Rain and NCS 5 benchmarks

The primary objective of the Brain Computation lab at University of Nevada, Reno is to discover principles and develop models of social intelligence in an artificial agent, with biology as basis. To help with this aim, a complex and relatively biologically realistic spiking neural network simulator was developed. This is the NeoCortical Simulator version 5 (NCS 5) which is capable of efficiently simulating large neural networks (more than 10,000 cells and 1,000,000 synapses) using a parallel cluster. The work done in this thesis develops neural network models which exhibit the principle of background activity present in a live biological brain using NCS. The principle of Recurrent Asynchronous Irregular Network (RAIN) might provide a basis for developing more advanced human aspects of memory, learning, consciousness, and pattern recognition and various other application fields. Furthermore, benchmarks were done to test neural networks used in a Virtual Social Robot (VSR) loop. Results of these benchmarks showed capabilities of our cluster and current software which would prove vital for future upgrades and design of neural network models using NCS.