Neural models, mathematical descriptions of neural behavior, are an invaluable tool for developing new medical treatments and understanding how the nervous system works. But as researchers discover more information about the nervous system, these models become more complicated. As a result, many modern neural models require powerful computer hardware, such as supercomputers, in order to be simulated and studied. Unfortunately, these systems are expensive and difficult to use. This project will create a low-cost, user-friendly, and computationally powerful system for neural modeling based on a technology called field-programmable gate arrays (FPGAs). This project will develop the user-friendly interface tools for creating neuron models on FPGAs, the software that turns a user's model description into an FPGA-compatible program, and a low-cost hardware platform that will maximize the computational power of FPGAs.
Our project will produce a product that will allow neuroscientists and physiologists to better understand the function of the nervous system, and to perform novel experiments interfacing neural models with biological neurons. By using this system, researchers will be able to develop novel treatments for treating neurological disorders and repairing traumatic neural injury.
| Weinstein, Randall K; Church, Christopher T; Lebsack, Carl S et al. (2009) SIMENGINE: a low-cost, high-performance platform for embedded biophysical simulations. Conf Proc IEEE Eng Med Biol Soc 2009:4238-41 |
