title: Real-time million-synapse simulation of rat barrel cortex.
abstract: Simulations of neural circuits are bounded in scale and speed by available computing resources, and particularly by the differences in parallelism and communication patterns between the brain and high-performance computers. SpiNNaker is a computer architecture designed to address this problem by emulating the structure and function of neural tissue, using very many low-power processors and an interprocessor communication mechanism inspired by axonal arbors. Here we demonstrate that thousand-processor SpiNNaker prototypes can simulate models of the rodent barrel system comprising 50,000 neurons and 50 million synapses. We use the PyNN library to specify models, and the intrinsic features of Python to control experimental procedures and analysis. The models reproduce known thalamocortical response transformations, exhibit known, balanced dynamics of excitation and inhibition, and show a spatiotemporal spread of activity though the superficial cortical layers. These demonstrations are a significant step toward tractable simulations of entire cortical areas on the million-processor SpiNNaker machines in development.
authors.affiliation: School of Computer Science, The University of Manchester Manchester, UK ; Laboratory for Neural Circuit Theory, RIKEN Brain Science Institute, Wakoshi Saitama, Japan.
authors.forename: Thomas
authors.initials: T
authors.lastname: Sharp
authors.affiliation: Faculty of Life Sciences, The University of Manchester Manchester, UK.
authors.forename: Rasmus
authors.initials: R
authors.lastname: Petersen
authors.affiliation: School of Computer Science, The University of Manchester Manchester, UK.
authors.forename: Steve
authors.initials: S
authors.lastname: Furber
keywords: SpiNNaker; barrel; large scale; real time; simulation