Sub-realtime simulation of a neuronal network of natural density

Full scale simulations of neuronal network models of the brain are challenging due to the high density of connections between neurons. This contribution reports run times shorter than the simulated span of biological time for a full scale model of the local cortical microcircuit with explicit representation of synapses on a recent conventional compute node. Realtime performance is relevant for robotics and closed-loop applications while sub-realtime is desirable for the study of learning and development in the brain, processes extending over hours and days of biological time.

Automated summary

Simulating full-scale neuronal network models of the brain is challenging, but this study achieved shorter run times than the simulated biological time span by using a recent conventional compute node. Realtime performance is important for robotics and closed-loop applications, while sub-realtime performance is desirable for studying learning and development in the brain, which takes hours and days.