cortical connectivity map. These models will help to elucidate how detailed connectivity of cortexshapes its dynamics on multiple scales and how prominent features of cortical activity can beexplained by population-level connectivity