We have constructed a FPGA-based "early neural circuit simulator" to model the first two stages of stimulus encoding and processing in the rat whisker system. Rats use tactile input from their whiskers to extract object features such as size and shape. We use the simulator to examine the plausibility of the hypothesis that neural circuits in the rat's brain compute gradients of radial distance across the whisker array to make predictions about the environment. This prediction could be a component of a feed-forward signal that guides the navigation behavior of the rat. The use of a FPGA is highly suitable for such an application, because the computation involved in this system is a massively parallel problem. For our applications, we determined that a Cyclone II FPGA could simulate up to 14 neurons in parallel in just 265 ns achieving a 386-fold speedup over the software implementation of the same model.