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A digital methodology integrating experimental and theoretical neuroscience

Ross Snider

Montana State University

A digital methodology integrating experimental and theoretical neuroscience is being developed by the creation of a reconfigurable on-line modeling platform (ROMP). The platform will perform real-time analysis of multi-channel data streams for data-driven neural simulations and modeling. The computational architecture is a distributed real-time system of modular design consisting of computational nodes that contain a floating-point digital signal processor (DSP) and a field programmable gate array (FPGA). Configuring the system as a multi-dimensional mesh will allow it to scale in order to process an arbitrary number of real-time data streams. The platform will be used to aid the discovery process where neural encoding schemes through which sensory information is represented and transmitted within a nervous system will be uncovered. The system will enable real-time decoding of neural information streams and it will allow neuronal models to be inserted in simple nervous systems. Allowing experimental perturbation of neural signals while in transit between peripheral and central processing stages will provide an unprecedented degree of interactive control in the analysis of neural function, and could lead to major insights into the biological basis of neural computation.