SIMULATION-DRIVEN DYNAMIC CLAMPING OF NEURONS
We describe an experimentation environment that enables large-scale numerical simulations of neural microphysiology to be fed back onto living neurons in-vitro via dynamic wholecell patch clamping - in effect making living neurons and simulated neurons part of the same neural circuit. Owing to high computational demands, the experimental testbed will be dispersed over a local area network comprising several high performance computing resources. Parallel execution, including feedback between the simulation components, will be managed by the Tarragon, a programming model and run time library that supports asynchronous data driven execution. Tarragon's execution model matches the underlying dynamics of Monte Carlo simulation of diffusive processes and it masks the long network latencies entailed in coupled dispersed simulations. We discuss Tarragon and show how its data driven execution model can be used to dynamically feed back the results of a neural circuit simulation onto living cells in order to better understand the underlying signaling pathways between and within living cells.