An integrated recording system using an asynchronous pulse representation

Abstract

A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. It demonstrates the first step in the development of a complete implanted wireless solution with fully integrated circuit architecture. A recording experiment comparing in parallel a commercial recording system (Tucker-Davis Technology (TDT)) and the UF's custom solution (FWIRE) is set up to compare performance. The novel aspect of the UF system is that the analog signal is represented by an asynchronous pulse train, which provides a low-power, low-bandwidth, noiseresistant means for coding and transmission. Taking advantage of neural firing features, the pulse-based approach uses only 3K pulses/second to record a 25 kHz bandwidth signal from a hardware neural simulator.I.

A toy model for the auditory system that exploits stochastic resonance

“…It is interesting to note that a LCD produces both detection and a kind of pulse-train encoding similar to that found in dedicated electronic circuits [36]: the amplitude of sub-threshold stimuli is encoded into the frequency of threshold crossings. The incoming stimuli can be sub-threshold and therefore undetectable.…”